| theme | Title | Links | Articles |
|---|---|---|---|
| Multiple myeloma (MM) is a haematological malignancy characterized by clonal proliferation of plasma cells in the bone marrow microenvironment. Despite improved survival, MM is still incurable. The interaction between the bone marrow microenvironment and multiple myeloma plasma cells (MMPCs) influences cellular growth and survival, drug resistance, intra-/extra-medullary disease (EMD), and ultimately disease prognosis. Spreading of MMPCs throughout bone marrow (BM) niche and EMD sites, as well PC leukemia (PCL), is an active process involving BM endothelial cells, adhesion molecules, and chemokine receptors. Profiling the intra/extra-MM genomic landscape and resolving its spatial architecture have the potential to uncover the complexities of MM, thus addressing outstanding questions in its biology and potentially leading to the identification of new pharmacological opportunities. This Collection will focus on the application of new high-throughput, high-resolution technologies from the omics field for dissecting the inter- and intra-MM heterogeneity and its translational implication. We encourage Original Research and Review papers focusing on, but not limited to, the following aspects: 1) State of the art and emerging techniques for studying Multiple Myeloma. 2) Omics-based investigations (such as genomics, transcriptomic, proteomics and metabolomics) and multi-omics approaches applied to Multiple Myeloma. 3) Spatial multimodal omics and potential for application in Multiple Myeloma. 4) Bioinformatics and network-based biology analysis in Multiple Myeloma. 5) System Biology in Multiple Myeloma. 6) Trends, challenges, and pitfalls in the field. Keywords: multiple myeloma, microenvironment, cell-cell communication, system biology, omics, biomarker and target identification | Accelerating Multiple Myeloma System Biology Research | https://link.springer.com/collections/eahfdhehjd | 0 |
| This Collection is dedicated to exploring the intricate landscape of cancer, with a special emphasis on cancer stem cells, reactive oxygen species (ROS), antioxidants, and the crucial roles of endoplasmic reticulum stress and oxidative stress in the progression and treatment of cancer. It seeks to uncover the complex biological mechanisms and pathways that are fundamental to the onset, development, and persistence of cancer, spotlighting the pivotal science behind cancer stem cells. These cells, a small but significantly impactful subset within tumors, have the capacity for self-renewal and are key drivers of tumor growth and metastasis, thereby playing a crucial role in the challenge of combating cancer recurrence. Additionally, the Collection delves into the nuanced role of ROS, which serves not only as agents of cellular damage but also as essential signaling molecules that can promote or inhibit cancer progression. This exploration sheds light on the delicate balance between oxidative stress and the body's antioxidant defenses, which is vital in the development and progression of cancer. Moreover, this Collection investigates the impact of oxidative stress and endoplasmic reticulum stress on cellular health, particularly focusing on how an imbalance in ROS can lead to DNA damage, and how stress from misfolded proteins can trigger cellular responses that affect cell survival, apoptosis, and cancer development. These discussions aim to connect these stress mechanisms to the broader understanding of cancer biology. Intended for researchers, clinicians, and students, this collection provides a comprehensive overview of current research findings and theoretical models at the intersection of cancer biology and cellular stress mechanisms. It aims to offer insights into potential therapeutic targets and interventions, with a pronounced emphasis on the role and therapeutic potential of targeting cancer stem cells. This focus is envisioned to contribute significantly to the development of more effective treatments for cancer, addressing both its onset and recurrence. | Advanced in Therapy Targeting Cancer and Cancer Stem Cells | https://link.springer.com/collections/ajhigabaid | 0 |
| The Collection "Advancements in Bioactive Compound-Derived Anticancer Agents" aims to elucidate the evolving landscape of cancer therapeutics by exploring the potential of bioactive compounds as effective anticancer agents. Cancer remains a global health challenge, necessitating continual exploration for novel treatments that exhibit enhanced efficacy and reduced adverse effects. This Collection will serve as a comprehensive platform to showcase the latest advancements, bridging the gap between laboratory discoveries and clinical applications. Bioactive compounds derived from natural sources or synthesized with specific structural characteristics have demonstrated promising anticancer properties in recent research. Delving into the identification, characterization, and mechanistic insights of these compounds, and highlighting their potential as targeted therapies against various cancer types would be the main goal of this Collection. Its scope encompasses a wide array of research domains, including basic science investigations unveiling the molecular mechanisms underlying the anticancer activities of bioactive compounds. Preclinical and clinical investigations evaluating these compounds' safety, efficacy, and therapeutic outcomes in diverse cancer models and patient populations form would be another crucial facet. Additionally, we welcome contributions that explore epidemiological perspectives, elucidating population-based trends, impact assessments, and the potential implications of bioactive compound-derived anticancer agents on public health. The Collection is an opportunity for researchers, clinicians, and epidemiologists to disseminate their cutting-edge findings, discuss challenges, and propose innovative solutions in harnessing bioactive compounds as potential anticancer therapies. It endeavours to accelerate the translation of promising compounds from laboratory discoveries to transformative clinical applications by providing a forum for multidisciplinary dialogue and sharing of diverse insights. Authors are encouraged to submit original research articles, reviews, perspectives, and studies that contribute to advancing our understanding of bioactive compound-derived anticancer agents and their potential role in revolutionizing cancer treatment strategies. | Advancements in Bioactive Compound-Derived Anticancer Agents | https://link.springer.com/collections/jcdhdjiccc | 1 |
| In recent decades, advancements in genetic sequencing and biotechnologies have facilitated the identification of genes linked to fundamental cancer processes marked by dynamic cellular biology. To prevent disease, the activities of these genes require precise regulation, achieved in part through carefully orchestrated post-transcriptional modifications. With over 170 such RNA modifications, including nucleotide substitutions (e.g., A-to-I, C-to-U), methylation (e.g., m6A, m1A, m5C, hm5C, 2'OMe), and pseudourylation (Ψ), epitranscriptomics investigates the consequences of these modifications in human biology and disease. Technological breakthroughs, like high-throughput sequencing, enhance researchers' ability to identify and understand these modifications, propelling the field forward. Epitranscriptomics research, particularly in exploring writers, readers, and erasers of RNA modifications, has rapidly expanded. Post-transcriptional modifications impact both the coding and non-coding genome, challenging the traditional view of non-coding regions as mere "transcriptional noise." These regions are now recognized for their crucial role in regulating gene expression and cellular activity. Disruptions in the non-coding genome contribute to the pathology of various human diseases, including cancer, necessitating tight regulation of non-coding gene expression and activity. This Collection will feature review and original research articles from epitranscriptomics and non-coding genetics experts, primarily focusing on cancer pathogenesis. Contributions should illuminate the progress and challenges in these fields, including but not limited to novel tools, computation approaches, databases for the study of non-coding RNAs and epitranscriptomics in cancer. | Advances in Epitranscriptomics and Non-coding RNAs in Cancer Research | https://link.springer.com/collections/fgfgcaigid | 1 |
| This Collection on "Advances in Immunity and Immunotherapy for Blood Cancers" aims to provide a comprehensive overview of the latest breakthroughs and novel approaches in the field of immunotherapy specifically tailored for the treatment of blood cancers. The Collection seeks to explore the mechanisms of action, clinical efficacy, and safety profiles of these innovative approaches. Blood cancers, including leukemia, lymphoma, and myeloma, are a diverse group of diseases that pose significant challenges in terms of treatment options and patient outcomes. Over the past decade, there have been remarkable advancements in the development and application of immunotherapeutic strategies for blood cancers. We welcome submissions that cover a wide range of topics, including but not limited to immune checkpoint inhibitors, CAR T cell therapy, bispecific antibodies, adoptive cell therapies, and novel immunotherapeutic targets. Authors are also encouraged to submit manuscripts that address challenges in the field, such as resistance to immunotherapy and strategies to overcome it. Additionally, the Collection welcomes submissions that explore combination therapies, personalized treatment approaches, and advancements in understanding the immune microenvironment in blood cancers. Keywords: cancer immunity, immunotherapy, blood cancers | Advances in Immunity and Immunotherapy for Blood Cancers | https://link.springer.com/collections/fabhecfbgj | 1 |
| Lymphomas are a group of haematological malignancies that are amongst the top ten cancers worldwide. Broadly, they may be divided into Hodgkin lymphomas and non-Hodgkin lymphomas of B-cell or T/NK-cell immunophenotypic subtypes. In terms of therapeutics, patients commonly receive multi-agent chemoimmunotherapy in the frontline setting. In the relapsed setting, haematopoetic stem cell transplant and CAR-T therapy remain the only potentially-curative options for eligible patients, with other agents such as targeted small molecule inhibitors, immune checkpoint inhibitors, and novel drugs providing additional options for disease control. Recently, advances in “omic” technologies have provided the opportunity to stratify lymphomas into distinct molecular subtypes, contributing to an improved understanding of disease pathobiology. However, the clinical implications of these findings often remain unclear at this juncture. This Topical Collection aims to collect papers dealing with the latest discoveries in lymphoma, particularly those that impact on clinical management and therapeutics. We welcome both original articles on clinical and translational research on lymphomas, as well as review articles that integrate knowledge in the field. Keywords: Lymphoma; Hematology; Therapeutics; Blood; Genomics | Advances in Lymphoma Discovery and Treatment | https://link.springer.com/collections/aghfdehdgb | 2 |
| Research in oncology has undergone a transformative evolution propelled by advances in biomarker discovery and drug target innovation. Biomarkers that encompass a wide range of biological molecules are essential in the early detection, diagnosis and prognosis of cancer. Advanced next-generation sequencing technology in genomics and proteomics has greatly influenced personalised medicine allowing for more tailored treatment all the while reducing adverse toxicity. Identification of precise drug targets has opened new avenues for cancer therapy. Targeted therapies now can be designed to interfere with specific molecules involved in cancer growth and progression, offering a promising alternative to traditional chemotherapy. These therapies have shown remarkable efficacy and specificity, minimizing damage to healthy tissues and improving the quality of life for patients. The integration of biomarker discovery with drug target innovation represents a paradigm shift in oncology, moving towards a more personalized and effective approach to cancer treatment. This new era in cancer research is marked by the continuous exploration of molecular mechanisms underlying cancer, the development of novel therapeutic agents, and the implementation of advanced diagnostic tools. As a result, the future of oncology holds the promise of improved survival rates, better management of the disease, and ultimately, a higher quality of life for cancer patients. | Advances in Oncology: Biomarker Discovery and Drug Target Innovation | https://link.springer.com/collections/dgcbiaabhc | 0 |
| Cancer prognosis is a critical aspect of oncology that significantly influences treatment decisions and patient outcomes. "Advancing Cancer Prognosis: Integrating Multiomics and Clinical Characteristics" aims to explore the latest developments in predicting the course of cancer by combining insights from multiple omics disciplines and clinical features. This Collection seeks to provide a comprehensive overview of how advancements in multiomics technologies and an in-depth understanding of clinical characteristics can synergistically enhance our ability to prognosticate various cancer types accurately. The importance of advancing cancer prognosis lies in its profound implications for personalized medicine and patient care. Accurate prediction of a patient's prognosis enables clinicians to tailor treatment strategies, optimizing therapeutic interventions for better outcomes. Integrating multiomics data, such as pathomics, radiomics genomics, transcriptomics, and proteomics, with clinical characteristics offers a holistic view of cancer biology. This approach not only refines prognostic accuracy but also opens avenues for targeted therapies and precision medicine. Ultimately, by enhancing our prognostic capabilities, we empower healthcare professionals to make informed decisions, improve patient outcomes, and contribute to the ongoing evolution of cancer care. This Collection aligns with the journal's scope by delving into the intersection of multiomics and clinical characteristics in cancer prognosis. Subtopics will encompass the integration of genomics, transcriptomics, proteomics, and other omics data with traditional clinical features. We encourage submissions that explore novel methodologies, predictive models, and advancements in technology that contribute to refining cancer prognostication. Preferred article types include original research studies, systematic reviews, and meta-analyses. By showcasing diverse research approaches, this Collection aspires to contribute to the journal's mission of advancing knowledge in oncology and promoting evidence-based practices. | Advancing Cancer Prognosis: Integrating Multiomics and Clinical Characteristics | https://link.springer.com/collections/fiegdhhjdg | 12 |
| Cancer is the leading cause of death worldwide. With about 10 million deaths in 2020, innovations in the detection and treatment of cancer are urgently needed. The gold standard for cancer prognosis and diagnosis currently relies on pathologists' evaluation of hematoxylin and eosin (H&E)-stained tumor tissue slides under a microscope, allowing the analysis of tissue structure and composition as well as cell morphology. By examining H&E slides, a pathologist can detect and identify tumor tissue which is important for making therapeutic decisions. However, it is limited with an additional invasive surgical extraction, causing discomfort, pain and risks for the patient. Cytological slides, which examine cells from human tissues or fluids under a microscope, are now being used in many studies for cancer diagnosis and prognosis. These slides are comparably easy to process, quick to perform, virtually painless, cost-efficient and with a minimally invasive procedure. However, manual pathologic and cytopathologic assessment is a highly professional task, which is challenging, time-consuming and requires formal training. Artificial intelligence has facilitated the development of computer-aided systems that assist in clinical diagnosis or treatment planning. Over the last decade, digital pathology and cytology combined with the computing power of advanced artificial intelligence have offered more robust cancer prevention, detection, and individualized therapy forms with faster networks and less expensive storage. This Topical Collection aims to collect papers dealing with artificial intelligence in pathology and cytology for cancer research. Keywords: Artificial Intelligence, Pathology, Cytology, Cancer, Diagnosis, Prognosis, Treatment | Artificial Intelligence in Pathology and Cytology for Cancer Research | https://link.springer.com/collections/ddiebdeeci | 1 |
| Artificial intelligence (AI) is revolutionizing almost every field of science. In the field of clinical trials, AI has the potential to offer unprecedented opportunities to enhance the efficiency, accuracy, and overall success of these studies. Each year, thousands of clinical trials are conducted to test new treatments and interventions, yet many face challenges such as high costs, lengthy durations, and complex data management. In addition, in the field of cancer research, high levels of false positives in phase-II clinical trials often lead to costly and unsuccessful phase-III trials that could have been avoided if more effective testing methods existed. AI has the potential to address these issues by streamlining trial processes, optimizing patient recruitment, and analysing vast amounts of data with remarkable speed and precision. This Collection focuses on the transformative impact of AI in improving clinical trials, exploring various applications and innovations. Key areas include AI-driven patient recruitment strategies that utilize machine learning algorithms to identify and match eligible participants more effectively, thus reducing recruitment times and costs. Additionally, the integration of AI in data analysis and interpretation can lead to more accurate and timely insights, enhancing response evaluation criteria, reduction of the number of false positive trials, and the overall quality of trial outcomes. A critical aspect covered in this Collection is the use of AI to monitor patient responses and adverse events, thereby improving patient safety and trial efficacy. AI-powered platforms can continuously analyze patient data, providing real-time feedback and facilitating adaptive trial designs that can be adjusted based on interim results. This adaptive approach can significantly improve trial success rates and accelerate the development of new therapies. | Artificial Intelligence to Improve Clinical Trial in Cancer Research | https://link.springer.com/collections/dahcehddhi | 0 |