Infrared Imaging for Diagnosis and Prediction of the Biopotental of Low and Intermediate Risk Prostate Cancer

红外成像用于低度和中度风险前列腺癌的生物电诊断和预测

• 批准号: EP/I027440/1
• 负责人: Peter Gardner
• 金额: $ 60.71万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FI027440%2F1
• 关键词: Infrared; Imaging; Diagnosis; Prediction; Biopotental

More than a quarter of a million people are diagnosed with cancer annually in the UK and the four most common ones, breast, lung, bowel and prostate cancer, make up over half of all these cases. Many, such as prostate cancer correlate strongly with age, 77% of cases being diagnosed in men over the age of 55. This produces a compound problem, as Western populations are ageing rapidly and the number of people diagnosed with cancer in European countries is inevitably going to rise. This will put a considerable strain on all parts of the health care systems and will have dramatic effects on health care costs. The problem is particularly prescient in certain cancers such as prostate cancer and breast cancer, which are endemic in the older population and whose natural history is uncertain in many cases. There is a clear clinical need for a robust and preferably automated system which can not only facilitate the pathological diagnosis but also to discriminate between tumours of low risk, which require surveillance or less aggressive treatment, and those of high risk, which will progress more rapidly and which need aggressive intervention to prevent morbidity and death. We have shown previously in small scale studies that infra red spectral markers used in conjunction with algorithmic models can be utilised not only to provide tumour grading data but also to provide staging and prognostic information. The attraction of infrared spectroscopy to aid clinical diagnosis is that it is a widely known technology which is readily available, reliable, simple to use and relatively inexpensive. It also allows further post scanning interrogation because it does not destroy the tissue under investigation. However, introduction into the clinical environment has been hampered by a lack of understanding of some of the fundamental principles. We have successfully addressed many of the fundamental issue with single cells and aim to utilize this knowledge to address scanning of tissue biopsiesThe aim of this proposal is to develop techniques using spectroscopic analysis of cancer tissue, which build on a strong scientific base developed by our collaborative research group and by others working in this field. We propose to develop rapid and accurate systems of analysis, which can be applied to the identification and characterisation of biological tissues and we will use prostate cancer as the primary model.Using prostate cancer as our model of low and high risk disease we will adapt existing technologies and protocols to enable rapid high throughput infra red screening of tissue samples which could be transferred from the research laboratory into a standard pathology laboratory. We will then use this system to develop a model, which can distinguish between low and high risk prostate cancers in samples that have been previously graded as low or intermediate grade prostate cancers and of known outcome. This model will then be blind tested using a large set of low and intermediate grade prostate cancers to assess the ability of the model to predict disease outcome. An added benefit of spectral screening is that interrogation of the spectral differences between high and low risk disease will direct research towards novel molecular markers that may shed light on tumour progression as well as generating new molecular diagnostic markers for use in the clinic. As the technique is non destructive any new markers identified can be tested back on the original tissue it was discovered from.We envision that development and robust testing of the system will lead to a powerful diagnostic and prognostic tool that may be incorporated in to oncological practice both in the laboratory and the clinic and that it will potentially describe new techniques with utility in other areas of bio-health and biological science.

在英国，每年有超过 25 万人被诊断患有癌症，其中四种最常见的癌症：乳腺癌、肺癌、肠癌和前列腺癌，占所有癌症病例的一半以上。许多癌症，例如前列腺癌，与年龄密切相关，77% 的病例是在 55 岁以上的男性中诊断出来的。这产生了一个复杂的问题，因为西方人口正在迅速老龄化，欧洲国家被诊断出患有癌症的人数不可避免地会增加。这将对医疗保健系统的各个部分造成相当大的压力，并对医疗保健费用产生巨大影响。这个问题在某些癌症中尤其有先见之明，例如前列腺癌和乳腺癌，这些癌症在老年人群中流行，并且在许多情况下其自然史是不确定的。临床显然需要一种强大且优选自动化的系统，该系统不仅可以促进病理诊断，还可以区分低风险肿瘤和高风险肿瘤，低风险肿瘤需要监测或不太积极的治疗，而高风险肿瘤进展更快，需要积极干预以防止发病和死亡。我们之前在小规模研究中表明，与算法模型结合使用的红外光谱标记不仅可以用来提供肿瘤分级数据，还可以提供分期和预后信息。红外光谱法辅助临床诊断的吸引力在于它是一种众所周知的技术，易于获得、可靠、使用简单且相对便宜。它还允许进一步的扫描后询问，因为它不会破坏所研究的组织。然而，由于缺乏对一些基本原理的理解，该技术引入临床环境受到了阻碍。我们已经成功解决了单细胞的许多基本问题，并旨在利用这些知识来解决组织活检的扫描问题。该提案的目的是开发使用癌症组织光谱分析的技术，该技术建立在我们的合作研究小组和该领域其他工作人员开发的强大科学基础之上。我们建议开发快速准确的分析系统，可应用于生物组织的识别和表征，我们将使用前列腺癌作为主要模型。使用前列腺癌作为我们的低风险和高风险疾病模型，我们将调整现有技术和协议，以实现组织样本的快速高通量红外筛查，这些样本可以从研究实验室转移到标准病理学实验室。然后，我们将使用该系统开发一个模型，该模型可以区分先前已分级为低级或中级前列腺癌且结果已知的样本中的低风险和高风险前列腺癌。然后将使用大量低级和中级前列腺癌对该模型进行盲测，以评估该模型预测疾病结果的能力。光谱筛查的另一个好处是，对高风险疾病和低风险疾病之间的光谱差异的询问将指导研究新的分子标记，这些标记可能揭示肿瘤的进展，并产生用于临床的新的分子诊断标记。由于该技术是非破坏性的，任何识别出的新标记都可以在其发现的原始组织上进行测试。我们设想，该系统的开发和稳健测试将带来强大的诊断和预后工具，可以将其纳入实验室和临床的肿瘤学实践中，并且它有可能描述在生物健康和生物科学其他领域具有实用性的新技术。

项目成果

FTIR microspectroscopy of selected rare diverse sub-variants of carcinoma of the urinary bladder

• DOI: 10.1002/jbio.201200126
• 发表时间: 2013-01-01
• 期刊: JOURNAL OF BIOPHOTONICS
• 影响因子: 2.8
• 作者: Hughes, Caryn;Iqbal-Wahid, Junaid;Gardner, Peter
• 通讯作者: Gardner, Peter

Assessment of paraffin removal from prostate FFPE sections using transmission mode FTIR-FPA imaging

• DOI: 10.1039/c3ay41308j
• 发表时间: 2014-01-01
• 期刊: ANALYTICAL METHODS
• 影响因子: 3.1
• 作者: Hughes, Caryn;Gaunt, Lydia;Gardner, Peter
• 通讯作者: Gardner, Peter

Using Fourier transform IR spectroscopy to analyze biological materials.

使用傅立叶变换红外光谱法分析生物材料。

• DOI: 10.1038/nprot.2014.110
• 发表时间: 2014-08
• 期刊: Nature protocols
• 影响因子: 14.8