Alpha B-crystallin, a new independent marker for poor prognosis in head and neck cancer

Objectives. Gene expression profiling has provided many insights into tumor progression but translation to clinical practice has been limited. We have previously identified a list of potential markers by the differences of expression profiling of seven matched head and neck cancer (HNSCC) tumors with autologous normal oral mucosa (NOM). Alpha B-crystallin (CRYAB) was in the top 5% of genes identified with statistically significant differences in expression between tumor and NOM at the mRNA level. The objective was to confirm this in routine paraffin sections at the protein level. Study Design: The level of alpha B-crystallin was determined in tumors of 62 HNSCC patients whose prognosis was known for 5 years. Methods. Immunohistochemical detection of alpha B-crystallin expression was performed on HNSCC paraffin sections. Results. Univariate survival analysis identified lack of alpha B-crystallin staining as an independent prognostic marker for disease-free interval (P < 0.001) and overall survival (P < 0.002) of HNSCC patients over the 5-year observation period. Notably, all 13 patients (100%), including 5 patients with nodal disease whose tumors lacked alpha B-crystallin had no recurrences (P < 0.001). Nineteen of 27 node-negative patients stained positive for alpha B-crystallin and seven of the 19 (36.8%) had recurrences. Conclusion: Presence or absence of expression of alpha B-crystallin was a powerful marker for prognosis in this series of patients.

Foretelling pathology: The poetics of prognosis

This paper examines a number of French middle-brow novels, usually called at the time romans de murs, from the period 1880-1910. It shows how, in these stories, doctors are shown to foretell the course of narrative through the diagnosis of certain pathologies, especially psychosexual ones. These pathologies are thus represented as implacable narrative programmes. In effect, most of these novels renounce the standard fictional resources of intrigue and suspense in favour of the relentless working out of their initial prognosis. The authority of medical discourse is therefore not just confirmed and disseminated: it is elaborated as fatality in the very terms of the novel. Copyright © SAGE Publications.

Predictive gene lists for breast cancer prognosis: a topographic visualisation study

Background: The controversy surrounding the non-uniqueness of predictive gene lists (PGL) of small selected subsets of genes from very large potential candidates as available in DNA microarray experiments is now widely acknowledged 1. Many of these studies have focused on constructing discriminative semi-parametric models and as such are also subject to the issue of random correlations of sparse model selection in high dimensional spaces. In this work we outline a different approach based around an unsupervised patient-specific nonlinear topographic projection in predictive gene lists. Methods: We construct nonlinear topographic projection maps based on inter-patient gene-list relative dissimilarities. The Neuroscale, the Stochastic Neighbor Embedding(SNE) and the Locally Linear Embedding(LLE) techniques have been used to construct two-dimensional projective visualisation plots of 70 dimensional PGLs per patient, classifiers are also constructed to identify the prognosis indicator of each patient using the resulting projections from those visualisation techniques and investigate whether a-posteriori two prognosis groups are separable on the evidence of the gene lists. A literature-proposed predictive gene list for breast cancer is benchmarked against a separate gene list using the above methods. Generalisation ability is investigated by using the mapping capability of Neuroscale to visualise the follow-up study, but based on the projections derived from the original dataset. Results: The results indicate that small subsets of patient-specific PGLs have insufficient prognostic dissimilarity to permit a distinction between two prognosis patients. Uncertainty and diversity across multiple gene expressions prevents unambiguous or even confident patient grouping. Comparative projections across different PGLs provide similar results. Conclusion: The random correlation effect to an arbitrary outcome induced by small subset selection from very high dimensional interrelated gene expression profiles leads to an outcome with associated uncertainty. This continuum and uncertainty precludes any attempts at constructing discriminative classifiers. However a patient's gene expression profile could possibly be used in treatment planning, based on knowledge of other patients' responses. We conclude that many of the patients involved in such medical studies are intrinsically unclassifiable on the basis of provided PGL evidence. This additional category of 'unclassifiable' should be accommodated within medical decision support systems if serious errors and unnecessary adjuvant therapy are to be avoided.

A study of patient-specific prognosis of ovarian cancer

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Lupus prognosis:a clinical study

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Survival prognosis in ovarian cancer

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The Inflation Index Prognosis Based on the Method of Decision-Marking “Tree”

The description of the support system for marking decision in terms of prognosing the inflation level based on the multifactor dependence represented by the decision – marking “tree” is given in the paper. The interrelation of factors affecting the inflation level – economic, financial, political, socio-demographic ones, is considered. The perspectives for developing the method of decision – marking “tree”, and pointing out the so- called “narrow” spaces and further analysis of possible scenarios for inflation level prognosing in particular, are defined.

Multi-agent Systems in the Harvest Prognosis

The paper presents a case study of geo-monitoring a region consisting in the capturing and encoding of human expertise into a knowledge-based system. As soon as the maps have been processed, the data patterns are detected using knowledge-based agents for the harvest prognosis.

Incidentally Raised Cardiac Troponin I Has a Worse Prognosis in Older Patients Compared to Those with Normal Cardiac Troponin I and Patients with Acute Coronary Syndrome : A Cohort Study

Acknowledgement J.H.B.-S. was supported by the Norfolk and Norwich University Hospital (NNUH) Research and Development (R&D) research capability funds between July 2013 and December 2014.

Medium-term prognosis of an incident cohort of parkinsonian patients compared to controls

Funding This work was supported by Parkinson's UK (grant numbers G0502, G0914), BMA Doris Hillier Award, the BUPA Foundation, NHS Grampian Endowments, RS MacDonald Trust.

Immunotherapy for the treatment of poor prognosis cancers

Cancer is amongst the leading causes of death worldwide and the number one cause in the developed world. Every year there are close to 10 million cancer related deaths and this corresponds to hundreds of millions of euro in health care costs and lost productivity, placing a substantial drain on the economy. The efficacy of traditional treatment modalities for cancer therapy, such as surgery, radiotherapy and chemotherapy has plateaued, and while they are undoubtedly effective at prolonging patient lifespan, there is a high rate of adverse side effects and fatal reoccurrence. Currently, there is a huge amount of interest in the areas of cancer immunosurveillance and cancer immuno-editing, which explain some of the complex interactions between the host immune system and cancer. If left unchecked, cancerous malignancies have the ability to generate an immunosuppressive microenvironment, effectively shielding themselves from elimination and promoting tumour growth and progression. To overcome this, the potential of the immune system must be harnessed and the work undertaken in this thesis sought to contribute to this goal. Focus was placed on using novel therapies, combining tumour ablation with immune-modulating antibodies to maximise tumour elimination in an immune dependent manner, to overcome immunosuppression and promote immune activation. Chapter 2 focuses on the use of ECT as a method of tumour ablation and its effects on the immune system. ECT proved to be effective at inhibiting the tumour growth both in vitro and in vivo, and conferred significant survival advantages in both small and large animal models. More importantly, ECT proved to cause tumour death in an immune dependent manner, displaying the hallmarks of Immunogenic Cell Death, increases in immune cell infiltration and generating tumour-specific immune responses. Chapter 3 focuses on combining ECT with immune checkpoint blockade inhibitors; anti- CTLA-4 and anti-PD-1. Both combinations proved to be effective at inhibiting both primary and distal tumour growth, indicating the generation of tumour specific immune responses and prolonged animal survival. In addition, the treatments caused increases in the levels of certain intra-tumoural immune cell subsets and modulated the cytokine profile of treated animals in a way that was favourable overall. Chapter 4 focuses on the combining ECT with an anti-iCOS agonist antibody, capable of causing immune co-stimulation. This novel combinational therapy proved to be the most effective by far, with a high cure rate achieved across a number of different in vivo tumour models. Total regression was seen in both primary and distal tumours, as well as spontaneous metastases, with the tumour specific immune response generated conferring total protection to animals on tumour rechallenge. Overall the data presented here adds further insight into the area of cancer immunotherapy with some of the novel combinational therapies demonstrating substantial clinic potential.