Explore the vast range of titles available.

The diagnosis and treatment of cancers have become a significant challenge in overcoming malignant diseases. Early detection of tumors and timely targeted therapy can greatly impede the rapid deterioration of cancers. In recent years, nano-systems based on photodynamic materials have shown great progress in tumor diagnosis and treatment applications. With the continuous exploration of tumor-specific targets and the development of photodynamic nanoparticles, the generation of new nanoparticles that are target-specific, highly sensitive, and biosafe for integrated diagnosis and therapy is realistic. This review introduces the rational basis for photosensitizer-based materials for integrating cancer diagnosis and anti-cancer therapy, types and characteristics of organic and inorganic photosensitizers currently used for PDT treatment, photosensitive nano-materials with dual detection and therapeutic properties the advancement in developing photo-dynamic nano-systems showing potential in integrated diagnosis and therapeutic applications. We also introduce current strategies for optimizing nano-systems with the properties for enhancing targeting ROS release and accurate imaging, combining therapeutic efficacy, as well as biosafety of the integrative materials for PDT application, providing references for the coordinated optimization of photosensitizer design and clinical translation.

Cancer heterogeneity is regarded as the main reason for the failure of conventional cancer therapy. The ability to reconstruct intra- and interpatient heterogeneity in cancer models is crucial for understanding cancer biology as well as for developing personalized anti-cancer therapy. Cancer organoids represent an emerging approach for creating patient-derived in vitro cancer models that closely recapitulate the pathophysiological features of natural tumorigenesis and metastasis. Meanwhile, cancer organoids have recently been utilized in the discovery of personalized anti-cancer therapy and prognostic biomarkers. Further, the synergistic combination of cancer organoids with organ-on-a-chip and 3D bioprinting presents a new avenue in the development of more sophisticated and optimized model systems to recapitulate complex cancer-stroma or multiorgan metastasis. Here, we summarize the recent advances in cancer organoids from a perspective of the in vitro emulation of natural cancer evolution and the applications in personalized cancer theranostics. We also discuss the challenges and trends in reconstructing more comprehensive cancer models for basic and clinical cancer research.

The treatment of metastatic lesions in the brain represents a serious unmet medical need in the field of neuro-oncology. Even though many effective compounds have demonstrated success in treating peripheral (non-CNS) tumors with targeted agents, one aspect of this lack of success in the brain may be related to poor delivery of otherwise effective compounds. Many factors can influence the brain delivery of these agents, but one key barrier is a heterogeneously “leaky” BBB that expresses efflux transporters that limit the BBB permeability for many targeted agents. Future success in therapeutics for brain metastases must take into account the adequate delivery of “active, free drug” to the target, and may include combinations of targeted drugs that are appropriate to address each individual patient’s tumor type. This review discusses some issues that are pertinent to precision medicine for brain metastases, using specific examples of tumor types that have a high incidence of brain metastases.

Cost-efficacy of currently applied treatments is an issue in overall cancer management challenging healthcare and causing tremendous economic burden to societies around the world. Consequently, complex treatment models presenting concepts of predictive diagnostics followed by targeted prevention and treatments tailored to the personal patient profiles earn global appreciation as benefiting the patient, healthcare economy, and the society at large. In this context, application of flavonoids as a spectrum of compounds and their nano-technologically created derivatives is extensively under consideration, due to their multi-faceted anti-cancer effects applicable to the overall cost-effective cancer management, primary, secondary, and even tertiary prevention. This article analyzes most recently updated data focused on the potent capacity of flavonoids to promote anti-cancer therapeutic effects and interprets all the collected research achievements in the frame-work of predictive, preventive, and personalized (3P) medicine. Main pillars considered are:- Predictable anti-neoplastic, immune-modulating, drug-sensitizing effects;- Targeted molecular pathways to improve therapeutic outcomes by increasing sensitivity of cancer cells and reversing their resistance towards currently applied therapeutic modalities.

PurposeThe formation of new blood vessels from previous ones, angiogenesis, is critical in tissue repair, expansion or remodeling in physiological processes and in various pathologies including cancer. Despite that, the development of anti-angiogenic drugs has great potential as the treatment of cancer faces many problems such as development of the resistance to treatment or an improperly selected therapy approach. An evaluation of predictive markers in personalized medicine could significantly improve treatment outcomes in many patients.MethodsThis comprehensive review emphasizes the anticancer potential of flavonoids mediated by their anti-angiogenic efficacy evaluated in current preclinical and clinical cancer research.Results and conclusionFlavonoids are important groups of phytochemicals present in common diet. Flavonoids show significant anticancer effects. The anti-angiogenic effects of flavonoids are currently a widely discussed topic of preclinical cancer research. Flavonoids are able to regulate the process of tumor angiogenesis through modulation of signaling molecules such as VEGF, MMPs, ILs, HIF or others. However, the evaluation of the anti-angiogenic potential of flavonoids within the clinical studies is not frequently discussed and is still of significant scientific interest.

While synergistic drug combinations are more effective at fighting tumors with complex pathophysiology, preference compensating mechanisms, and drug resistance, the identification of novel synergistic drug combinations, especially complex higher-order combinations, remains challenging due to the size of combination space. Even though certain computational methods have been used to identify synergistic drug combinations in lieu of traditional in vitro and in vivo screening tests, the majority of previously published work has focused on predicting synergistic drug pairs for specific types of cancer and paid little attention to the sophisticated high-order combinations. The main objective of this study is to develop a deep learning-based approach that integrated multi-omics data to predict novel synergistic multi-drug combinations (DeepMDS) in a given cell line. To develop this approach, we firstly created a dataset comprising of gene expression profiles of cancer cell lines, target information of anti-cancer drugs, and drug response against a large variety of cancer cell lines. Based on the principle of a fully connected feed forward Deep Neural Network, the proposed model was constructed using this dataset, which achieved a high performance with a Mean Square Error (MSE) of 2.50 and a Root Mean Squared Error (RMSE) of 1.58 in the regression task, and gave the best classification accuracy of 0.94, an area under the Receiver Operating Characteristic curve (AUC) of 0.97, a sensitivity of 0.95, and a specificity of 0.93. Furthermore, we utilized three breast cancer cell subtypes (MCF-7, MDA-MD-468 and MDA-MB-231) and one lung cancer cell line A549 to validate the predicted results of our model, showing that the predicted top-ranked multi-drug combinations had superior anti-cancer effects to other combinations, particularly those that were widely used in clinical treatment. Our model has the potential to increase the practicality of expanding the drug combinational space and to leverage its capacity to prioritize the most effective multi-drug combinational therapy for precision oncology applications.

Cancer incidence and mortality continue to increase, while the conventional chemotherapeutic drugs confer limited efficacy and relevant toxic side effects. Novel strategies are urgently needed for more effective and safe therapeutics in oncology. However, a large number of proteins are considered undruggable by conventional drugs, such as the small molecules. Moreover, the mRNA itself retains oncological functions, and its targeting offers the double advantage of blocking the tumorigenic activities of the mRNA and the translation into protein. Finally, a large family of non-coding RNAs (ncRNAs) has recently emerged that are also dysregulated in cancer, but they could not be targeted by drugs directed against the proteins. In this context, this review describes how the oligonucleotide therapeutics targeting RNA or DNA sequences, are emerging as a new class of drugs, able to tackle the limitations described above. Numerous clinical trials are evaluating oligonucleotides for tumor treatment, and in the next few years some of them are expected to reach the market. We describe the oligonucleotide therapeutics targeting undruggable proteins (focusing on the most relevant, such as those originating from the MYC and RAS gene families), and for ncRNAs, in particular on those that are under clinical trial evaluation in oncology. We highlight the challenges and solutions for the clinical success of oligonucleotide therapeutics, with particular emphasis on the peculiar challenges that render it arduous to treat tumors, such as heterogeneity and the high mutation rate. In the review are presented these and other advantages offered by the oligonucleotide as an emerging class of biotherapeutics for a new era of precision anti-cancer medicine.

Organoids are stem cell-derived three-dimensional tissue cultures composed of multiple cell types that recapitulate the morphology and functions of their in vivo counterparts. Organ-on-a-chip devices are tiny chips with interconnected wells and channels designed using a perfusion system and microfluidics to precisely mimic the in vivo physiology and mechanical forces experienced by cells in the body. These techniques have recently been used to reproduce the structure and function of organs in vitro and are expected to be promising alternatives for animal experiments in the future. In the present study, we designed and fabricated an organ-on-a-chip system for mounting organoids from mammary tumor-affected cats (FMT organoids) and normal intestinal organoids from mice (MI organoids) and perfused them with anti-cancer drugs. The effects of drug perfusion on FMT and MI organoids were examined by measuring cell viability and performing genetic analysis. After 48 h of perfusion with toceranib (10 µM) or doxorubicin (1 µM), cell viability of FMT organoids was decreased compared to the non-perfusion condition. The expression of apoptosis-related genes, such as p53 and Caspase-9 was significantly upregulated in FMT organoids with drug perfusion. The rate of cell death drastically differed before and after branching in the device, owing to differences in flow velocity and drug infiltration. Perfusion of MI organoids with toceranib also reduced viability, as observed in FMT organoids; however, this was due to the induction of necrosis rather than apoptosis. In conclusion, our established multi-organoid-on-chip system could be used to evaluate anti-cancer drug sensitivity and side effects in vitro, which might contribute to developing personalized medicine for cancer patients.

Despite tremendous progress in deciphering breast cancer at the genomic level, the pronounced intra- and intertumoral heterogeneity remains a major obstacle to the advancement of novel and more effective treatment approaches. Frequent treatment failure and the development of treatment resistance highlight the need for patient-derived tumor models that reflect the individual tumors of breast cancer patients and allow a comprehensive analyses and parallel functional validation of individualized and therapeutically targetable vulnerabilities in protein signal transduction pathways. Here, we introduce the generation and application of breast cancer patient-derived 3D microtumors (BC-PDMs). Residual fresh tumor tissue specimens were collected from n  = 102 patients diagnosed with breast cancer and subjected to BC-PDM isolation. BC-PDMs retained histopathological characteristics, and extracellular matrix (ECM) components together with key protein signaling pathway signatures of the corresponding primary tumor tissue. Accordingly, BC-PDMs reflect the inter- and intratumoral heterogeneity of breast cancer and its key signal transduction properties. DigiWest®-based protein expression profiling of identified treatment responder and non-responder BC-PDMs enabled the identification of potential resistance and sensitivity markers of individual drug treatments, including markers previously associated with treatment response and yet undescribed proteins. The combination of individualized drug testing with comprehensive protein profiling analyses of BC-PDMs may provide a valuable complement for personalized treatment stratification and response prediction for breast cancer.

Cancer is one of the most serious threats to human health. Precision medicine is an innovative approach to treatment, as part of which theranostic nanomedicine has been studied extensively. However, the required biocompatibility and substantial cost for the approval of nanomedicines hinder their clinical translation. We designed a novel type of theranostic nanoparticle (NP) folate-receptor-targeted laser-activatable poly(lactide- -glycolic acid) (PLGA) NPs loaded with paclitaxel (Ptx)/indo-cyanine green (ICG)-folic acid-polyethylene glycol (PEG)-PLGA-Ptx@ICG-perfluorohexane (Pfh)- using safe and approved materials and drugs, which would facilitate clinical translation. With laser irradiation, highly efficient photothermal therapy can be achieved. Additionally, targeted NPs can be activated by near-infrared laser irradiation at a specific region, which leads to the sharp release of Ptx at areas of high folate-receptor expression and ensures a higher Ptx concentration within the tumor region, thereby leading to chemo/photothermal synergistic antitumor efficacy. Meanwhile, the NPs can be used as a dual-modality contrast agent for photoacoustic and ultrasound imaging. FA-PEG-PLGA-Ptx@ICG-Pfh NPs were prepared by sonification method and characterized for physicochemical properties. Cytotoxicity and in vivo biocompatibility were evaluated respectively by CCK8 assay and blood analysis. NPs as dual-modality contrast agents were evaluated by photoacoustic/ultrasound imaging system in vitro and in vivo. In vitro anticancer effect and in vivo anticancer therapy was evaluated by CCK8 assay and MDA-MB231 tumor-bearing mice model. FA-PEG-PLGA-Ptx@ICG-Pfh NPs were in the size of 308±5.82 nm with negative zeta potential and showed excellent photothermal effect. The NPs could be triggered sharp release of Ptx by laser irradiation, and showed the good biocompatibility in vitro and in vivo. Through photoacoustic/ultrasound imaging, the NPs showed an excellent ability as dual-modality contrast agents in vitro and in vivo. FA-PEG-PLGA-Ptx@ICG-Pfh NPs with laser irradiation showed the best anticancer efficacy in vitro and in vivo. Such a biocompatible and novel theranostic NP is expected to integrate dual-modality imaging with improved therapeutic efficacy and provide a promising paradigm for cancer therapy.