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  • 《细胞》子刊:新的诊断分析方法能为肺癌患者制定个性化治疗方案

    发布时间:2021年08月31日 08:16:11 来源:振东健康网

    《细胞》子刊:新的诊断分析方法能为肺癌患者制定个性化治疗方案

    资讯作者:University of Helsinki

    编辑翻译:奇奇


    本文献于2021年8月18日发表在国际著名期刊《细胞报告医学》(Cell Reports Medicine)上。文中赫尔辛基大学的研究人员发现一种新的诊断分析方法,这种方法能为肺癌患者提供个性化治疗方案,也为其他癌症治疗方案提供了新思路。

    赫尔辛基大学的一项新研究表明,从肺癌中新分离出来的细胞可以用来建立可靠的药物反应数据。这种方法可以识别可操作的或无反应的治疗,案例说明中该分析用于指导对患者的治疗。

    每种癌症组织都是独特的,这让治疗策略复杂化。因此,精准医疗在将治疗方法与患者个体相匹配方面的力量是显而易见的。然而,它在临床上的实际成功仍然有限,特别是对于实体肿瘤。

    肺癌是世界上最常见的癌症,与其他癌症类型相比其预后较差。根据基因突变分析,大约三分之一的非小细胞肺癌患者可以找到匹配的治疗方法,但只有略多于一半的患者受益于这种基因匹配治疗。其中一个问题是缺乏诊断上可解释的检测方法,这种方法可以为特定癌症确定最有希望的治疗方法。

    为了克服这一挑战,由来自赫尔辛基大学芬兰分子医学研究所的Emmy Verschuren领导的研究小组验证了一种检测方法,可以在术后立即对肺癌样本进行药物反应测量。他们将这种潜在方法的研究结果发表在了《细胞报告医学》杂志上。

    对于血液系统恶性肿瘤患者来说,FIMM精准癌症药物的作用以及协同团队通过分析来自患者的血液样本的分析方法,在为患者匹配个性化治疗方面取得了巨大进展。然而,对于实体上皮肿瘤,却不能简单地采用这些方法。

    Emmy博士认为,现在仍然非常需要强大的诊断细胞模型。这是因为现有的诊断细胞模型建立的时间较长,重要的是,还不能保证恶性细胞的扩增。

    Emmy博士说:“为了解是否可以利用肿瘤组织获得可靠的数据,我们已经进行了多年的研究。我们发现肿瘤组织极其脆弱,手术后随着时间的推移,其生物学变化越来越明显。这一点也毫不奇怪。”

    在他们最近与哥本哈根大学的Krister Wennerberg教授合作的概念验证研究中,她的团队旨在开发一种替代方法来规避这些挑战。该团队开始评估未培养的肿瘤细胞群是否可以在分离后立即用于药物分析。研究结果证明了研究人员所谓的新鲜未培养的肿瘤细胞(FUTCs)的效用。

    该团队通过分析20个非小细胞肺癌患者的样本来检测该方法。所用药物筛选小组包含了66种肺癌选择性药物。他们的检测结果表明,在20例患者中有19例产生了可靠的药物反应数据。遗传癌症突变分析和药物敏感性数据很好地匹配,为该方法的有效性提供了进一步的支持。

    根据患者的要求,通过对难治性转移性非小细胞肺癌患者的治疗和现实世界的转化,证实了基于FUTC的功能性方法的前景。根据筛选结果选择三种药物进行治疗,患者从中获得了临床益处。

    该研究的第一作者、来自FIMM的Sarang Talwelkar说:“FUTC检测方法能够在样本收集后72小时左右对癌细胞进行药理学测试,从而以一种个性化的方式影响临床治疗决策。”基于FUTC的诊断还有助于预测临床对高价靶向治疗的无反应,以降低其可观的成本。

    Emmy博士说:“虽然现在还处于早期阶段,需要进一步在活检中检测FUTC分析,但我们希望我们的检测能够越来越多地让复发性肺癌患者受益。”Wennerberg教授补充道:“此外,通过更广泛地适应其他癌症类型的方法,我们可以了解到什么,这也将变得很有意义。”


    英语原文

    New Diagnostic Assay Holds Potential for Tailoring Personalized Cancer Treatment

    A new study from the University of Helsinki shows that cells that are freshly isolated from lung cancers can be used to create robust drug response data. This approach can identify actionable or non-responsive treatments, illustrated by a case study in which the assay was used to guide the compassionate treatment of a patient.

    Each cancer tissue is unique, complicating treatment decisions. The power of precision medicine to match treatments to and individual patient is therefore evident. Yet, its actual success in the clinichas remained limited, particularly for solid tumors.

    Lung cancer is the most common cancer worldwide and has a poor prognosis compared to other cancer types. Based on genetic mutation analyses, matched treatments can be identified for around a third of patients with non-small cell lung cancer, but only just over half of all patients benefit from such gene-matched treatments. One of the issues is the lack of diagnostically interpretable assays that can identify the most promising treatment for a particular cancer.

    To overcome this challenge, a research team led by Emmy Verschuren from the Institute for Molecular Medicine Finland FIMM, University of Helsinki, validated an assay to enable drug response measurements in lung cancer samples immediately following surgery. Their promising approachhas just been published in the journal Cell Reports Medicine.

    For patients with hematological malignancies, the FIMM precision cancer medicine efforts and collaborating teams have made great progress on matching individualized therapies to patients via the analysis of patient-derived blood samples. However, for solid epithelial tumors, these methods cannot simply be adopted.

    According to Dr. Verschuren, there still is a great need for robust diagnostic cell models since the presently available models take long times to be established, and importantly, do not guarantee the expansion of malignant cells.

    “We have invested many years ofresearch to understand whether tumor tissue can be used to obtain reliable data. Not surprisingly, we learned that tissue is extremely fragile, and biological changes are increasingly pronounced with time elapsed since thesurgery,” says Dr. Emmy Verschuren.

    In their recent proof-of-concept study in collaboration with Professor Krister Wennerberg from the University of Copenhagen, her group aimed to develop an alternative approach to circumvent these challenges. The team set out to assess whether uncultured tumor cell populations could be used for drug profiling, immediately following their isolation. The research findings demonstrate the utility of what the researchers called Fresh Uncultured Tumor Cells, or FUTCs.

    The team tested the method by profiling twenty non-small cell lung cancer patient samples. The drug screening panelused contained 66 lung cancer-selective drugs.

    Their results demonstrated that robust drug response data was generated in 19 of 20 patient cases. Genetic cancer mutation analyses and the drug sensitivity data were well aligned, providing further support for the validity of the approach.

    The promise of FUTC-based functional approach was also demonstrated via real-world translation, through compassionate treatment of a patient with refractory metastatic non-small celllung cancer, per the patient's request. The patient received clinical benefit from the treatment with three drugs selected based on the screening results.

    “The FUTC assay enables pharmacological testing of cancer cells in around 72 hours after sample collection and thus offers a possibility to impact treatment decision in the clinic, in anindividualized manner,” says the first author of the study, Sarang Talwelkar from FIMM. FUTC-based diagnostics could additionally help to predict clinical non-responses to highly-priced targeted therapies to decrease their considerable costs.

    “While it remains early days, and further investigation is warranted to test FUTC profiling on biopsies, we are hopeful that our assay can increasingly benefit patients with recurrent lung cancer,” says Dr. Verschuren. “In addition, it will be intriguing to see what we may learn by broader adaptation of the approach to other cancer types,” adds Prof. Wennerberg.


    参考文献

    Sarang S. Talwelkar et al, Functional diagnostics using fresh uncultured lung tumor cells to guide personalized treatments, Cell Reports Medicine (2021). DOI: 10.1016/j.xcrm.2021.100373


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