59 research outputs found
Eureka – objective assessment of the empty pelvis syndrome to measure volumetric changes in pelvic dead space following pelvic exenteration
No full textBackground: large tissue defects following pelvic exenteration (PE) fill with fluid and small bowel, leading to the “the empty pelvis syndrome” (EPS). EPS causes a constellation of complications including pelvic sepsis and reduced quality-of-life. EPS remains poorly defined and cannot be objectively measured. Pathophysiology of EPS is multifactorial, with increased pelvic dead space potentially important. This study aims to describe methodology to objectively measure volumetric changes relating to EPS.Methods: the true pelvis is defined by the pelvic inlet and outlet. Within the true pelvis there is physiological pelvic dead space (PDS) between the peritoneal reflection and the inlet. This dead space is increased following PE and is defined as the exenteration pelvic dead space (EPD). EPD may be reduced with pelvic filling, the volume of filling is defined as the pelvic filling volume (PFV). PDS, EPD, and PFV were measured intra-operatively using a bladder syringe, and Archimedes’ water displacement principle. Results: a patient undergoing total infralevator PE, had a PDS of 50ml. A rectus flap rendered the pelvic outlet watertight. EPD was then measured as 540ml, therefore there was a 10.8-fold increase in true pelvis dead space. An omentoplasty was placed into the EPD, displacing 130ml, therefore percentage of PFV to EPD was 24.1%. Conclusions: this is the first reported quantitative assessment of pathophysiological volumetric changes of pelvic dead space – these measurements may correlate to severity of EPS. PDS, EPD and PFV should be amendable to assessment based on peri-operative cross-sectional imaging, allowing for potential prediction of EPS-related outcomes
Clinical relevance, prognostic potential, and therapeutic strategies of noncoding RNAs in cancer
No full textNoncoding RNAs (ncRNAs) are master regulators of the genome, controlling the most fundamental of cellular processes. Several hundred studies have demonstrated their dysregulation across a range of cancer types, and translational follow-on studies have led to the development of putative ncRNA biomarkers for identification and staging of cancer. Additionally, mechanistic studies have clearly identified key functions for ncRNAs in cancer progression, and highlighted actionable pathways to be targeted by ncRNA-directed therapies. Consequently, ncRNA-derived therapeutics is now entering later stage clinical trials. In this chapter, we describe the classification of ncRNAs, their biology, and their potential clinical applications
Profiling the microRNA payload of exosomes derived from ex vivo primary colorectal fibroblasts
No full textThe tumor microenvironment is a heterogeneous and dynamic network that exists between cancer and stroma, playing a critical role in cancer progression. Certain tumorigenic signals such as microRNAs are derived from the stroma and conveyed to cancer cells (and vice versa) in nanoparticles called exosomes. Their identification and characterization is an important step in better understanding cellular cross talk and its consequences. To this end we describe how to culture primary ex vivo derived fibroblasts from colorectal tissue, isolate their exosomes, extract exosomal RNA and perform microRNA profiling
Novel biomarkers for patient stratification in colorectal cancer: A review of definitions, emerging concepts, and data
No full textColorectal cancer (CRC) treatment has become more personalised, incorporating a combination of the individual patient risk assessment, gene testing, and chemother apy with surgery for optimal care. The improvement of staging with high-resolution imaging has allowed more selective treatments, optimising survival outcomes. The next step is to identify biomarkers that can inform clinicians of expected prognosis and offer the most beneficial treatment, while reducing unnecessary morbidity for the patient. The search for biomarkers in CRC has been of significant interest, with questions remaining on their impact and applicability. The study of biomarkers can be broadly divided into metabolic, molecular, microRNA, epithelial-to-mesenchymal-transition (EMT), and imaging classes. Although numerous molecules have claimed to impact prognosis and treatment, their clinical application has been limited. Furthermore, routine testing of prognostic markers with no demonstrable influence on response to treatment is a questionable practice, as it increases cost and can adversely affect expectations of treatment. In this review we focus on recent developments and emerging biomarkers with potential utility for clinical translation in CRC. We examine and critically appraise novel imaging and molecular-based approaches; evaluate the promising array of microRNAs, analyze metabolic profiles, and highlight key findings for biomarker potential in the EMT pathway.</p
ERCC1 abundance is an indicator of DNA repair-apoptosis decision upon DNA damage
No full textDNA repair is essential for successful propagation of genetic material and fidelity of transcription. Nucleotide excision repair (NER) is one of the earliest DNA repair mechanisms, functionally conserved from bacteria to human. The fact that number of NER genes vary significantly between prokaryotes and metazoans gives the insight that NER proteins have evolved to acquire additional functions to combat challenges associated with a diploid genome, including being involved in the decision between DNA repair and apoptosis. However, no direct association between apoptosis and NER proteins has been shown to date. In this study, we induced apoptosis with a variety of agents, including oxaliplatin, doxorubicin and TRAIL, and observed changes in the abundance and molecular weight of NER complex proteins. Our results showed that XPA, XPC and ERCC1 protein levels change during DNA damage-induced apoptosis. Among these, ERCC1 decrease was observed as a pre-mitochondria depolarisation event which marks the “point of no return” in apoptosis signalling. ERCC1 decrease was due to proteasomal degradation upon lethal doses of oxaliplatin exposure. When ERCC1 protein was stabilised using proteasome inhibitors, the pro-apoptotic activity of oxaliplatin was attenuated. These results explain why clinical trials using proteasome inhibitors and platinum derivatives showed limited efficacy in carcinoma treatment and also the importance of how deep understanding of DNA repair mechanisms can improve cancer therapy
SELDI-TOF MS Proteomics in Breast Cancer
No full textBackground: Proteomic profiling is a rapidly developing technology that may enable early disease screening and diagnosis. Surface-enhanced laser desorption ionization–time of flight mass spectrometry (SELDI-TOF MS) has demonstrated promising results in screening and early detection of many diseases. In particular, it has emerged as a high-throughput tool for detection and differentiation of several cancer types. This review aims to appraise published data on the impact of SELDI-TOF MS in breast cancer. Methods: A systematic literature search between 1965 and 2009 was conducted using the PubMed, EMBASE, and Cochrane Library databases. Studies covering different aspects of breast cancer proteomic profiling using SELDI-TOF MS technology were critically reviewed by researchers and specialists in the field. Results: Fourteen key studies involving breast cancer biomarker discovery using SELDI-TOF MS proteomic profiling were identified. The studies differed in their inclusion and exclusion criteria, biologic samples, preparation protocols, arrays used, and analytical settings. Taken together, the numerous studies suggest that SELDI-TOF MS methodology may be used as a fast and robust approach to study the breast cancer proteome and enable the analysis of the correlations between proteomic expression patterns and breast cancer. Conclusion: SELDI-TOF MS is a promising high-throughput technology with potential applications in breast cancer screening, detection, and prognostication. Further studies are needed to resolve current limitations and facilitate clinical utility. <br/
The Use of Hellinger Distance Undersampling Model to Improve the Classification of Disease Class in Imbalanced Medical Datasets
No full textImbalanced class distribution in the medical dataset is a challenging task that hinders classifying disease correctly. It emerges when the number of healthy class instances being much larger than the disease class instances. To solve this problem, we proposed undersampling the healthy class instances to improve disease class classification. This model is named Hellinger Distance Undersampling (HDUS). It employs the Hellinger Distance to measure the resemblance between majority class instance and its neighbouring minority class instances to separate classes effectively and boost the discrimination power for each class. An extensive experiment has been conducted on four imbalanced medical datasets using three classifiers to compare HDUS with a baseline model and three state-of-the-art undersampling models. The outcomes display that HDUS can perform better than other models in terms of sensitivity, F1 measure, and balanced accuracy
The colorectal cancer microenvironment: strategies for studying the role of cancer-associated fibroblasts
No full textColorectal cancer (CRC) is a key public health concern and the second highest cause of cancer related death in Western society. A dynamic interaction exists between CRC cells and the surrounding tumor microenvironment, which can stimulate not only the development of CRC, but its progression and metastasis, as well as the development of resistance to therapy. In this chapter, we focus on the role of fibroblasts within the CRC tumor microenvironment and describe some of the key methods for their study, as well as the evaluation of dynamic interactions within this biological ecosystem.</p
Exosomal microRNAs (exomiRs): small molecules with a big role in cancer
No full textExosomes are secreted vesicles which can transmit molecular cargo between cells. Exosomal microRNAs (exomiRs) have drawn much attention in recent years because there is increasing evidence to suggest that loading of microRNAs into exosomes is not a random process. Preclinical studies have identified functional roles for exomiRs in influencing many hallmarks of cancer. Mechanisms underpinning their actions, such as exomiR receptors ("miRceptors"), are now becoming apparent. Even more exciting is the fact that exomiRs are highly suitable candidates for use as non-invasive biomarkers in an era of personalized cancer medicine.</p
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