Cancer genomics is an evolving field driven by advances in laboratory and computational technologies, enabling a detailed examination of the molecular and cellular aspects of cancer. This field goes beyond DNA analysis to include gene expression, proteins, and other molecular features, helping to detect crucial alterations that could lead to the disease. With the advent of new data types, enhanced data quality, and cheaper sequencing methods, researchers are achieving a comprehensive understanding of cancer's mechanisms. Identifying cancer-causing changes allows scientists to better grasp the molecular foundations of cancer growth, metastasis, and resistance to treatment. This knowledge is enhanced by clinical data on patient treatment responses, laboratory studies using cell lines and model organisms, and the analysis of large genomic datasets. Sharing these datasets globally is crucial for advancing cancer research, facilitating discoveries, and enabling precision medicine—a personalized treatment approach based on the patient's tumor genetics. Genomic insights are revolutionizing diagnosis and treatment, leading to the development of targeted therapies. These treatments specifically target cancer cell abnormalities, minimizing damage to normal cells and reducing toxicity compared to traditional therapies like chemotherapy and radiation. Examples include Imatinib for leukemia, Trastuzumab for breast cancer, and Erlotinib and Gefitinib for lung cancer, among others. Furthermore, cancer genomics is refining the classification of cancer types and subtypes based on genetic characteristics, offering patients more accurate diagnoses and personalized treatments. This molecular taxonomy has already benefited patients with various cancers, such as breast cancer, diffuse large B cell lymphoma, endometrial cancer, and lung cancer, demonstrating the potential of precision medicine to improve care and treatment outcomes.

Keywords: cancer genomics, oncogenomics, genomic profiling, precision medicine, targeted therapies, personalized cancer treatment

Cancer immunotherapy is a hot area of current oncology research, with its core focus on activating or enhancing the body's immune system's ability to recognize and kill cancer cells. However, cancer cells possess complex heterogeneity and dynamics, which affect the efficacy of immunotherapy in many ways. Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool in recent years, providing us with an unprecedented insight into the cellular heterogeneity and dynamics within tumors. This technology has revolutionized our understanding of cancer biology, especially in the context of cancer immunotherapy. By enabling researchers to analyze individual cells, scRNA-seq allows them to identify distinct cell populations, track cellular responses to treatments, and discover new therapeutic targets. This collection aims to compile cutting-edge research in this field and explore the various applications of single-cell RNA sequencing in cancer immunotherapy.

This collection will cover the following topics: 1. The latest advances in single-cell RNA sequencing technology in cancer immunotherapy, including research on technology optimization and data interpretation; 2. Using single-cell RNA sequencing to reveal the characteristics of immune cell subgroups in the tumor microenvironment and their interaction mechanisms with cancer cells; 3. Analyzing the molecular basis of immune therapy response and resistance through single-cell RNA sequencing, exploring new biomarkers and therapeutic targets; 4. Combining single-cell RNA sequencing with clinical studies of immunotherapy to assess treatment outcomes, predict patient prognosis, and optimize treatment plans.

Keywords: cancer immunotherapy, single-cell RNA sequencing, therapeutic targets, tumor microenvironment, treatment response