Seminars in cancer biology最新文献

Lung cancer is the leading cause of cancer related death, and is divided into two major histological subtypes, non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Histological transformation from NSCLC to SCLC has been reported as a mechanism of treatment resistance in patients who received tyrosine kinase inhibitors (TKIs) targeting EGFR, ALK and ROS1 or immunotherapies. The transformed histology could be due to therapy-induced lineage plasticity or clonal selection of pre-existing SCLC cells. Evidence supporting either mechanism exist in the literature. Here, we discuss potential mechanisms of transformation and review the current knowledge about cell of origin of NSCLC and SCLC. In addition, we summarize genomic alterations that are frequently observed in both “de novo” and transformed SCLC, such as TP53, RB1 and PIK3CA. We also discuss treatment options for transformed SCLC, including chemotherapy, radiotherapy, TKIs, immunotherapy and anti-angiogenic agents.

Reactive oxygen species (ROS) are common products of normal cellular metabolism, but their elevated levels can result in nucleotide modifications. These modified or noncanonical nucleotides often integrate into nascent DNA during replication, causing lesions that trigger DNA repair mechanisms such as the mismatch repair machinery and base excision repair. Four superfamilies of sanitization enzymes can effectively hydrolyze noncanonical nucleotides from the precursor pool and eliminate their unintended incorporation into DNA. Notably, we focus on the representative MTH1 NUDIX hydrolase, whose enzymatic activity is ostensibly nonessential under normal physiological conditions. Yet, the sanitization attributes of MTH1 are more prevalent when ROS levels are abnormally high in cancer cells, rendering MTH1 an interesting target for developing anticancer treatments. We discuss multiple MTH1 inhibitory strategies that have emerged in recent years, and the potential of NUDIX hydrolases as plausible targets for the development of anticancer therapeutics.

The use of artificial intelligence (AI) to assist biomedical imaging have demonstrated its high accuracy and high efficiency in medical decision-making for individualized cancer medicine. In particular, optical imaging methods are able to visualize both the structural and functional information of tumors tissues with high contrast, low cost, and noninvasive property. However, no systematic work has been performed to inspect the recent advances on AI-aided optical imaging for cancer theranostics. In this review, we demonstrated how AI can guide optical imaging methods to improve the accuracy on tumor detection, automated analysis and prediction of its histopathological section, its monitoring during treatment, and its prognosis by using computer vision, deep learning and natural language processing. By contrast, the optical imaging techniques involved mainly consisted of various tomography and microscopy imaging methods such as optical endoscopy imaging, optical coherence tomography, photoacoustic imaging, diffuse optical tomography, optical microscopy imaging, Raman imaging, and fluorescent imaging. Meanwhile, existing problems, possible challenges and future prospects for AI-aided optical imaging protocol for cancer theranostics were also discussed. It is expected that the present work can open a new avenue for precision oncology by using AI and optical imaging tools.

Primary cutaneous lymphomas (CLs) represent a heterogeneous group of T-cell lymphomas and B-cell lymphomas that present in the skin without evidence of extracutaneous involvement at time of diagnosis. CLs are largely distinct from their systemic counterparts in clinical presentation, histopathology, and biological behavior and, therefore, require different therapeutic management. Additional diagnostic burden is added by the fact that several benign inflammatory dermatoses mimic CL subtypes, requiring clinicopathological correlation for definitive diagnosis. Due to the heterogeneity and rarity of CL, adjunct diagnostic tools are welcomed, especially by pathologists without expertise in this field or with limited access to a centralized specialist panel. The transition into digital pathology workflows enables artificial intelligence (AI)-based analysis of patients’ whole-slide pathology images (WSIs). AI can be used to automate manual processes in histopathology but, more importantly, can be applied to complex diagnostic tasks, especially suitable for rare disease like CL. To date, AI-based applications for CL have been minimally explored in literature. However, in other skin cancers and systemic lymphomas, disciplines that are recognized here as the building blocks for CLs, several studies demonstrated promising results using AI for disease diagnosis and subclassification, cancer detection, specimen triaging, and outcome prediction. Additionally, AI allows discovery of novel biomarkers or may help to quantify established biomarkers. This review summarizes and blends applications of AI in pathology of skin cancer and lymphoma and proposes how these findings can be applied to diagnostics of CL.

Small cell lung cancer (SCLC) is a recalcitrant cancer with an urgent need for novel therapeutics, preclinical models, and elucidation of the molecular pathways responsible for its rapid resistance. Recently, there have been many significant advancements in our knowledge of SCLC that led to the development of novel treatments. This review will go over the recent attempts to provide new molecular subcategorization of SCLC, recent breakthroughs in various systemic treatments including immunotherapy, targeted therapy, cellular therapy, as well as advancements in radiation therapy.

Hepatocellular carcinoma (HCC) is estimated to be the third leading cause of cancer-related mortality and is characterized by low survival rates. Nonalcoholic fatty liver disease (NAFLD) is emerging as a leading cause of HCC, whose rates are increasing, owing to the increasing prevalence of NAFLD. The pathogenesis of NAFLD-associated HCC is multifactorial: insulin resistance, obesity, diabetes and the low-grade hepatic inflammation, which characterizes NAFLD, seem to play key roles in the development and progression of HCC. The diagnosis of NAFLD-associated HCC is based on imaging in the presence of liver cirrhosis, preferably computerized tomography or magnetic resonance imaging, but liver biopsy for histological confirmation is usually required in the absence of liver cirrhosis. Some preventive measures have been recommended for NAFLD-associated HCC, including weight loss, cessation of even moderate alcohol drinking and smoking, as well as the use of metformin, statins and aspirin. However, these preventive measures are mainly based on observational studies, thus they need validation in trials of different design before introducing in clinical practice. The treatment of NAFLD should be tailored on an individual basis and should be ideally determined by a multidisciplinary team. In the last two decades, new medications, including tyrosine kinase inhibitors and immune checkpoints inhibitors, have improved the survival of patients with advanced HCC, but trials specifically designed for patients with NAFLD-associated HCC are scarce. The aim of this review was to overview evidence on the epidemiology and pathophysiology of NAFLD-associated HCC, then to comment on imaging tools for its appropriate screening and diagnosis, and finally to critically summarize the currently available options for its prevention and treatment.

Obesity has been closely related to cancer progression, recurrence, metastasis, and treatment resistance. We aim to review recent progress in the knowledge on the obese macroenvironment and the generated adipose tumor microenvironment (TME) inducing lipid metabolic dysregulation and their influence on carcinogenic processes. Visceral white adipose tissue expansion during obesity exerts systemic or macroenvironmental effects on tumor initiation, growth, and invasion by promoting inflammation, hyperinsulinemia, growth-factor release, and dyslipidemia. The dynamic relationship between cancer and stromal cells of the obese adipose TME is critical for cancer cell survival and proliferation as well. Experimental evidence shows that secreted paracrine signals from cancer cells can induce lipolysis in cancer-associated adipocytes, causing them to release free fatty acids and acquire a fibroblast-like phenotype. Such adipocyte delipidation and phenotypic change is accompanied by an increased secretion of cytokines by cancer-associated adipocytes and tumor-associated macrophages in the TME. Mechanistically, the availability of adipose TME free fatty acids and tumorigenic cytokines concomitant with the activation of angiogenic processes creates an environment that favors a shift in the cancer cells toward an aggressive phenotype associated with increased invasiveness. We conclude that restoring the aberrant metabolic alterations in the host macroenvironment and in adipose TME of obese subjects would be a therapeutic option to prevent cancer development. Several dietary, lipid-based, and oral antidiabetic pharmacological therapies could potentially prevent tumorigenic processes associated with the dysregulated lipid metabolism closely linked to obesity.

Primary tumors secrete a variety of factors to turn distant microenvironments into favorable and fertile ‘soil’ for subsequent metastases. Among these ‘seeding’ factors that initiate pre-metastatic niche (PMN) formation, tumor-derived extracellular vesicles (EVs) are of particular interest as tumor EVs can direct organotropism depending on their surface integrin profiles. In addition, EVs also contain versatile, bioactive cargo, which include proteins, metabolites, lipids, RNA, and DNA fragments. The cargo incorporated into EVs is collectively shed from cancer cells and cancer-associated stromal cells. Increased understanding of how tumor EVs promote PMN establishment and detection of EVs in bodily fluids highlight how tumor EVs could serve as potential diagnostic and prognostic biomarkers, as well as provide a therapeutic target for metastasis prevention. This review focuses on tumor-derived EVs and how they direct organotropism and subsequently modulate stromal and immune microenvironments at distal sites to facilitate PMN formation. We also outline the progress made thus far towards clinical applications of tumor EVs.