Lou Emil, Clemente Valentino, Grube Marcel, Svedbom Axel, Nelson Andrew, Blome Freya, Staebler Annette, Kommoss Stefan, Bazzaro Martina
bioRxiv. 2023 Jun 29:2023.06.27.546712. doi: 10.1101/2023.06.27.546712.
The tumor stroma is composed of a complex network of non-cancerous cells and extracellular matrix elements that collectively are crucial for cancer progression and treatment response. Within the realm of ovarian cancer, the expression of the stromal gene cluster has been linked to poorer progression-free and overall survival rates. However, in the age of precision medicine and genome sequencing, the notion that the simple measurement of tumor-stroma proportion alone can serve as a biomarker for clinical outcome is a topic that continues to generate controversy and provoke discussion. Our current study reveals that it is the quantity of stroma, rather than its quality, that serves as a clinically significant indicator of patient outcome in ovarian cancer.
This study leveraged the High-Grade-Serous-Carcinoma (HGSC) cohort of the publicly accessible Cancer Genome Atlas Program (TCGA) along with an independent cohort comprising HGSC clinical specimens in diagnostic and Tissue Microarray formats. Our objective was to investigate the correlation between the Tumor-Stroma-Proportion (TSP) and progression-free survival (PFS), overall survival (OS), and response to chemotherapy. We assessed these associations using H&E-stained slides and tissue microarrays. Our analysis employed semi-parametric models that accounted for age, metastases, and residual disease as controlling factors.
We found that high TSP (>50% stroma) was associated with significantly shorter progression-free survival (PFS) (p=0.016) and overall survival (OS) (p=0.006). Tumors from patients with chemoresistant tumors were twice as likely to have high TSP as compared to tumors from chemosensitive patients (p=0.012). In tissue microarrays, high TSP was again associated with significantly shorter PFS (p=0.044) and OS (p=0.0001), further confirming our findings. The Area Under the ROC curve for the model predicting platinum was estimated at 0.7644.
In HGSC, TSP was a consistent and reproducible marker of clinical outcome measures, including PFS, OS, and platinum chemoresistance. Assessment of TSP as a predictive biomarker that can be easily implemented and integrated into prospective clinical trial design and adapted to identify, at time of initial diagnosis, patients who are least likely to benefit long-term from conventional platinum-based cytotoxic chemotherapy treatment.
肿瘤基质由非癌细胞和细胞外基质成分组成的复杂网络构成,这些成分共同对癌症进展和治疗反应至关重要。在卵巢癌领域,基质基因簇的表达与无进展生存期和总生存率较差有关。然而,在精准医学和基因组测序时代,仅简单测量肿瘤-基质比例就能作为临床结局生物标志物的观点仍是一个不断引发争议和讨论的话题。我们目前的研究表明,在卵巢癌中,是基质的数量而非质量作为患者结局的临床重要指标。
本研究利用了公开可用的癌症基因组图谱计划(TCGA)的高级别浆液性癌(HGSC)队列以及一个独立队列,该独立队列包含诊断和组织微阵列形式的HGSC临床标本。我们的目的是研究肿瘤-基质比例(TSP)与无进展生存期(PFS)、总生存期(OS)以及化疗反应之间的相关性。我们使用苏木精和伊红(H&E)染色切片和组织微阵列评估这些关联。我们的分析采用了半参数模型,将年龄、转移和残留疾病作为控制因素。
我们发现高TSP(基质>50%)与显著更短的无进展生存期(PFS)(p=0.016)和总生存期(OS)(p=0.006)相关。与化疗敏感患者的肿瘤相比,化疗耐药患者的肿瘤出现高TSP的可能性高出两倍(p=0.012)。在组织微阵列中,高TSP再次与显著更短的PFS(p=0.044)和OS(p=0.0001)相关,进一步证实了我们的发现。预测铂类药物疗效的模型的ROC曲线下面积估计为0.7644。
在HGSC中,TSP是临床结局指标(包括PFS、OS和铂类化疗耐药)的一个一致且可重复的标志物。将TSP评估为一种可轻松实施并整合到前瞻性临床试验设计中的预测生物标志物,适用于在初次诊断时识别那些最不可能从传统铂类细胞毒性化疗中获得长期益处的患者。