Cancer treatment and research最新文献

{"title":"Clinical Trials and Translational Advances in Metabolic Targeting.","authors":"Hariharan Thirumalai Vengateswaran, Mohammad Habeeb, Huay Woon You, Ciniraj Raveendran","doi":"10.1007/978-3-032-21861-2_13","DOIUrl":"10.1007/978-3-032-21861-2_13","url":null,"abstract":"<p><p>Targeting metabolic pathways provides novel therapeutic prospects as metabolic reprogramming is becoming more widely recognized as a characteristic of a variety of disorders. Despite preclinical research and clinical trials demonstrating the potential of metabolic treatments, the complicated nature and flexibility of cellular metabolic networks prevent their advancement into effective treatments. Compared to conventional methods, metabolism-based treatment may be able to interfere with important functions in diseased cells and their surroundings, allowing for more individualized and accurate treatments. However, there are still challenges associated with overcoming variability and resistance, which highlights the necessity of advanced single-cell analysis methods. Personalizing metabolic therapies and optimizing treatment plans for individual patients are becoming feasible with the integration of artificial intelligence (AI) and machine learning (ML). Furthermore, patient stratification depends significantly on the application of metabolomics and advanced imaging methods, which allow for a more accurate decision of treatment modalities. This chapter provides a comprehensive overview of recent clinical trials and translational advancements in metabolic targeting, with a focus on small-molecule inhibitors and multi-omics technologies. New developments in metabolic research, from mechanistic understanding to clinical applications, are transforming the biomedical treatment while offering novel opportunities for disease management rather than traditional approaches.</p>","PeriodicalId":9486,"journal":{"name":"Cancer treatment and research","volume":"195 ","pages":"249-266"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147962320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolic Cross Talk in the Tumor Microenvironment.","authors":"Chinmay Das, Somya Ranjan Dash, Biswajit Das, Subhajit Chatterjee, Tithi Parija","doi":"10.1007/978-3-032-21861-2_7","DOIUrl":"10.1007/978-3-032-21861-2_7","url":null,"abstract":"<p><p>The tumor microenvironment (TME) is a dynamic network of diverse cellular and noncellular components that interact with malignant cells to influence cancer progression, immune evasion, metastasis, and the development of therapeutic resistance. The major constituents of the TME include malignant cells, immune cells, stromal cells, endothelial cells (ECs), pericytes, adipocytes, nerve cells, and the extracellular matrix (ECM). Findings revealed that a dynamic metabolic crosstalk occurs continuously within the tumor niche, leading to metabolic rewiring in the tumor resident cells that supports cancer progression under nutrient deprivation, hypoxia, and acidosis conditions in TME. This chapter provides a comprehensive overview of various types of metabolic interactions between malignant cells and the diverse cellular components of the TME, including autocrine, paracrine, juxtacrine, and endocrine-like communication, and highlights the role of key metabolites involved in this type of communication. Thus, the interplay between malignant and tumor-resident cells emphasizes their metabolic interactions that promote drug resistance. Additionally, the chapter explores the molecular mechanisms and signaling pathways triggered by this exchange of metabolites. The chapter also explores the molecular mechanisms and signaling pathways triggered by metabolite exchange and clarifies how dysregulated metabolic reprogramming contributes to cancer progression and drug resistance. Therefore, understanding these complex metabolic interactions within the tumor niche provides critical insights for developing novel therapeutic approaches that target the metabolic vulnerabilities of the malignant cells.</p>","PeriodicalId":9486,"journal":{"name":"Cancer treatment and research","volume":"195 ","pages":"121-154"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147962259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lipid Metabolism and Oncogenesis.","authors":"Mirunalini Gobinath, Pratik Phalke, Parikshit Roychowdhury, Alberto Ouro Villasante, Naina Mohamed Pakkir Maideen","doi":"10.1007/978-3-032-21861-2_4","DOIUrl":"10.1007/978-3-032-21861-2_4","url":null,"abstract":"<p><p>Lipid metabolism is important for processes, such as tumor progression, because cancer cells undergo metabolic changes that assist in maintaining their growth, survival, and metastasis. During the development, cancer cells usually adapt to several changes in the tumor microenvironment (TME) and immune modulation. In tumor progression, overexpression of enzymes such as fatty acid (FA) synthase and other related oncogenes in de novo lipid biosynthesis occurs, thus promoting angiogenesis and related growth factors. In recent research, the role of sphingosine-1-phosphate, which activates inflammatory signaling molecules, has been explored in depth. Subsequently, abnormal cholesterol homeostasis, oxidation of FAs, and phospholipid (PL) metabolism might provoke cancer metastasis and tumor evasion. Thus, lipid metabolism has an important role in cancer biology in promoting tumor progression. Consequently, by understanding these molecular mechanisms of lipid biosynthesis in cancer development and progression, it might help to discover novel therapeutic strategies for treating several types of cancers and alleviate immunotherapy-resistant tumors and chemoresistance. This chapter deals with a comprehensive overview of lipid metabolic pathways, response to oxidative stress, and their contribution toward the formation of tumor cells and oncogenesis.</p>","PeriodicalId":9486,"journal":{"name":"Cancer treatment and research","volume":"195 ","pages":"79-94"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147962284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence and Machine Learning Approaches in Designing Immunotherapy in Cancer.","authors":"Lokesh Seth, Colton Ladbury, Arya Amini","doi":"10.1007/978-3-031-97242-3_2","DOIUrl":"10.1007/978-3-031-97242-3_2","url":null,"abstract":"<p><p>Artificial intelligence (AI) and machine learning (ML) are revolutionizing cancer immunotherapy by addressing the complex interplay between cancer and the immune system. This chapter explores how AI technologies enhance immunotherapy development across multiple domains: antibody design, response prediction, biomarker identification, and T-cell target discovery. In therapeutic antibody design, AI improves efficiency through predictive modeling of antibody-antigen interactions, structure prediction tools, generative models that create novel antibody sequences, and developability optimization. Clinical applications include AI-powered systems that predict immunotherapy responses using multi-omics data integration, helping distinguish pseudoprogression from true disease progression. Beyond conventional biomarkers like programmed cell death protein 1, AI enables identification of additional markers including tumor mutational burden, microsatellite instability, immune cell infiltration patterns, and novel genomic alterations. Multi-omics approaches leverage AI to synthesize diverse data types, uncovering complex biomarker signatures that more accurately predict treatment outcomes. For T-cell target identification, next-generation immunoediting platforms like Gritstone's EDGE™ system exemplify AI-powered approaches that precisely identify neoantigens by integrating sequencing technologies with sophisticated prediction algorithms (Table 2.1). These platforms support both personalized and shared antigen approaches to immunotherapy, potentially enhanced through integration with innate immune pathways. Despite remarkable progress, challenges persist in addressing tumor heterogeneity, immune evasion mechanisms, and technical limitations in prediction algorithms. The continued refinement of AI approaches, expansion to diverse cancer types, and integration with complementary therapeutic modalities represent promising future directions. Overall, AI and ML are poised to transform cancer immunotherapy by enabling more precise, effective, and personalized treatment approaches that harness the immune system's power against cancer.</p>","PeriodicalId":9486,"journal":{"name":"Cancer treatment and research","volume":"129 ","pages":"17-32"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144943861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phenotypic Plasticity, Non-genetic Mechanisms, and Immune Drug Resistance in Cancer.","authors":"Prakash Kulkarni, Sravani Ramisetty, Debora Bruno, TingTing Tan, Amartej Merla, Ravi Salgia","doi":"10.1007/978-3-031-97242-3_14","DOIUrl":"10.1007/978-3-031-97242-3_14","url":null,"abstract":"<p><p>Cancer immunotherapy is a major advancement in the field. It works by stimulating the patient's immune system to recognize and destroy cancer cells. Several different types of cancer immunotherapies have been developed, such as T-cell therapy, immune checkpoint inhibitors, monoclonal antibodies, cancer vaccines, and many others, which can result in sustainable responses in patients with a wide range of metastatic diseases. Additionally, immunotherapy drugs are being combined with chemotherapy and other targeted therapies to treat a variety of cancer types. Despite the promising results, several challenges remain, such as the almost inevitable immune resistance, drug-related toxicity, and the lack of established and reliable predictive biomarkers to predict toxicity and/or discern a patient's response to immunotherapy. In this chapter, we summarize the mechanisms underlying cancer immunotherapy resistance, especially the contributions of phenotypic plasticity and the underlying non-genetic mechanisms. Furthermore, recent developments in preventing relapses following treatment so that the efficacy of immunotherapy can be improved are also briefly discussed. Finally, the positive impact of an interdisciplinary \"Team Medicine\" approach to personalize cancer immunotherapy for each patient is highlighted.</p>","PeriodicalId":9486,"journal":{"name":"Cancer treatment and research","volume":"129 ","pages":"309-324"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144944084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Colorectal Cancers and Immunotherapy.","authors":"Farzad Teymouri, Gagandeep Brar","doi":"10.1007/978-3-031-97242-3_5","DOIUrl":"10.1007/978-3-031-97242-3_5","url":null,"abstract":"<p><p>Colorectal cancer (CRC) is a growing concern worldwide, particularly affecting younger populations in recent years. The progression of CRC involves diverse molecular pathways, each contributing to how the tumor behaves and responds to treatment. The immune system is crucial in detecting and destroying cancer cells, but tumors can avoid immune destruction through various strategies, such as altering antigen expression or reshaping their environment to suppress immune activity. These escape mechanisms have prompted the development of immunotherapy, which has significantly improved outcomes for patients with specific genetic profiles like microsatellite instability-high (MSI-H) or mismatch repair deficiency (dMMR). Drugs such as pembrolizumab, nivolumab, and others have demonstrated notable clinical benefits in these populations. Research is now expanding to evaluate immunotherapy in earlier stages of disease and in combination with other treatments like chemoradiation, even in patients without traditional predictive biomarkers. Ongoing studies are also exploring novel immune targets and combinations to enhance effectiveness and broaden access to these therapies. Understanding the interaction between tumor biology and the immune system is essential for advancing personalized care in CRC.</p>","PeriodicalId":9486,"journal":{"name":"Cancer treatment and research","volume":"129 ","pages":"83-102"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144943953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immunotherapy in Renal Cell Carcinoma.","authors":"Miguel Zugman, Salvador Jaime-Casas, Peter D Zang, Koral Shah, Charles B Nguyen","doi":"10.1007/978-3-031-97242-3_13","DOIUrl":"10.1007/978-3-031-97242-3_13","url":null,"abstract":"<p><p>There have been tremendous advancements in immunotherapy approaches for patients with renal cell carcinoma (RCC) from the initial interleukin-2 era to the current immune checkpoint inhibitor (ICI) combinations. Several ICI-based therapies have greatly improved outcomes for patients with RCC with the potential for durable responses for a subset of patients. In this chapter, we review the data of key frontline ICI-based combinations for RCC in the metastatic setting and recent data on adjuvant immunotherapy. We also discuss recent data on the role of immunotherapy rechallenge following prior ICI treatment as well as emerging novel immunotherapy strategies with chimeric antigen receptor (CAR) T and gut microbiome interventions. Lastly, we highlight a multidisciplinary team-based approach for patients with RCC treated with ICI including management of immune-related adverse events as well as potential role of cytoreductive nephrectomy in an evolving treatment landscape.</p>","PeriodicalId":9486,"journal":{"name":"Cancer treatment and research","volume":"129 ","pages":"293-308"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144944023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immunotherapy in Melanoma.","authors":"Yan Xing, Helena T Wu, Swapnil Rajurkar, Tingting Tan, Vanessa Hsu","doi":"10.1007/978-3-031-97242-3_9","DOIUrl":"10.1007/978-3-031-97242-3_9","url":null,"abstract":"<p><p>This chapter explores systemic treatment strategies for cutaneous melanoma across neoadjuvant, adjuvant, and Stage IV settings. Neoadjuvant therapy aims to reduce tumor burden pre-surgery, primarily using immune checkpoint inhibitors like nivolumab plus ipilimumab, showing promising response rates. Adjuvant therapy, post-resection, leverages immunotherapy (e.g., nivolumab) and targeted therapies (e.g., dabrafenib plus trametinib) to prevent recurrence in high-risk patients, improving relapse-free survival. Stage IV systemic treatment addresses metastatic disease, employing immunotherapy (nivolumab, pembrolizumab) and targeted mitogen-activated protein kinase (MAPK) pathway inhibitors (dabrafenib plus trametinib) for BRAF-mutant cases, while BRAF wild-type patients benefit from nivolumab-relatlimab or combination therapies. Tables summarize key regimens, efficacy, and toxicities. Content aligns with clinical guidelines, with updates on emerging therapies like tumor-infiltrating lymphocytes (TIL). These approaches enhance survival and treatment-free intervals, tailored to mutation status and disease stage.</p>","PeriodicalId":9486,"journal":{"name":"Cancer treatment and research","volume":"129 ","pages":"173-186"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144944004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breast Cancer Immunotherapy: A Team Science Approach.","authors":"Max Duesberg, Alexis LeVee, Hannah Chang, Karen Tsai, Bridget Crossman, Marissa Tadi, Sharon Xu, Deric Wheeler, Irene Kang","doi":"10.1007/978-3-031-97242-3_4","DOIUrl":"10.1007/978-3-031-97242-3_4","url":null,"abstract":"<p><p>Immunotherapy has reshaped the treatment landscape of several malignancies, including breast cancer. While historically considered less immunogenic, breast cancer-particularly the triple-negative subtype (TNBC)-has demonstrated responsiveness to immune checkpoint inhibitors (ICIs). TNBC is characterized by higher tumor mutational burden, elevated PD-L1 expression, and increased tumor-infiltrating lymphocytes, making it a leading focus of immunotherapy development. In metastatic TNBC with PD-L1 expression, trials such as KEYNOTE-355 have shown improvements in progression-free and overall survival with the addition of the ICI, pembrolizumab to chemotherapy, leading to regulatory approval. In early-stage TNBC, KEYNOTE-522 established a neoadjuvant chemotherapy plus ICI as the standard of care for stage II and III tumors. This was based on improved pathologic complete response and event-free survival in this pivotal clinical trial regardless of PD-L1 expression. ICIs in other subtypes, such as HER2-positive and hormone receptor-positive/HER2-negative disease, remain under active investigation. Ongoing studies are also exploring novel strategies including dual immune checkpoint blockade, cellular therapies (e.g., CAR-T, TILs), cancer vaccines, and rational combinations with targeted agents and antibody-drug conjugates (ADCs). Biomarkers such as PD-L1, tumor mutational burden, immune gene signatures, and the gut microbiome are being evaluated to refine patient selection and predict response. Additionally, effective management of immune-related toxicities is critical, particularly in curative-intent settings. As the role of immunotherapy expands, a multidisciplinary, biomarker-driven approach will be essential to optimize outcomes and broaden its applicability across breast cancer subtypes.</p>","PeriodicalId":9486,"journal":{"name":"Cancer treatment and research","volume":"129 ","pages":"67-82"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144943934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel Immune Modulatory Agents in the Treatment of Non-small Cell Lung Cancer.","authors":"Amanda Reyes, Matthew Lee","doi":"10.1007/978-3-031-97242-3_8","DOIUrl":"10.1007/978-3-031-97242-3_8","url":null,"abstract":"<p><p>Lung cancer is the leading cause of cancer-related mortality worldwide. Non-small cell lung cancer (NSCLC) makes up the large majority of lung cancer diagnoses. After the discovery of immune modulators or immunotherapy, treatments that could utilize the patient's own immune system to target malignant cells, the landscape of lung cancer treatment, NSCLC in particular, has greatly evolved with vast improvements in outcomes and survival. Currently, immune checkpoint inhibitors (ICI) have had the greatest impact on the current treatment of non-driver mutated non-small cell lung cancer. Unfortunately, resistance to treatment whether primary or secondary, remains a concern. To overcome resistance, investigators have sought combination immune modulator treatments and have even identified novel agents to utilize, including adoptive cellular therapies, antibody-drug conjugates, and vaccines. Some of these agents have been more successful than others with combination strategies currently leading the way but there are some limitations. Other agents are early in development and will need to await further data before determining the impact on lung cancer treatment. Immunotherapy or immune modulatory agents remain an essential aspect of NSCLC treatment and continue to be the subject of novel research and development.</p>","PeriodicalId":9486,"journal":{"name":"Cancer treatment and research","volume":"129 ","pages":"157-172"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144944018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}