Better Understanding Of Cancer Progression Research Articles

Model discovery approach enables noninvasive measurement of intra-tumoral fluid transport in dynamic MRI.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to noninvasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that our method will contribute to the better understanding of cancer progression and therapeutic response.

Cancer and apoptosis: The apoptotic activity of plant and marine natural products and their potential as targeted cancer therapeutics.

Cancer is a multifactorial, multi-stage disease, including complex cascades of signaling pathways—the cell growth governed by dysregulated and abrupt cell division. Due to the complexity and multi-regulatory cancer progression, cancer is still a challenging disease to treat and survive. The screening of extracts and fractions from plants and marine species might lead to the discovery of more effective compounds for cancer therapeutics. The isolated compounds and reformed analogs were known as future prospective contenders for anti-cancer chemotherapy. For example, Taxol, a potent mitotic inhibitor discovered from Taxus brevifolia, suppresses cell growth and arrest, induces apoptosis, and inhibits proliferation. Similarly, marine sponges show remarkable tumor chemo preventive and chemotherapeutic potential. However, there is limited research to date. Several plants and marine-derived anti-cancer compounds having the property to induce apoptosis have been approved for clinical trials. The anti-cancer activity kills the cell and slows the growth of cancer cells. Among cell death mechanisms, apoptosis induction is a more profound mechanism of cell death triggered by naturally isolated anti-cancer agents. Evading apoptosis is the major hurdle in killing cancer cells, a mechanism mainly regulated as intrinsic and extrinsic. However, it is possible to modify the apoptosis-resistant phenotype of the cell by altering many of these mechanisms. Various extracts and fractions successfully induce apoptosis, cell-cycle modulation, apoptosis, and anti-proliferative activity. Therefore, there is a pressing need to develop new anti-cancer drugs of natural origins to reduce the effects on normal cells. Here, we’ve emphasized the most critical elements: i) A better understanding of cancer progression and development and its origins, ii) Molecular strategies to inhibit the cell proliferation/Carcino-genesis, iii) Critical regulators of cancer cell proliferation and development, iv) Signaling Pathways in Apoptosis: Potential Targets for targeted therapeutics, v) Why Apoptosis induction is mandatory for effective chemotherapy, vi) Plants extracts/fractions as potential apoptotic inducers, vii) Marine extracts as Apoptotic inducers, viii) Marine isolated Targeted compounds as Apoptotic inducers (FDA Approved/treatment Phase). This study provides a potential therapeutic option for cancer, although more clinical studies are needed to verify its efficacy in cancer chemotherapy.

In vitro 3D liver tumor microenvironment models for immune cell therapy optimization.

Despite diagnostic and therapeutic advances, liver cancer kills more than 18 million people every year worldwide, urging new strategies to model the disease and to improve the current therapeutic options. In vitro tumor models of human cancer continue to evolve, and they represent an important screening tool. However, there is a tremendous need to improve the physiological relevance and reliability of these in vitro models to fulfill today's research requirements for better understanding of cancer progression and treatment options at different stages of the disease. This review describes the hepatocellular carcinoma microenvironmental characteristics and illustrates the current immunotherapy strategy to fight the disease. Moreover, we present a recent collection of 2D and 3D in vitro liver cancer models and address the next generation of in vitro systems recapitulating the tumor microenvironment complexity in more detail.

Tracing cell lineages in videos of lens-free microscopy.

In vitro experiments with cultured cells are essential for studying their growth and migration pattern and thus, for gaining a better understanding of cancer progression and its treatment. Recent progress in lens-free microscopy (LFM) has rendered it an inexpensive tool for label-free, continuous live cell imaging, yet there is only little work on analysing such time-lapse image sequences. We propose (1) a cell detector for LFM images based on fully convolutional networks and residual learning, and (2) a probabilistic model based on moral lineage tracing that explicitly handles multiple detections and temporal successor hypotheses by clustering and tracking simultaneously. (3) We benchmark our method in terms of detection and tracking scores on a dataset of three annotated sequences of several hours of LFM, where we demonstrate our method to produce high quality lineages. (4) We evaluate its performance on a somewhat more challenging problem: estimating cell lineages from the LFM sequence as would be possible from a corresponding fluorescence microscopy sequence. We present experiments on 16 LFM sequences for which we acquired fluorescence microscopy in parallel and generated annotations from them. Finally, (5) we showcase our methods effectiveness for quantifying cell dynamics in an experiment with skin cancer cells.

Epithelial-mesenchymal Transition in Tumor Tissue and Its Role for Metastatic Spread of Cancer

Metastasis, recurrence, and resistance to chemotherapy are leading causes of the majority of cancer-related mortality worldwide. The process of metastasis can be artificially divided into a series of sequential, highly organized, and organ-specific steps. The underlying mechanisms are still poorly understood, but are believed to be mediated by epithelial-mesenchymal transition (EMT). First described in embryogenesis, EMT is a cellular reprogramming process in which epithelial cells acquire a mesenchymal phenotype. During this transformation, epithelial cells lose their shape, epithelial markers, and ability to grow in colonies. They acquire a spindle-shaped morphology and exhibit more motile and invasive behavior. These phenotypic changes are associated with modifications in different interconnected protein and gene families, such as transcription factors, cadherins, catenins, matrix metalloproteases, and growth receptors. EMT has been observed in many cancers, such as breast, ovarian, colon, and esophageal cancers, and is associated with poor prognosis and metastasis. Also, resistance to cytotoxic treatments is associated with reactivation of embryonic programs. Understanding this process is necessary to provide a better understanding of cancer progression and could lead to the development of new therapeutic or prognostic strategies for the treatment of cancer. This article summarizes the known molecular pathways involved in EMT in cancer.Key words: epithelial-mesenchymal transition - carcinoma - metastasisThe authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers.Submitted: 24. 6. 2016Accepted: 14. 11. 2016.

Noninvasive Imaging of CD206-Positive M2 Macrophages as an Early Biomarker for Post-Chemotherapy Tumor Relapse and Lymph Node Metastasis.

Tumor relapse after initial regression post-chemotherapy is a major challenge in cancer treatment, as it usually leads to local-regional recurrence or inoperable distant metastasis. M2 macrophages diminish the tumor-inhibitory effect of chemotherapy and correlate with distant metastasis and poor prognosis. In this study, we investigated whether molecular imaging of M2 macrophages could serve as an early biomarker for tumor relapse after chemotherapy and tumor lymph node metastasis in preclinical mouse models. Methods: We developed M2 macrophage-targeted probes for near-infrared fluorescence (NIRF) imaging and single-photon emission computed tomography (SPECT) using an anti-CD206 monoclonal antibody. The specific targeting capacity and potential applications of the NIRF and SPECT probes were investigated in subcutaneous tumor and lymph node metastasis models of 4T1 murine breast cancer. Results: M2 macrophage infiltration was significantly increased in the 4T1 tumors that later underwent relapse but not in non-relapsing 4T1 tumors after cyclophosphamide treatment. Through NIRF imaging and SPECT using our synthesized probes, the infiltration of M2 macrophages in relapsing tumors and tumor lymph node metastasis could be sensitively detected. Importantly, early prediction of tumor relapse by molecular imaging of M2 macrophages resulted in an effective eradication of tumors upon combination with additional radiotherapy. Conclusion: Our findings demonstrate that M2 macrophage-targeted imaging allows for noninvasively predicting post-chemotherapy tumor relapse and sensitively detecting the metastatic lymph nodes in vivo. This imaging strategy could provide a better understanding of cancer progression, enable early prediction of tumor resistance, and have implications on the rational design of cancer therapeutics.

Glycoprotein asporin as a novel player in tumour microenvironment and cancer progression.

Small leucine rich proteoglycans (SLRPs), major non-collagen components of the extracellular matrix (ECM), have multiple biological roles with diverse effects. Asporin, a member of the SLRPs class I, competes with other molecules in binding to collagen and affects its mineralization. Its role in cancer is only now being elucidated. The PubMed online database was used to search relevant reviews and original articles. Furthermore, altered asporin expression was analysed in publicly available genome-wide expression data at the Gene Expression Omnibus database. Polymorphisms in the N-terminal polyaspartate domain, which binds calcium, are associated with osteoarthritis and prostate cancer. Asporin also promotes the progression of scirrhous gastric cancer where it is required for coordinated invasion by cancer associated fibroblasts and cancer cells. Besides the enhanced expression of asporin observed in multiple cancer types, such as breast, prostate, gastric, pancreas and colon cancer, tumour suppressive effects of asporin were described in triple-negative breast cancer. We also discuss a number of factors modulating asporin expression in different cell types relevant for alterations toing the tumour microenvironment. The apparent contradicting tumour promoting and suppressive effects of asporin require further investigation. Deciphering the role of asporin and other SLRPs in tumour-stroma interactions is needed for a better understanding of cancer progression and potentially also for novel tumour microenvironment based therapies.

Combined Population Dynamics and Entropy Modelling Supports Patient Stratification in Chronic Myeloid Leukemia.

Modelling the parameters of multistep carcinogenesis is key for a better understanding of cancer progression, biomarker identification and the design of individualized therapies. Using chronic myeloid leukemia (CML) as a paradigm for hierarchical disease evolution we show that combined population dynamic modelling and CML patient biopsy genomic analysis enables patient stratification at unprecedented resolution. Linking CD34+ similarity as a disease progression marker to patient-derived gene expression entropy separated established CML progression stages and uncovered additional heterogeneity within disease stages. Importantly, our patient data informed model enables quantitative approximation of individual patients’ disease history within chronic phase (CP) and significantly separates “early” from “late” CP. Our findings provide a novel rationale for personalized and genome-informed disease progression risk assessment that is independent and complementary to conventional measures of CML disease burden and prognosis.

ELMO3: A direct driver of cancer metastasis?

The development of distant metastases in vital organs is the most deadly aspect of cancer. This is mainly due to most metastatic cancers being inoperable, and treatment options for the later stages of the disease mainly aim at prolonging life rather than curing the patients. Thus, we need a better understanding of cancer progression in order to develop better treatment strategies for these patients. Metastasis is, however, a complex multi-step process that requires a yet unknown number of cellular changes. The most fundamental steps include a local invasion, intravasation, survival in the circulation, extravasation, and finally colonization and proliferation at the new site. Characterization of the features distinguishing cancer cells with metastatic capabilities from those without may enable the discovery of new diagnostic and prognostic biomarkers as well as therapeutic targets. Unfortunately, this task is not straightforward (Fig. 1). We believe that comparisons of primary tumor tissues with matched surgically resected metastases are instrumental for this endeavor, however, comparisons with relevant cancer cells without metastatic capabilities are of equal importance.

TGF-β signalling and its role in cancer progression and metastasis

The transforming growth factor-β (TGF-β) system signals via protein kinase receptors and SMAD mediators to regulate a large number of biological processes. Alterations of the TGF-β signalling pathway are implicated in human cancer. Prior to tumour initiation and early during progression, TGF-β acts as a tumour suppressor; however, at later stages, it is often a tumour promoter. Knowledge about the mechanisms involved in TGF-β signal transduction has allowed a better understanding of cancer progression, invasion, metastasis and epithelial-to-mesenchymal transition. Furthermore, several molecular targets with great potential in therapeutic interventions have been identified. This review discusses the TGF-β signalling pathway, its involvement in cancer and current therapeutic approaches.