Therapeutic agents for targeting desmoplasia: current status and emerging trends

Heat shock protein 72 supports extracellular matrix production in metastatic mammary tumors

This study identified tumorigenic processes most dependent on murine heat shock protein 72 (HSP72) in the mouse mammary tumor virus-PyMT mammary tumor model, which give rise to spontaneous mammary tumors that exhibit HSP72-dependent metastasis to the lung. RNA-seq expression profiling of Hspa1a/Hspa1b (Hsp72) WT and Hsp72-/- primary mammary tumors discovered significantly lower expression of genes encoding components of the extracellular matrix (ECM) in Hsp72 knockout mammary tumors compared to WT controls. In vitro studies found that genetic or chemical inhibition of HSP72 activity in cultured collagen-expressing human or murine cells also reduces mRNA and protein levels of COL1A1 and several other ECM-encoding genes. In search of a possible mechanistic basis for this relationship, we found HSP72 to support the activation of the tumor growth factor-β-suppressor of mothers against decapentaplegic-3 signaling pathway and evidence of suppressor of mothers against decapentaplegic-3 and HSP72 coprecipitation, suggesting potential complex formation. Human COL1A1 mRNA expression was found to have prognostic value for HER2+ breast tumors over other breast cancer subtypes, suggesting a possible human disease context where targeting HSP72 may have a therapeutic rationale. Analysis of human HER2+ breast tumor gene expression data using a gene set comprising ECM-related gene and protein folding-related gene as an input to the statistical learning algorithm, Galgo, found a subset of these genes that can collectively stratify patients by relapse-free survival, further suggesting a potential interplay between the ECM and protein-folding genes may contribute to tumor progression.

Belinostat loaded lipid-polymer hybrid nanoparticulate delivery system for breast cancer: improved pharmacokinetics and biodistribution in a tumor model

Despite various treatment modalities for breast cancer, it still persists as one of the most diagnosed types of cancer in females. The recent investigations in the epigenetics of breast cancer reveal several aberrations in the expression levels of various HDAC enzymes. Henceforth, the present work entails the formulation and characterization of a lipid polymer-based hybrid nanoparticulate (LPN) system for delivery of an epigenetic modulator drug, Belinostat, for its clinical application in breast cancer. The size of Belinostat nanoparticles prepared using a modified hot homogenization method was found to be 166.6 ± 19.95 nm with an encapsulation efficiency of 94.5 ± 5.1%. In vitro characterization for cytotoxicity, cellular uptake, and protein expression in two different breast cancer cells, 4T1 and MCF 7, revealed the superiority of the formulation in comparison with the free drug in MCF 7 cells. Subsequently, the behaviour of the formulation in in vivo settings of healthy and breast cancer xenograft bearing animals was analyzed using pharmacokinetic and biodistribution studies. The results revealed that the formulation demonstrated multi-fold improvement in the pharmacokinetic parameters in tumor bearing animals when compared with the free drug while no difference in pharmacokinetic behaviour was observed in healthy animals indicating the altered biodistribution and specificity of the formulation in breast tumor. This was confirmed by the biodistribution studies exhibiting 20-fold improved uptake and retention of the nanoparticulate formulation in tumor tissues of the animal model at the end of 4 h. Thus, the developed LPN system holds potential to act as a novel drug delivery system for Belinostat with several advantages over the free drug.

Periostin+ Stromal Cells Guide Lymphovascular Invasion by Cancer Cells

Cancer cell dissemination to sentinel lymph nodes is associated with poor patient outcomes, particularly in breast cancer. The process by which cancer cells egress from the primary tumor upon interfacing with the lymphatic vasculature is complex and driven by dynamic interactions between cancer cells and stromal cells, including cancer-associated fibroblasts (CAF). The matricellular protein periostin can distinguish CAF subtypes in breast cancer and is associated with increased desmoplasia and disease recurrence in patients. However, as periostin is secreted, periostin-expressing CAFs are difficult to characterize in situ, limiting our understanding of their specific contribution to cancer progression. Here, we used in vivo genetic labeling and ablation to lineage trace periostin+ cells and characterize their functions during tumor growth and metastasis. Periostin-expressing CAFs were spatially found at periductal and perivascular margins, were enriched at lymphatic vessel peripheries, and were differentially activated by highly metastatic cancer cells versus poorly metastatic counterparts. Surprisingly, genetically depleting periostin+ CAFs slightly accelerated primary tumor growth but impaired intratumoral collagen organization and inhibited lymphatic, but not lung, metastases. Periostin ablation in CAFs impaired their ability to deposit aligned collagen matrices and inhibited cancer cell invasion through collagen and across lymphatic endothelial cell monolayers. Thus, highly metastatic cancer cells mobilize periostin-expressing CAFs in the primary tumor site that promote collagen remodeling and collective cell invasion within lymphatic vessels and ultimately to sentinel lymph nodes.

SIGNIFICANCE

Highly metastatic breast cancer cells activate a population of periostin-expressing CAFs that remodel the extracellular matrix to promote escape of cancer cells into lymphatic vessels and drive colonization of proximal lymph nodes.

Drug Delivery Strategies for the Treatment of Pancreatic Cancer

Pancreatic cancer is fast becoming a global menace and it is projected to be the second leading cause of cancer-related death by 2030. Pancreatic adenocarcinomas, which develop in the pancreas' exocrine region, are the predominant type of pancreatic cancer, representing about 95% of total pancreatic tumors. The malignancy progresses asymptomatically, making early diagnosis difficult. It is characterized by excessive production of fibrotic stroma known as desmoplasia, which aids tumor growth and metastatic spread by remodeling the extracellular matrix and releasing tumor growth factors. For decades, immense efforts have been harnessed toward developing more effective drug delivery systems for pancreatic cancer treatment leveraging nanotechnology, immunotherapy, drug conjugates, and combinations of these approaches. However, despite the reported preclinical success of these approaches, no substantial progress has been made clinically and the prognosis for pancreatic cancer is worsening. This review provides insights into challenges associated with the delivery of therapeutics for pancreatic cancer treatment and discusses drug delivery strategies to minimize adverse effects associated with current chemotherapy options and to improve the efficiency of drug treatment.

Biomedical Applications of Non-Small Cell Lung Cancer Spheroids

Lung malignancies accounted for 11% of cancers worldwide in 2020 and remained the leading cause of cancer deaths. About 80% of lung cancers belong to non-small cell lung cancer (NSCLC), which is characterized by extremely high clonal and morphological heterogeneity of tumors and development of multidrug resistance. The improvement of current therapeutic strategies includes several directions. First, increasing knowledge in cancer biology results in better understanding of the mechanisms underlying malignant transformation, alterations in signal transduction, and crosstalk between cancer cells and the tumor microenvironment, including immune cells. In turn, it leads to the discovery of important molecular targets in cancer development, which might be affected pharmaceutically. The second direction focuses on the screening of novel drug candidates, synthetic or from natural sources. Finally, "personalization" of a therapeutic strategy enables maximal damage to the tumor of a patient. The personalization of treatment can be based on the drug screening performed using patient-derived tumor xenografts or in vitro patient-derived cell models. 3D multicellular cancer spheroids, generated from cancer cell lines or tumor-isolated cells, seem to be a helpful tool for the improvement of current NSCLC therapies. Spheroids are used as a tumor-mimicking in vitro model for screening of novel drugs, analysis of intercellular interactions, and oncogenic cell signaling. Moreover, several studies with tumor-derived spheroids suggest this model for the choice of "personalized" therapy. Here we aim to give an overview of the different applications of NSCLC spheroids and discuss the potential contribution of the spheroid model to the development of anticancer strategies.

Targeting Tumor-Stromal Interactions in Pancreatic Cancer: Impact of Collagens and Mechanical Traits

Pancreatic ductal adenocarcinoma (PDAC) has one of the worst outcomes among cancers with a 5-years survival rate of below 10%. This is a result of late diagnosis and the lack of effective treatments. The tumor is characterized by a highly fibrotic stroma containing distinct cellular components, embedded within an extracellular matrix (ECM). This ECM-abundant tumor microenvironment (TME) in PDAC plays a pivotal role in tumor progression and resistance to treatment. Cancer-associated fibroblasts (CAFs), being a dominant cell type of the stroma, are in fact functionally heterogeneous populations of cells within the TME. Certain subtypes of CAFs are the main producer of the ECM components of the stroma, with the most abundant one being the collagen family of proteins. Collagens are large macromolecules that upon deposition into the ECM form supramolecular fibrillar structures which provide a mechanical framework to the TME. They not only bring structure to the tissue by being the main structural proteins but also contain binding domains that interact with surface receptors on the cancer cells. These interactions can induce various responses in the cancer cells and activate signaling pathways leading to epithelial-to-mesenchymal transition (EMT) and ultimately metastasis. In addition, collagens are one of the main contributors to building up mechanical forces in the tumor. These forces influence the signaling pathways that are involved in cell motility and tumor progression and affect tumor microstructure and tissue stiffness by exerting solid stress and interstitial fluid pressure on the cells. Taken together, the TME is subjected to various types of mechanical forces and interactions that affect tumor progression, metastasis, and drug response. In this review article, we aim to summarize and contextualize the recent knowledge of components of the PDAC stroma, especially the role of different collagens and mechanical traits on tumor progression. We furthermore discuss different experimental models available for studying tumor-stromal interactions and finally discuss potential therapeutic targets within the stroma.

Application of omics- and multi-omics-based techniques for natural product target discovery

Natural products continue to be an unparalleled source of pharmacologically active lead compounds because of their unprecedented structures and unique biological activities. Natural product target discovery is a vital component of natural product-based medicine translation and development and is required to understand and potentially reduce mechanisms that may be associated with off-target side effects and toxicity. Omics-based techniques, including genomics, transcriptomics, proteomics, metabolomics, and bioinformatics, have become recognized as effective tools needed to construct innovative strategies to discover natural product targets. Although considerable progress has been made, the successful discovery of natural product targets remains a challenging time-consuming process that has come to increasingly rely on the effective integration of multi-omics-based technologies to create emerging panomics (a.k.a., integrative omics, pan-omics, multiomics)-based strategies. This review summarizes a series of successful studies regarding the application of integrative omics-based methods in natural product target discovery. The advantages and disadvantages of each technique are discussed, with a particular focus on the systematic integration of multi-omics strategies. Further, emerging micro-scale single-cell-based techniques are introduced, especially to deal with minute natural product samples.

Pathway-Based Drug Repurposing with DPNetinfer: A Method to Predict Drug-Pathway Associations via Network-Based Approaches

Identification of drug-pathway associations plays an important role in pathway-based drug repurposing. However, it is time-consuming and costly to uncover new drug-pathway associations experimentally. The drug-induced transcriptomics data provide a global view of cellular pathways and tell how these pathways change under different treatments. These data enable computational approaches for large-scale prediction of drug-pathway associations. Here we introduced DPNetinfer, a novel computational method to predict potential drug-pathway associations based on substructure-drug-pathway networks via network-based approaches. The results demonstrated that DPNetinfer performed well in a pan-cancer network with an AUC (area under curve) = 0.9358. Meanwhile, DPNetinfer was shown to have a good capability of generalization on two external validation sets (AUC = 0.8519 and 0.7494, respectively). As a case study, DPNetinfer was used in pathway-based drug repurposing for cancer therapy. Unexpected anticancer activities of some nononcology drugs were then identified on the PI3K-Akt pathway. Considering tumor heterogeneity, seven primary site-based models were constructed by DPNetinfer in different drug-pathway networks. In a word, DPNetinfer provides a powerful tool for large-scale prediction of drug-pathway associations in pathway-based drug repurposing. A web tool for DPNetinfer is freely available at http://lmmd.ecust.edu.cn/netinfer/.

Transforming Growth Factor-β Signaling in Fibrotic Diseases and Cancer-Associated Fibroblasts

Transforming growth factor-β (TGF-β) signaling is essential in embryo development and maintaining normal homeostasis. Extensive evidence shows that TGF-β activation acts on several cell types, including epithelial cells, fibroblasts, and immune cells, to form a pro-fibrotic environment, ultimately leading to fibrotic diseases. TGF-β is stored in the matrix in a latent form; once activated, it promotes a fibroblast to myofibroblast transition and regulates extracellular matrix (ECM) formation and remodeling in fibrosis. TGF-β signaling can also promote cancer progression through its effects on the tumor microenvironment. In cancer, TGF-β contributes to the generation of cancer-associated fibroblasts (CAFs) that have different molecular and cellular properties from activated or fibrotic fibroblasts. CAFs promote tumor progression and chronic tumor fibrosis via TGF-β signaling. Fibrosis and CAF-mediated cancer progression share several common traits and are closely related. In this review, we consider how TGF-β promotes fibrosis and CAF-mediated cancer progression. We also discuss recent evidence suggesting TGF-β inhibition as a defense against fibrotic disorders or CAF-mediated cancer progression to highlight the potential implications of TGF-β-targeted therapies for fibrosis and cancer.