Cancer and Signaling Pathway Deregulation

2011 ◽  
pp. 369-379
Author(s):  
Yingchun Liu
Keyword(s):  
Cancer Patients ◽  
Tumor Cells ◽  
Malignant Tumor ◽  
Molecular Mechanisms ◽  
Complex Disease ◽  
Cancer Therapies ◽  
Normal Cells ◽  
Genetic Aberrations ◽  
Cancer Subtypes ◽  
Pathway Deregulation

Cancer is a complex disease that is associated with a variety of genetic aberrations. The diagnosis and treatment of cancer have been difficult because of poor understanding of cancer and lack of effective cancer therapies. Many studies have investigated cancer from different perspectives. It remains unclear what molecular mechanisms have triggered and sustained the transition of normal cells to malignant tumor cells in cancer patients. This chapter gives an introduction to the genetic aberrations associated with cancer and a brief view of the topics key to decode cancer, from identifying clinically relevant cancer subtypes to uncovering the pathways deregulated in particular subtypes of cancer.

Molecular mechanisms for vascular complications of targeted cancer therapies

2016 ◽  
Vol 130 (20) ◽  
pp. 1763-1779 ◽  
Author(s):  
Srila Gopal ◽  
Kenneth B. Miller ◽  
Iris Z. Jaffe
Keyword(s):  
Cancer Patients ◽  
Molecular Mechanisms ◽  
Cell Function ◽  
Vascular Complications ◽  
Vascular Complication ◽  
Cancer Therapies ◽  
Vegf Inhibitors ◽  
Increased Risk ◽  
Anti Cancer ◽  
Targeted Cancer Therapies

Molecularly targeted anti-cancer therapies have revolutionized cancer treatment by improving both quality of life and survival in cancer patients. However, many of these drugs are associated with cardiovascular toxicities that are sometimes dose-limiting. Moreover, the long-term cardiovascular consequences of these drugs, some of which are used chronically, are not yet known. Although the scope and mechanisms of the cardiac toxicities are better defined, the mechanisms for vascular toxicities are only beginning to be elucidated. This review summarizes what is known about the vascular adverse events associated with three classes of novel anti-cancer therapies: vascular endothelial growth factor (VEGF) inhibitors, breakpoint cluster-Abelson (BCR-ABL) kinase inhibitors used to treat chronic myelogenous leukaemia (CML) and immunomodulatory agents (IMiDs) used in myeloma therapeutics. Three of the best described vascular toxicities are reviewed including hypertension, increased risk of acute cardiovascular ischaemic events and arteriovenous thrombosis. The available data regarding the mechanism by which each therapy causes vascular complication are summarized. When data are limited, potential mechanisms are inferred from the known effects of inhibiting each target on vascular cell function and disease. Enhanced understanding of the molecular mechanisms of vascular side effects of targeted cancer therapy is necessary to effectively manage cancer patients and to design safer targeted cancer therapies for the future.

scholarly journals Molecular mechanisms of hemostasis impairment in oncology

2021 ◽  
Vol 20 (4) ◽  
pp. 191-198
Author(s):  
E. M. Koltsova ◽  
G. S. Svidelskaya ◽  
Yu. A. Shifrin ◽  
F. I. Ataullakhanov
Keyword(s):  
Cancer Patients ◽  
Tumor Cells ◽  
Anticancer Drugs ◽  
Molecular Mechanisms ◽  
Current Knowledge ◽  
Neoplastic Transformation ◽  
Malignant Neoplasms ◽  
Coagulation Disorders ◽  
Platelet Dysfunction ◽  
Hemostasis System

Malignant neoplasms are characterized by the presence of the hemostasis system pathology, predisposing cancer patients to thrombohemorrhagic complications. The pathogenesis of cancer-associated coagulopathy is complex and involves a variety of mechanisms. Tumor cells have the ability to activate the host’s hemostasis system, and this phenomenon is controlled by the same oncogenes that are responsible for neoplastic transformation. In addition to predisposing factors to impaired hemostasis from the side of the disease, the anticancer drugs themselves carry risks of developing coagulation disorders. The pathophysiological basis of this kind of disorders caused by chemotherapy is associated with damage to the endothelium, imbalance of coagulation and anticoagulant proteins, platelet dysfunction and their deficiency. In this article, the authors set themselves the goal of generalizing and updating the current knowledge of the molecular mechanisms that cause thrombohemorrhagic risk in cancer. 

scholarly journals Molecular mechanisms of autophagy and its role in cancer development

2016 ◽  
Vol 64 (3) ◽  
pp. 529
Author(s):  
Kathleen Salazar-Ramírez ◽  
Jhonny Molinares-Rodríguez ◽  
Samir Bolívar-González
Keyword(s):  
Cancer Patients ◽  
Tumor Cells ◽  
Therapeutic Efficacy ◽  
Molecular Mechanisms ◽  
Evolutionary Process ◽  
Cancer Development ◽  
Cell Homeostasis ◽  
Pathological Conditions ◽  
Extracellular Stimuli

Autophagy is an evolutionary process preserved in eukaryotes, which removes harmful components and maintains cell homeostasis in response to a variety of extracellular stimuli. It is involved in both physiological and pathological conditions, including cancer.The role of autophagy in the treatment of cancer is described as a “double-edged sword”, which reflects its involvement in tumor suppression, survival and subsequent proliferation of tumor cells. Recent advances are useful for planning appropriate adjustments to inhibit or promote autophagy in order to obtain therapeutic efficacy in cancer patients. The objectives of this review are to clarify the role of autophagy in cancer and to highlight the need for more research in the field.

scholarly journals Optimization of an enrichment process for circulating tumor cells from the blood of head and neck cancer patients through depletion of normal cells

2009 ◽  
Vol 102 (2) ◽  
pp. 521-534 ◽  
Author(s):  
Liying Yang ◽  
James C. Lang ◽  
Priya Balasubramanian ◽  
Kris R. Jatana ◽  
David Schuller ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Cancer Patients ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Neck Cancer ◽  
Normal Cells ◽  
Enrichment Process

Ovarian cancer and the evolution of subtype classifications using transcriptional profiling†

2019 ◽  
Vol 101 (3) ◽  
pp. 645-658 ◽  
Author(s):  
David P Cook ◽  
Barbara C Vanderhyden
Keyword(s):  
Ovarian Cancer ◽  
Molecular Mechanisms ◽  
Complex Disease ◽  
Transcriptional Profiling ◽  
Model Systems ◽  
Valuable Insight ◽  
Cancer Subtypes ◽  
Molecular Alterations ◽  
Spatially Resolved ◽  
Technological Advances

AbstractOvarian cancer is a complex disease with multiple subtypes, each having distinct histopathologies and variable responses to treatment. This review highlights the technological milestones and the studies that have applied them to change our definitions of ovarian cancer. Over the past 50 years, technologies such as microarrays and next-generation sequencing have led to the discovery of molecular alterations that define each of the ovarian cancer subtypes and has enabled further subclassification of the most common subtype, high-grade serous ovarian cancer (HGSOC). Improvements in mutational profiling have provided valuable insight, such as the ubiquity of TP53 mutations in HGSOC tumors. However, the information derived from these technological advances has also revealed the immense heterogeneity of this disease, from variation between patients to compositional differences within single masses. In looking forward, the emerging technologies for single-cell and spatially resolved transcriptomics will allow us to better understand the cellular composition and structure of tumors and how these contribute to the molecular subtypes. Attempts to incorporate the complexities ovarian cancer has resulted in increasing sophistication of model systems, and the increased precision in molecular profiling of ovarian cancers has already led to the introduction of inhibitors of poly (ADP-ribose) polymerases as a new class of treatments for ovarian cancer with DNA repair deficiencies. Future endeavors to define increasingly accurate classification strategies for ovarian cancer subtypes will allow for confident prediction of disease progression and provide important insight into potentially targetable molecular mechanisms specific to each subtype.

scholarly journals Pan-Cancer Integrative Analysis of Whole-Genome De novo Somatic Point Mutations Reveals 17 Cancer Types

2021 ◽  
Author(s):  
Amirreza Kazemi ◽  
Amin Ghareyazi ◽  
Kimia Hamidieh ◽  
Hamed Dashti ◽  
Maedeh Tahaei ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Molecular Mechanisms ◽  
High Throughput Sequencing ◽  
Specific Treatment ◽  
Cancer Drug ◽  
Cancer Type ◽  
Cancer Subtypes ◽  
Genotypic Analysis ◽  
Cancer Types ◽  
Pan Cancer

The advent of high throughput sequencing has enabled researchers to systematically evaluate the genetic variations in cancer, resulting in identifying many cancer-associated genes. Although cancers in the same tissue are widely categorized in the same group, they demonstrate many differences concerning their mutational profiles. Hence there is no “silver bullet” for the treatment of a cancer type. This reveals the importance of developing a pipeline to identify cancer-associated genes accurately and re-classify patients with similar mutational profiles. Classification of cancer patients with similar mutational profiles may help discover subtypes of cancer patients who might benefit from specific treatment types. In this study, we propose a new machine learning pipeline to identify protein-coding genes mutated in a significant portion of samples to identify cancer subtypes. We applied our pipeline to 12270 samples collected from the International Cancer Genome Consortium (ICGC), covering 19 cancer types. Here we identified 17 different cancer subtypes. Comprehensive phenotypic and genotypic analysis indicates distinguishable properties, including unique cancer-related signaling pathways, in which, for most of them, targeted treatment options are currently available. This new subtyping approach offers a novel opportunity for cancer drug development based on the mutational profile of patients. We also comprehensive study the causes of mutations among samples in each subtype by mining the mutational signatures, which provides important insight into their active molecular mechanisms. Some of the pathways we identified in most subtypes, including the cell cycle and the Axon guidance pathways, are frequently observed in cancer disease. Interestingly, we also identified several mutated genes and different rates of mutation in multiple cancer subtypes. In addition, our study on “gene-motif” suggests the importance of considering both the context of the mutations and mutational processes in identifying cancer-associated genes. The source codes for our proposed clustering pipeline and analysis are publicly available at: https://github.com/bcb-sut/Pan-Cancer.

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