Immune checkpoint inhibitors (ICIs) such as anti-PD-1 and anti-PD-L1 antibodies are highly effective against many types of cancer, yet durable responses are limited to a subset of patients highlighting the need for the development of effective biomarkers to predict prognosis and efficacy. Currently, PD-L1 expression in tumors, microsatellite instability (MSI) or mismatch repair deficiency (dMMR), and tumor mutation burden (TMB) are known as biomarkers for cancer immunotherapy but are not sufficient. Combination therapy with immune checkpoint inhibitors and chemotherapy or radiation therapy, as well as diverse therapies targeting intra-tumoral regulatory T cells have been described, but there are currently no unifying biomarkers that are applicable to clinically, a simple, fast, non-invasive method that can yield biomarkers of disease with a minimal adverse effect on patients is desirable. Recent findings suggest that the balancing of effector T cells and regulatory cells in the tumor microenvironment is associated with cancer progression and prognosis. Cells and molecules involved in the control of cancer are complex, and a better understanding of the tumor immune environment will lead to the development of truly effective biomarkers. This topic will focus on novel biomarkers that predict efficacy, prognosis, or the development of adverse events in various cancer immunotherapies, and extensive basic research leading to the development of biomarkers. Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by robust and relevant validation (clinical cohort or biological validation in vitro or in vivo) are out of scope for this topic. We expect a wide range of research, not only in serology, genetics, and immunocytochemistry but also in bacterial flora. Research on the development of novel assays and bioinformatics methods is also welcome: • Non-invasive biomarkers for cancer immunotherapy. • Bulk RNA-seq, scRNA-seq, or Rep-seq methods. • Correlation of tumor immune cells with gut microbiota in tumor immunotherapy. • Impact of Teff and Treg balance in the tumor microenvironment on tumor prognosis. • Inflammatory and immune signatures associated with drug response versus resistance in cancer.

Immunotherapy has revolutionized the treatment of malignancies. Targeting of immune checkpoints cytotoxic T-lymphocyte-associated protein 4, programmed cell death protein 1 (PD-1) and its ligand (PD-L1) has led to improving survival in a subset of patients. Despite their remarkable success, clinical benefit remains limited to only a subset of patients. A significant limitation behind these current treatment modalities is an irregularity in clinical response, which is especially pronounced among checkpoint inhibition. Currently, relevant predictors of cancer immunotherapy response include microsatellite instability-high/deficient mismatch repair (MSI-H/dMMR), expression of PD-L1, tumor mutation burden (TMB), immune genomic characteristics, and tumor infiltrating lymphocytes (TILs). However, none of them have sufficient evidence to be a stratification factor. Moreover, as the combined strategies for effective cancer immunotherapy had been developed in multiple tumors, such as Immunotherapy combined with chemotherapy, radiotherapy, targeted therapy and anti-angiogenesis therapy. Therefore, the development of novel biomarkers endowed with high sensitivity, specificity and accuracy able to identify which patients may truly benefit from the treatment with cancer immunotherapy would allow to refine the therapeutic selection and to better tailor the treatment strategy.

Bladder cancer is one of the most common urological diseases with a high mortality rate and poor prognosis. It is currently ranked as the 10th most common malignancy worldwide. The majority of bladder cancer patients have been found to be diagnosed with non-muscle invasive bladder cancer (NMIBC) and the remaining, are diagnosed with muscle-invasive bladder cancer (MIBC). Although there have been advances in the treatment and therapies provided for bladder cancer patients, the survival rate remains low, primarily due to recurrence and metastasis of the disease following treatment. Surgical treatment is currently the most common form including radical cystectomy which is the standard form of treatment combined with neoadjuvant chemotherapy. However, the 5-year overall survival rate is 50%. Therefore, further studies are required to understand the molecular mechanisms involved in the progression of bladder cancer and identify novel biomarkers to act as a diagnostic tool for patients. There have been many studies involving the detection of biomarkers in bladder cancer in addition to monitoring disease recurrence to understand the impact and predict potential outcomes. A variety of urine biomarkers have been developed to detect bladder cancer and prognostic risk stratification including mutational DNA and the levels of RNA expression. Circulating tumor cells have also been identified as a potential biomarker for bladder cancer patients. However, there are significant challenges as bladder cancer has demonstrated high levels of cellular and molecular heterogeneity and some markers do not have sufficient sensitivity for accurate detection. Therefore, further studies are required to continue to identify new novel biomarkers for bladder cancer. The aim of this Research Topic is to discuss novel biomarkers in bladder cancer and how it impacts the disease progression and the survival rate for bladder cancer patients.

Precision medicine is an emerging practice by which clinicians aim to deliver a personalized treatment program to affected patients based on information gained from their individual clinical and biological profiles. In the context of precise cancer immunotherapy, multi-omics, high-throughput sequencing, big data, and other approaches serve to screen new predictive factors for immunotherapy response and prognosis in cancer patients.

Tumor Immunology and Immunotherapy Integrated Methods - Part A, Volume 635 in the Methods in Enzymology series, continues the legacy of this premier serial with quality chapters authored by leaders in the field. Specific chapters to this release include Deconvolution of the immunological contexture of mouse tumors with multiplexed immunohistochemistry, High-dimensional multiplexed immunohistochemical characterization of immune contexture in human cancers, Multiplex assay by IHC for melanoma tumor microenvironment evaluation, Characterization of the tumor immune microenvironment by multispectral image analysis of multiplex immunofluorescence images, Phenotyping of immune cells in situ using multispectral imaging quantification, and much more. - Authored by leaders in the field of enzymology - Provides a comprehensiveness level of discussion on the field - Presents a highly specialized group of topics that delve deep into new updates and future prospects

Translational medicine was first mentioned in 1992 by Choi D. W and has since become a rapidly expanding area within biomedical research. It is based on the ‘bench to bedside’ approach, which describes it’s relationship between basic science and clinical practice. In 2008, Drs Conway and Dougherty provided a 3 step process to translational medicine and how it should be implemented to transform healthcare systems. The first step is the translation of basic science into clinical research (T1). The second step (T2) focuses on making healthcare more patient specific, basing itself on providing ‘the right treatment for the right patient in the right way at the right time’. T2 also looks for this science to be translated into practice guidelines for clinicians, policy makers and the patients themselves. The final step (T3) addresses the ‘how’ of implementing these ideas, so that high quality healthcare can be delivered reliably to all patients in all settings of care. T3 activities would include policy changes that could serve to bring about meaningful change towards this goal. Cancer is a major public health problem worldwide. Clarifying the etiology and pathogenesis of cancer is of great significance to the prevention, diagnosis, and treatment of the disease. The bench to bedside pattern can be a useful method for cancer-related studies. This Research Topic aims to highlight the emerging role of oncogenetics in cancer, and discuss potential challenges of diagnosis and treatment, from the bench to the bedside.

This Research Topic is the second volume of the “Community Series in Novel Biomarkers for Predicting Response to Cancer Immunotherapy". Please see Volume I here. Immunotherapy has revolutionized the treatment of malignancies. Targeting of immune checkpoints cytotoxic T-lymphocyte-associated protein 4, programmed cell death protein 1 (PD-1) and its ligand (PD-L1) has led to improving survival in a subset of patients. Despite their remarkable success, clinical benefit remains limited to only a subset of patients. A significant limitation behind these current treatment modalities is an irregularity in clinical response, which is especially pronounced among checkpoint inhibition. Currently, relevant predictors of cancer immunotherapy response include microsatellite instability-high/deficient mismatch repair (MSI-H/dMMR), expression of PD-L1, tumor mutation burden (TMB), immune genomic characteristics, and tumor infiltrating lymphocytes (TILs). However, none of them have sufficient evidence to be a stratification factor. Moreover, as the combined strategies for effective cancer immunotherapy had been developed in multiple tumors, such as Immunotherapy combined with chemotherapy, radiotherapy, targeted therapy and anti-angiogenesis therapy. Therefore, the development of novel biomarkers endowed with high sensitivity, specificity and accuracy able to identify which patients may truly benefit from the treatment with cancer immunotherapy would allow to refine the therapeutic selection and to better tailor the treatment strategy. This research topic aims to focus on the advances in the discoveries of novel biomarkers for predicting response to cancer immunotherapy in various tumors. We welcome the submission of original research and review articles that include biomarkers in clinical study and applications, as well as technologies or discoveries in experimental approaches.