Background

Platinum-based neoadjuvant chemotherapy (NAC) is standard for patients with muscle-invasive bladder cancer (MIBC). Pathologic response (complete: ypT0N0 and partial: <ypT2N0) to NAC is associated with improved survival with ypT0N0 achieved in 30–40% of cases. Strategies to increase response to NAC are needed. Incorporation of immune checkpoint inhibitors (ICIs) has demonstrated promise, and better spatial understanding of the tumor microenvironment may help predict NAC/ICI response.

Objective

Using the NanoString GeoMx platform, we performed proteomic digital spatial profiling (DSP) on transurethral resections of bladder tumors from 18 responders (<ypT2) and 18 nonresponders (≥ypT2) from two studies of NAC (gemcitabine and cisplatin) plus ICI (LCCC1520 [pembrolizumab] and BLASST-1 [nivolumab]).

Design, setting, and participants

Pretreatment tumor samples were stained by hematoxylin and eosin and immunofluorescence (panCK and CD45) to select four regions of interest (ROIs): tumor enriched (TE), immune enriched (IE), tumor/immune interface (tumor interface = TX and immune interface = IX).

Outcome measurements and statistical analysis

DSP was performed with 52 protein markers from immune cell profiling, immunotherapy drug target, immune activation status, immune cell typing, and pan-tumor panels.

Results and limitations

Protein marker expression patterns were analyzed to determine their association with pathologic response, incorporating or agnostic of their ROI designation (TE/IE/TX/IX). Overall, DSP-based marker expression showed high intratumoral heterogeneity; however, response was associated with markers including PD-L1 (ROI agnostic), Ki-67 (ROI agnostic, TE, IE, and TX), HLA-DR (TX), and HER2 (TE). An elastic net model of response with ROI-inclusive markers demonstrated better validation set performance (area under the curve [AUC] = 0.827) than an ROI-agnostic model (AUC = 0.432). A model including DSP, tumor mutational burden, and clinical data performed no better (AUC = 0.821) than the DSP-only model.

Conclusions

Despite high intratumoral heterogeneity of DSP-based marker expression, we observed associations between pathologic response and specific DSP-based markers in a spatially dependent context. Further exploration of tumor region–specific biomarkers may help predict response to neoadjuvant chemoimmunotherapy in MIBC.

Patient summary

In this study, we used the GeoMx platform to perform proteomic digital spatial profiling on transurethral resections of bladder tumors from 18 responders and 18 nonresponders from two studies of neoadjuvant chemotherapy (gemcitabine and cisplatin) plus immune checkpoint inhibitor therapy (LCCC1520 [pembrolizumab] and BLASST-1 [nivolumab]). We found that assessing protein marker expression in the context of tumor architecture improved response prediction.

中文翻译：

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肿瘤微环境中的空间关系表明与肌层浸润性膀胱癌新辅助化学免疫治疗的病理反应相关

背景

以铂类为基础的新辅助化疗 (NAC) 是肌层浸润性膀胱癌 (MIBC) 患者的标准治疗。NAC 的病理反应（完全：ypT0N0 和部分：<ypT2N0）与 30-40% 病例中达到 ypT0N0 的生存率改善相关。需要制定加强 NAC 响应的策略。免疫检查点抑制剂 (ICIs) 的结合已被证明是有希望的，对肿瘤微环境更好的空间理解可能有助于预测 NAC/ICI 反应。

客观的

使用 NanoString GeoMx 平台，我们对来自两项 NAC（吉西他滨和顺铂）加 ICI（LCCC1520）研究的 18 名有反应者（<ypT2）和 18 名无反应者（≥ypT2）经尿道切除膀胱肿瘤进行了蛋白质组数字空间分析 (DSP)。派姆单抗]和 BLASST-1 [纳武单抗]）。

设计、设置和参与者

预处理的肿瘤样本通过苏木精和伊红以及免疫荧光（panCK和CD45）染色，选择四个感兴趣区域（ROI）：肿瘤富集（TE）、免疫富集（IE）、肿瘤/免疫界面（肿瘤界面= TX和免疫界面） = 九）。

结果测量和统计分析

使用来自免疫细胞分析、免疫治疗药物靶点、免疫激活状态、免疫细胞分型和泛肿瘤组的 52 个蛋白质标记物进行 DSP。

结果和局限性

分析蛋白质标志物表达模式以确定它们与病理反应的关联，纳入或不考虑其 ROI 名称 (TE/IE/TX/IX)。总体而言，基于 DSP 的标记表达表现出高度的瘤内异质性；然而，反应与标志物相关，包括 PD-L1（ROI 不可知）、Ki-67（ROI 不可知、TE、IE 和 TX）、HLA-DR (TX) 和 HER2 (TE)。包含 ROI 标记的弹性响应网络模型表现出比 ROI 不可知模型 (AUC = 0.432) 更好的验证集性能（曲线下面积 [AUC] = 0.827）。包含 DSP、肿瘤突变负荷和临床数据的模型的表现并不比仅包含 DSP 的模型更好（AUC = 0.821）。

结论

尽管基于 DSP 的标记物表达具有高度肿瘤内异质性，但我们在空间依赖性背景下观察到病理反应与特定的基于 DSP 的标记物之间的关联。进一步探索肿瘤区域特异性生物标志物可能有助于预测 MIBC 对新辅助化学免疫治疗的反应。

患者总结

在本研究中，我们使用 GeoMx 平台对新辅助化疗（吉西他滨和顺铂）加免疫检查点抑制剂治疗（LCCC1520 [pembrolizumab] 和 BLASST）两项研究中的 18 名有反应者和 18 名无反应者进行膀胱肿瘤经尿道切除术进行蛋白质组数字空间分析。 -1 [纳武利尤单抗]）。我们发现，在肿瘤结构的背景下评估蛋白质标记物的表达可以改善反应预测。