Khaos Research, Universidad de Málaga, Málaga, Spain, Arquitecto Francisco Peñalosa 18, Málaga, 29071, Spain.
Unidad de Oncología Intercentros, Hospitales Univesitarios Regional y Virgen de la Victoria de Málaga, Instituto de Investigaciones Biomédicas (IBIMA), Málaga, Spain, Málaga, Spain.
BMC Bioinformatics. 2019 Apr 18;20(Suppl 4):150. doi: 10.1186/s12859-019-2695-7.
The analysis of gene expression levels is used in many clinical studies to know how patients evolve or to find new genetic biomarkers that could help in clinical decision making. However, the techniques and software available for these analyses are not intended for physicians, but for geneticists. However, enabling physicians to make initial discoveries on these data would benefit in the clinical assay development.
Melanoma is a highly immunogenic tumor. Therefore, in recent years physicians have incorporated immune system altering drugs into their therapeutic arsenal against this disease, revolutionizing the treatment of patients with an advanced stage of the cancer. This has led us to explore and deepen our knowledge of the immunology surrounding melanoma, in order to optimize the approach. Within this project we have developed a database for collecting relevant clinical information for melanoma patients, including the storage of patient gene expression levels obtained from the NanoString platform (several samples are taken from each patient). The Immune Profiling Panel is used in this case. This database is being exploited through the analysis of the different expression profiles of the patients. This analysis is being done with Python, and a parallel version of the algorithms is available with Apache Spark to provide scalability as needed.
VIGLA-M, the visual analysis tool for gene expression levels in melanoma patients is available at http://khaos.uma.es/melanoma/ . The platform with real clinical data can be accessed with a demo user account, physician, using password physician_test_7634 (if you encounter any problems, contact us at this email address: mailto: khaos@lcc.uma.es). The initial results of the analysis of gene expression levels using these tools are providing first insights into the patients' evolution. These results are promising, but larger scale tests must be developed once new patients have been sequenced, to discover new genetic biomarkers.
基因表达水平分析被广泛应用于临床研究中，用于了解患者的病情进展，或寻找有助于临床决策的新的遗传生物标志物。然而，现有的分析技术和软件并非专为医生设计，而是为遗传学家设计的。然而，如果能够让医生能够在这些数据上进行初步发现，将有助于临床检测的发展。
黑色素瘤是一种高度免疫原性的肿瘤。因此，近年来，医生将改变免疫系统的药物纳入他们治疗这种疾病的武器库中，彻底改变了晚期癌症患者的治疗方法。这促使我们探索和深化对黑色素瘤周围免疫学的了解，以优化治疗方法。在这个项目中，我们开发了一个数据库，用于收集黑色素瘤患者的相关临床信息，包括从 NanoString 平台获得的患者基因表达水平的存储（每个患者会采集多个样本）。在这种情况下使用免疫分析面板。通过分析患者不同的表达谱来利用该数据库。该分析是用 Python 完成的，并且有一个 Apache Spark 的并行版本的算法，以根据需要提供可扩展性。
VIGLA-M，用于黑色素瘤患者基因表达水平的可视化分析工具，可在 http://khaos.uma.es/melanoma/ 上访问。带有真实临床数据的平台可以使用演示用户帐户访问，用户名是 physician，密码是 physician_test_7634（如果遇到任何问题，请通过以下电子邮件地址与我们联系：mailto:khaos@lcc.uma.es）。使用这些工具对基因表达水平进行分析的初步结果为患者的病情进展提供了初步的见解。这些结果很有希望，但必须在对新患者进行测序后开发更大规模的测试，以发现新的遗传生物标志物。
