Seminars in cancer biology最新文献

Artificial Intelligence (AI)-enhanced histopathology presents unprecedented opportunities to benefit oncology through interpretable methods that require only one overall label per hematoxylin and eosin (H&E) slide with no tissue-level annotations. We present a structured review of these methods organized by their degree of verifiability and by commonly recurring application areas in oncological characterization. First, we discuss morphological markers (tumor presence/absence, metastases, subtypes, grades) in which AI-identified regions of interest (ROIs) within whole slide images (WSIs) verifiably overlap with pathologist-identified ROIs. Second, we discuss molecular markers (gene expression, molecular subtyping) that are not verified via H&E but rather based on overlap with positive regions on adjacent tissue. Third, we discuss genetic markers (mutations, mutational burden, microsatellite instability, chromosomal instability) that current technologies cannot verify if AI methods spatially resolve specific genetic alterations. Fourth, we discuss the direct prediction of survival to which AI-identified histopathological features quantitatively correlate but are nonetheless not mechanistically verifiable. Finally, we discuss in detail several opportunities and challenges for these one-label-per-slide methods within oncology. Opportunities include reducing the cost of research and clinical care, reducing the workload of clinicians, personalized medicine, and unlocking the full potential of histopathology through new imaging-based biomarkers. Current challenges include explainability and interpretability, validation via adjacent tissue sections, reproducibility, data availability, computational needs, data requirements, domain adaptability, external validation, dataset imbalances, and finally commercialization and clinical potential. Ultimately, the relative ease and minimum upfront cost with which relevant data can be collected in addition to the plethora of available AI methods for outcome-driven analysis will surmount these current limitations and achieve the innumerable opportunities associated with AI-driven histopathology for the benefit of oncology.

Hypoxia in solid tumors is an important predictor of poor clinical outcome to radiotherapy. Both physicochemical and biological processes contribute to a reduced sensitivity of hypoxic tumor cells to ionizing radiation and hypoxia-related treatment resistances. A conventional low-dose fractionated radiotherapy regimen exploits iterative reoxygenation in between the individual fractions, nevertheless tumor hypoxia still remains a major hurdle for successful treatment outcome. The technological advances achieved in image guidance and highly conformal dose delivery make it nowadays possible to prescribe larger doses to the tumor as part of single high-dose or hypofractionated radiotherapy, while keeping an acceptable level of normal tissue complication in the co-irradiated organs at risk. However, we insufficiently understand the impact of tumor hypoxia to single high-doses of RT and hypofractionated RT. So-called FLASH radiotherapy, which delivers ionizing radiation at ultrahigh dose rates (> 40 Gy/sec), has recently emerged as an important breakthrough in the radiotherapy field to reduce normal tissue toxicity compared to irradiation at conventional dose rates (few Gy/min). Not surprisingly, oxygen consumption and tumor hypoxia also seem to play an intriguing role for FLASH radiotherapy. Here we will discuss the role of tumor hypoxia for radiotherapy in general and in the context of novel radiotherapy treatment approaches.

Hypoxia is intrinsic to tumours and contributes to malignancy and metastasis while hindering the efficiency of existing treatments. Epigenetic mechanisms play a crucial role in the regulation of hypoxic cancer cell programs, both in the initial phases of sensing the decrease in oxygen levels and during adaptation to chronic lack of oxygen. During the latter, the epigenetic regulation of tumour biology intersects with hypoxia-sensitive transcription factors in a complex network of gene regulation that also involves metabolic reprogramming. Here, we review the current literature on the epigenetic control of gene programs in hypoxic cancer cells. We highlight common themes and features of such epigenetic remodelling and discuss their relevance for the development of therapeutic strategies.

Hypoxia is a hallmark feature of the tumor microenvironment which can promote mutagenesis and instability. This increase in mutational burden occurs as a result of the downregulation of DNA repair systems. Deficits in the DNA damage response can be exploited to induce cytotoxicity and treat advanced stage cancers. With the advent of precision medicine, agents such as Poly (ADP-ribose) polymerase (PARP) inhibitors have been used to achieve synthetic lethality in homology directed repair (HDR) deficient cancers. However, most cancers lack these predictive biomarkers. Treatment for the HDR proficient population represents an important unmet clinical need. There has been interest in the use of anti-angiogenic agents to promote tumor hypoxia and induce deficiency in a HDR proficient background. For example, the use of cediranib to inhibit PDGFR and downregulate enzymes of the HDR pathway can be used synergistically with a PARP inhibitor. This combination can improve therapeutic responses in HDR proficient cancers. Preclinical results and Phase II and III clinical trial data support the mechanistic rationale for the efficacy of these agents in combination. Future investigations should explore the effectiveness of cediranib and other anti-angiogenic agents with a PARP inhibitor to elicit an antitumor response and sensitize cancers to immunotherapy.

Cardiotoxicity is a common side-effect of many cancer therapeutics; however, to-date there has been very little push to understand the mechanisms underlying this group of pathologies. This has led to the emergence of cardio-oncology, a field of medicine focused on understanding the effects of cancer and its treatment on the human heart. Here, we describe how mechanistic modeling approaches have been applied to study open questions in the cardiovascular system and how these approaches are being increasingly applied to advance knowledge of the underlying effects of cancer treatments on the human heart. A variety of mechanistic, mathematical modeling techniques have been applied to explore the link between common cancer treatments, such as chemotherapy, radiation, targeted therapy, and immunotherapy, and cardiotoxicity, nevertheless there is limited coverage in the different types of cardiac dysfunction that may be associated with these treatments. Moreover, cardiac modeling has a rich heritage of mathematical modeling and is well suited for the further development of novel approaches for understanding the cardiotoxicities associated with cancer therapeutics. There are many opportunities to combine mechanistic, bottom-up approaches with data-driven, top-down approaches to improve personalized, precision oncology to better understand, and ultimately mitigate, cardiac dysfunction in cancer patients.

Pancreatic ductal adenocarcinoma (PDAC) is an extremely deadly form of cancer, with limited progress in 5-year survival rates despite significant research efforts. The main challenges in treating PDAC include difficulties in early detection, and resistance to current therapeutic approaches due to aggressive molecular and microenvironment features. These challenges emphasize the importance of identifying clinically validated biomarkers for early detection and clinical management. Extracellular vesicles (EVs), particularly exosomes, have emerged as crucial mediators of intercellular communication by transporting molecular cargo. Recent research has unveiled their role in initiation, metastasis, and chemoresistance of PDAC. Consequently, utilizing EVs in liquid biopsies holds promise for the identification of biomarkers for early detection, prognosis, and monitoring of drug efficacy. However, numerous limitations, including challenges in isolation and characterization of homogeneous EVs populations, as well as the absence of standardized protocols, can affect the reliability of studies involving EVs as biomarkers, underscoring the necessity for a prudent approach. EVs have also garnered considerable attention as a promising drug delivery system and novel therapy for tumors. The loading of biomolecules or chemical drugs into exosomes and their subsequent delivery to target cells can effectively impede tumor progression. Nevertheless, there are obstacles that must be overcome to ensure the accuracy and efficacy of therapies relying on EVs for the treatment of tumors. In this review, we examine both recent advancements and remaining obstacles, exploring the potential of utilizing EVs in biomarker discovery as well as for the development of drug delivery vehicles.

Transforming growth factor-β (TGF-β) signaling regulates cell-specific programs involved in embryonic development, wound-healing, and immune homeostasis. Yet, during tumor progression, these TGF-β-mediated programs are altered, leading to epithelial cell plasticity and a reprogramming of epithelial cells into mesenchymal lineages through epithelial-to-mesenchymal transition (EMT), a critical developmental program in morphogenesis and organogenesis. These changes, in turn, lead to enhanced carcinoma cell invasion, metastasis, immune cell differentiation, immune evasion, and chemotherapy resistance. Here, we discuss EMT as one of the critical programs associated with carcinoma cell plasticity and the influence exerted by TGF-β on carcinoma status and function. We further explore the composition of carcinoma and other cell populations within the tumor microenvironment, and consider the relevant outcomes related to the programs associated with cancer treatment resistance.

Disruption of oxygen homeostasis, resulting from an imbalance between O₂ supply and demand during malignant proliferation, leads to the development of hypoxic tumor microenvironments that promote the acquisition of aggressive cancer cell phenotypes linked to metastasis and patient mortality. In this review, the mechanistic links between tumor hypoxia and metastatic progression are presented. Current status and perspectives of targeting hypoxia signaling pathways as a strategy to halt cancer cell metastatic activities are emphasized.

Obesity is a prominent health issue worldwide and directly impacts pancreatic health, with obese individuals exhibiting a significant risk for increasing pancreatic ductal adenocarcinoma (PDAC). Several factors potentially explain the increased risk for the development of PDAC, including obesity-induced chronic inflammation within and outside of the pancreas, development of insulin resistance and metabolic dysfunction, promotion of immune suppression within the pancreas during inflammation, pre- and malignant stages, variations in hormones levels (adiponectin, ghrelin, and leptin) produced from the adipose tissue, and acquisition of somatic mutations in tumor once- and suppressor proteins critical for pancreatic tumorigenesis. In this manuscript, we will explore the broad impact of these obesity-induced risk factors on the development and progression of PDAC, focusing on changes within the tumor microenvironment (TME) as they pertain to prevention, current therapeutic strategies, and future directions for targeting obesity management as they relate to the prevention of pancreatic tumorigenesis.