脂质驱动癌症基础研究背景下的SARIFA生物标志物-动脉网

The SARIFA biomarker in the context of basic research of lipid-driven cancers

Nature 等信源发布 2024-07-31 23:28

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AbstractSARIFA was very recently introduced as a histomorphological biomarker with strong prognostic power for colorectal, gastric, prostate, and pancreatic cancer. It is characterized by the direct contact between tumor cells and adipocytes due to a lack of stromal reaction. This can be easily evaluated on routinely available H&E-slides with high interobserver agreement.

摘要SARIFA最近被引入作为组织形态学生物标志物，对结直肠癌，胃癌，前列腺癌和胰腺癌具有很强的预后能力。它的特征是由于缺乏基质反应，肿瘤细胞和脂肪细胞之间直接接触。这可以很容易地在常规可用的H＆E幻灯片上进行评估，并具有高度的观察者间一致性。

SARIFA also reflects a specific tumor biology driven by metabolic reprogramming. Tumor cells in SARIFA-positive tumors benefit from direct interaction with adipocytes as an external source of lipids. Numerous studies have shown that lipid metabolism is crucial in carcinogenesis and cancer progression.

SARIFA还反映了由代谢重编程驱动的特定肿瘤生物学。SARIFA阳性肿瘤中的肿瘤细胞受益于与脂肪细胞作为脂质外部来源的直接相互作用。大量研究表明，脂质代谢在癌发生和癌症进展中至关重要。

We found that the interaction between tumor cells and adipocytes was not triggered by obesity, as previously assumed. Instead, we believe that this is due to an immunological mechanism. Knowledge about lipid metabolism in cancer from basic experiments can be transferred to develop strategies targeting this reprogramed metabolism..

我们发现，如前所述，肿瘤细胞和脂肪细胞之间的相互作用不是由肥胖引发的。相反，我们认为这是由于免疫机制。基础实验中关于癌症脂质代谢的知识可以转移到开发针对这种重编程代谢的策略。。

IntroductionWe recently introduced SARIFA as a prognostic biomarker in cancer. SARIFA, an acronym for Stroma AReactive Invasion Front Areas, describes the histomorphological phenomenon of direct contact between tumor cells and adipocytes without intervening collagenous or inflammatory stroma. In gastric and colorectal cancer, SARIFA positivity is present when at least five tumor cells with direct contact with adipocytes are identified1,2 (Fig.

简介我们最近引入了SARIFA作为癌症的预后生物标志物。SARIFA是基质区域侵袭前沿区域的缩写，描述了肿瘤细胞和脂肪细胞直接接触而不干预胶原或炎性基质的组织形态学现象。在胃癌和结直肠癌中，当鉴定出至少五个与脂肪细胞直接接触的肿瘤细胞时，存在SARIFA阳性1,2（图）。

1). In contrast, in pancreatic and prostate cancer, a quantitative cut-off has to be defined to achieve better prognostic discrimination. The threshold of five tumor cells has been chosen to define a clear distinction from tumor budding, defined as single cells and clusters of up to four tumor cells.

1）。。已经选择了五个肿瘤细胞的阈值来定义与肿瘤萌芽的明确区别，肿瘤萌芽定义为单个细胞和最多四个肿瘤细胞的簇。

Because the evaluation is based on conventional light microscopy on H&E-stained routine slides, this marker is characterized by unlimited and fast availability, as well as virtual no additional costs. Wulczyn et al. published a very similar but not identical feature named tumor adipose feature (TAF) analyzed by a deep learning approach in the same year as we reported SARIFA3,4.

由于该评估是基于H＆E染色的常规载玻片上的常规光学显微镜，因此该标记的特点是无限制且快速可用，并且虚拟无需额外成本。Wulczyn等人在我们报道SARIFA3,4的同一年发表了一个非常相似但不完全相同的特征，称为肿瘤脂肪特征（TAF）。

Briefly, the authors here aimed at predicting survival of CRC patients directly from routine H&E slides, then explored the human interpretability of important features and hereby identified TAF. In a subsequent pathologist validation study, they could prove that TAF as a machine learning-derived histopathologic feature could indeed be learned and scored by pathologists (3, 4).

简而言之，作者在此旨在直接从常规H＆E幻灯片预测CRC患者的生存率，然后探索重要特征的人类可解释性，并据此确定TAF。在随后的病理学家验证研究中，他们可以证明TAF作为机器学习衍生的组织病理学特征确实可以被病理学家学习和评分（3,4）。

In similar approaches, Foersch et al. and Jiang et al. both also independently identified the proximity of adipocytes and tumor cells as an unfavorable factor in CRC by deploying DL-algorithms5,6.Fig. 1: Histology examples of tumor-adipocyte interaction.a H&E, Scale bar: 500 µm, SARIFA-ne.

在类似的方法中，Foersch等人和Jiang等人也通过部署DL-algorithms5,6独立地将脂肪细胞和肿瘤细胞的接近性鉴定为CRC中的不利因素。图1：肿瘤-脂肪细胞相互作用的组织学例子。H＆E，比例尺：500μm，SARIFA ne。

Data availability

数据可用性

No datasets were generated or analyzed for this article. This word does not include novel data but only refers to original contributions.

本文未生成或分析任何数据集。这个词不包括新颖的数据，只指原始贡献。

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Download referencesAcknowledgementsThis work has been financed exclusively by the regular faculty budget of Pathology.FundingOpen Access funding enabled and organized by Projekt DEAL.Author informationAuthor notesThese authors contributed equally: Bruno Märkl, Nic G. Reitsam.Authors and AffiliationsPathology, Medical Faculty Augsburg, University of Augsburg, Augsburg, GermanyBruno Märkl, Nic G.

下载参考文献致谢这项工作完全由病理学的常规教师预算资助。资金开放获取资金由Projekt交易启用和组织。作者信息作者注意到这些作者做出了同样的贡献：Bruno Märkl，Nic G.Reitsam。作者和附属机构奥格斯堡大学奥格斯堡医学院心理学，德国奥格斯堡Bruno Märkl，Nic G。

Reitsam, Przemyslaw Grochowski & Bianca GrosserBavarian Cancer Research Center (BZKF), Augsburg, GermanyBruno Märkl, Nic G. Reitsam, Przemyslaw Grochowski, Johanna Waidhauser & Bianca GrosserWERA Comprehensive Cancer Center, Augsburg, GermanyBruno Märkl, Nic G. Reitsam, Przemyslaw Grochowski, Johanna Waidhauser & Bianca GrosserHematology and Oncology, Medical Faculty Augsburg, University of Augsburg, Augsburg, GermanyJohanna WaidhauserAuthorsBruno MärklView author publicationsYou can also search for this author in.

Reitsam，Przemyslaw Grochowski&Bianca Grosservarian癌症研究中心（BZKF），奥格斯堡，GermanyBruno Märkl，Nic G.Reitsam，Przemyslaw Grochowski，Johanna Waidhauser&Bianca GrosserWERA综合癌症中心，奥格斯堡，GermanyBruno Märkl，Nic G.Reitsam，Przemyslaw Grochowski，Johanna Waidhauser&Bianca Grosser血液学和肿瘤学，奥格斯堡大学医学院，奥格斯堡ations您也可以在中搜索此作者。

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PubMed Google ScholarContributionsB.M., N.R., P.G., J.W., and B.G. conceptualized the study, drafted individual parts of the initial draft, reviewed, and revised the manuscript. B.M. carried out the visualization. All authors have read and agreed to the final version of the manuscript.

PubMed谷歌学术贡献b。M、，N.R.，P.G.，J.W。和B.G.将研究概念化，起草了初稿的各个部分，审查并修订了手稿。B、 M.进行了可视化。。

B.M. and N.R. contributed equally to this work.Corresponding authorCorrespondence to.

B、 M.和N.R.对这项工作做出了同样的贡献。相应的作者对。

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Reprints and permissionsAbout this articleCite this articleMärkl, B., Reitsam, N.G., Grochowski, P. et al. The SARIFA biomarker in the context of basic research of lipid-driven cancers.

转载和许可本文引用本文Märkl，B.，Reitsam，N.G.，Grochowski，P。等人在脂质驱动的癌症基础研究中的SARIFA生物标志物。

npj Precis. Onc. 8, 165 (2024). https://doi.org/10.1038/s41698-024-00662-2Download citationReceived: 27 February 2024Accepted: 19 July 2024Published: 31 July 2024DOI: https://doi.org/10.1038/s41698-024-00662-2Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard.

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