Immune cell pair ratio captured by imaging mass cytometry has superior predictive value for prognosis of non-small cell lung cancer than cell fraction and density

IF 20.1 1区 医学 Q1 ONCOLOGY Cancer Communications Pub Date : 2024-03-26 DOI:10.1002/cac2.12540
Jian-Rong Li, Chao Cheng
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Limited by technical issues, most studies focused on a few immune cell lineages or relied on inferred immune cell levels from computational deconvolution. To investigate the prognostic effects of all major immune cell types unbiasedly, more systematic high-quality immune cell profiling data with matched patient survival information are needed.</p><p>Recently, Sorin <i>et al.</i> [<span>8</span>] used imaging mass cytometry (IMC) to characterize the immunological landscape of 416 distinct lung adenocarcinoma (LUAD) samples at single-cell resolution. The IMC images provide the counts and spatial distribution of 16 cell types with high precision in each sample. These cell types include cancer and endothelial cells, along with 14 immune cell types, including CD163<sup>+</sup> and CD163<sup>−</sup> macrophages, CD8<sup>+</sup>, CD4<sup>+</sup>, regulatory, and other T cells, classical, non-classical, and intermediate monocytes, natural killer cells, dendritic cells, mast cells, neutrophils, and other immune cells. Additionally, the data provide patient survival and other clinical information. Using these data, we investigated the prognostic associations of the cell density (#cells/megapixel) and fractions of the 16 cell types as well as the fraction ratio between each pair of cell types (Supplementary Methods). Our results indicated that the relative abundance between cell types (fraction ratios) was more prognostic than cell fractions and densities.</p><p>We calculated the densities of the 16 cell types in each patient's IMC image and applied Cox regression analysis to examine their associations with progression-free survival (PFS) after adjusting for established clinical factors including age, sex, smoking status, and tumor stage. At the significance level of <i>P</i> &lt; 0.05, only the density of non-classical monocytes was found to have a significant association with worse prognosis (hazard ratio [HR] = 1.004, <i>P</i> = 0.040, Figure 1A). After multiple testing corrections, none of the cell types was significant (false discovery rate [FDR] &gt; 0.05). Similar results were obtained when cell fractions among all cells were used for prognostic association analysis (Figure 1B). In addition, we conducted prognostic analysis on 14 immune cell types, focusing on their proportions among immune cells (excluding cancer and endothelial cells), yielding similar results. It has been well-known that some cell types play more immune suppressive toles in the TME, while others are more stimulatory. We therefore investigated the prognostic effect of relative abundance between different cell types. For each pair of the 16 cell types we calculated the ratio of their cell fractions (equal to the ratio of cell densities). From these ratios, we identified 28 cell pairs significantly associated with PFS (<i>P</i> &lt; 0.05), adjusted for clinical factors (Figure 1C). After multiple testing corrections, 9 pairs remained significant (FDR &lt; 0.05). As an example, the non-classical monocyte/CD4<sup>+</sup> T cell ratio was associated with a significantly worse PFS (<i>P</i> &lt; 0.001). We conducted a multivariable Cox regression model incorporating the fractions of non-classical monocytes, CD4<sup>+</sup> T cells, their ratio, and various clinical factors. The result indicated that neither non-classical monocytes nor CD4<sup>+</sup> T cells was significant, but the non-classical monocyte/CD4<sup>+</sup> T cell ratio was significantly associated with a shorter PFS (Figure 1D). Similar results were obtained when overall survival (OS) was used: cell-cell ratios were more prognostic than cell fractions and densities (Figure 1E and Supplementary Figure S1). Further analysis revealed significant associations of T other/CD4<sup>+</sup> T cell and non-classical monocyte/CD4<sup>+</sup> T cell ratios with advanced stages or male patients and of the CD8<sup>+</sup> T cell/cancer cell ratio with smoking or patients under 75 years old (Supplementary Figure S2), highlighting these clinical factors' prognostic impact.</p><p>By connecting all significant cell-cell pairs, we established a prognostic cell-cell interaction network, providing an overview of key pairs. Figure 1F illustrates a significant association of LUAD progression with the ratios of both infiltrating non-classical monocytes and their precursor intermediate monocytes to both CD8<sup>+</sup> and CD4<sup>+</sup> T cells. Additionally, higher ratios of infiltrating non-classical monocytes, intermediate monocytes, CD163<sup>+</sup> macrophages, and other T cells to B cells, CD8<sup>+</sup> T cells, or CD4<sup>+</sup> T cells, were linked to poorer OS (Supplementary Figure S3). These results highlight the pivotal prognostic role of the ratio of non-classical or intermediate monocytes to CD4<sup>+</sup> or CD8<sup>+</sup> T cells in LUAD, consistent with previous studies showing that non-classical or intermediate monocytes suppressed the proliferation and immune responses of CD8<sup>+</sup> or CD4<sup>+</sup> T cells [<span>9, 10</span>].</p><p>To further consolidate our results, we performed down-sampling analyses 100 times, each time randomly selecting 80% of samples for prognostic analysis. For cell density and cell fraction, the numbers of cell types significantly associated with PFS (FDR &lt; 0.05) were only 0.01 and 0.02 on average, respectively (Supplementary Figure S4A). In contrast, an average of 9.37 significant cell-cell pairs was identified. Additionally, we down-sampled cells from all images by randomly selecting 80% of cells and recalculated cell fractions for prognostic analysis, repeated 100 times. On average, 9.74 significant cell-cell pairs were identified each time, while no significant associations were found using cell fraction and cell density (Supplementary Figure S4B). These findings suggest that the greater prognostic relevance of relative cell abundances over cell density/fraction was not merely due to a limited subset of patient samples or cells.</p><p>In conclusion, our study established that in LUAD, the prognostic value was more closely associated with the relative abundances between specific cell types within the TME than with the absolute cell densities or fractions depicted by IMC images. This finding underscores the prognostic significance of interactions between distinct immune cells in the TME, especially the immunological equilibrium between immunosuppressive and immunostimulatory cells. Such insights have significant implications for the development of targeted therapies and patient stratification in LUAD, based on the nuanced understanding of immune cell interactions.</p><p>Chao Cheng designed the study. Jian-Rong Li collected the dataset. Chao Cheng and Jian-Rong Li performed the analysis. Jian-Rong Li constructed the figures. Chao Cheng and Jian-Rong Li interpret results and wrote the manuscript. Chao Cheng supervised the project. All authors provided feedback, revisions, and input on the final manuscript.</p><p>The authors declare no competing financial interests.</p><p>This study is supported by the Cancer Prevention Research Institute of Texas (CPRIT) (RR180061 to CC) and the National Cancer Institute of the National Institute of Health (1R01CA269764 to CC). 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引用次数: 0

Abstract

Infiltrating immune cells in the tumor microenvironment (TME) play critical roles in the initiation, progression, and metastasis of cancer [1]. Previous studies have reported that the infiltration levels of various immune cell types are significantly associated with patient prognosis in different cancers [2, 3]. Specifically, in non-small cell lung cancer (NSCLC) the prognostic associations of major immune cell types have been investigated [4-6], however, some of the reported associations are inconsistent and remain debated [7]. Limited by technical issues, most studies focused on a few immune cell lineages or relied on inferred immune cell levels from computational deconvolution. To investigate the prognostic effects of all major immune cell types unbiasedly, more systematic high-quality immune cell profiling data with matched patient survival information are needed.

Recently, Sorin et al. [8] used imaging mass cytometry (IMC) to characterize the immunological landscape of 416 distinct lung adenocarcinoma (LUAD) samples at single-cell resolution. The IMC images provide the counts and spatial distribution of 16 cell types with high precision in each sample. These cell types include cancer and endothelial cells, along with 14 immune cell types, including CD163+ and CD163 macrophages, CD8+, CD4+, regulatory, and other T cells, classical, non-classical, and intermediate monocytes, natural killer cells, dendritic cells, mast cells, neutrophils, and other immune cells. Additionally, the data provide patient survival and other clinical information. Using these data, we investigated the prognostic associations of the cell density (#cells/megapixel) and fractions of the 16 cell types as well as the fraction ratio between each pair of cell types (Supplementary Methods). Our results indicated that the relative abundance between cell types (fraction ratios) was more prognostic than cell fractions and densities.

We calculated the densities of the 16 cell types in each patient's IMC image and applied Cox regression analysis to examine their associations with progression-free survival (PFS) after adjusting for established clinical factors including age, sex, smoking status, and tumor stage. At the significance level of P < 0.05, only the density of non-classical monocytes was found to have a significant association with worse prognosis (hazard ratio [HR] = 1.004, P = 0.040, Figure 1A). After multiple testing corrections, none of the cell types was significant (false discovery rate [FDR] > 0.05). Similar results were obtained when cell fractions among all cells were used for prognostic association analysis (Figure 1B). In addition, we conducted prognostic analysis on 14 immune cell types, focusing on their proportions among immune cells (excluding cancer and endothelial cells), yielding similar results. It has been well-known that some cell types play more immune suppressive toles in the TME, while others are more stimulatory. We therefore investigated the prognostic effect of relative abundance between different cell types. For each pair of the 16 cell types we calculated the ratio of their cell fractions (equal to the ratio of cell densities). From these ratios, we identified 28 cell pairs significantly associated with PFS (P < 0.05), adjusted for clinical factors (Figure 1C). After multiple testing corrections, 9 pairs remained significant (FDR < 0.05). As an example, the non-classical monocyte/CD4+ T cell ratio was associated with a significantly worse PFS (P < 0.001). We conducted a multivariable Cox regression model incorporating the fractions of non-classical monocytes, CD4+ T cells, their ratio, and various clinical factors. The result indicated that neither non-classical monocytes nor CD4+ T cells was significant, but the non-classical monocyte/CD4+ T cell ratio was significantly associated with a shorter PFS (Figure 1D). Similar results were obtained when overall survival (OS) was used: cell-cell ratios were more prognostic than cell fractions and densities (Figure 1E and Supplementary Figure S1). Further analysis revealed significant associations of T other/CD4+ T cell and non-classical monocyte/CD4+ T cell ratios with advanced stages or male patients and of the CD8+ T cell/cancer cell ratio with smoking or patients under 75 years old (Supplementary Figure S2), highlighting these clinical factors' prognostic impact.

By connecting all significant cell-cell pairs, we established a prognostic cell-cell interaction network, providing an overview of key pairs. Figure 1F illustrates a significant association of LUAD progression with the ratios of both infiltrating non-classical monocytes and their precursor intermediate monocytes to both CD8+ and CD4+ T cells. Additionally, higher ratios of infiltrating non-classical monocytes, intermediate monocytes, CD163+ macrophages, and other T cells to B cells, CD8+ T cells, or CD4+ T cells, were linked to poorer OS (Supplementary Figure S3). These results highlight the pivotal prognostic role of the ratio of non-classical or intermediate monocytes to CD4+ or CD8+ T cells in LUAD, consistent with previous studies showing that non-classical or intermediate monocytes suppressed the proliferation and immune responses of CD8+ or CD4+ T cells [9, 10].

To further consolidate our results, we performed down-sampling analyses 100 times, each time randomly selecting 80% of samples for prognostic analysis. For cell density and cell fraction, the numbers of cell types significantly associated with PFS (FDR < 0.05) were only 0.01 and 0.02 on average, respectively (Supplementary Figure S4A). In contrast, an average of 9.37 significant cell-cell pairs was identified. Additionally, we down-sampled cells from all images by randomly selecting 80% of cells and recalculated cell fractions for prognostic analysis, repeated 100 times. On average, 9.74 significant cell-cell pairs were identified each time, while no significant associations were found using cell fraction and cell density (Supplementary Figure S4B). These findings suggest that the greater prognostic relevance of relative cell abundances over cell density/fraction was not merely due to a limited subset of patient samples or cells.

In conclusion, our study established that in LUAD, the prognostic value was more closely associated with the relative abundances between specific cell types within the TME than with the absolute cell densities or fractions depicted by IMC images. This finding underscores the prognostic significance of interactions between distinct immune cells in the TME, especially the immunological equilibrium between immunosuppressive and immunostimulatory cells. Such insights have significant implications for the development of targeted therapies and patient stratification in LUAD, based on the nuanced understanding of immune cell interactions.

Chao Cheng designed the study. Jian-Rong Li collected the dataset. Chao Cheng and Jian-Rong Li performed the analysis. Jian-Rong Li constructed the figures. Chao Cheng and Jian-Rong Li interpret results and wrote the manuscript. Chao Cheng supervised the project. All authors provided feedback, revisions, and input on the final manuscript.

The authors declare no competing financial interests.

This study is supported by the Cancer Prevention Research Institute of Texas (CPRIT) (RR180061 to CC) and the National Cancer Institute of the National Institute of Health (1R01CA269764 to CC). CC is a CPRIT Scholar in Cancer Research.

Not applicable

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成像质控细胞仪捕获的免疫细胞对比率对非小细胞肺癌预后的预测价值优于细胞分数和密度。
这些结果凸显了非经典或中间单核细胞与CD4+或CD8+T细胞的比例在LUAD中的关键预后作用,这与之前的研究显示非经典或中间单核细胞抑制CD8+或CD4+T细胞的增殖和免疫反应[9, 10]是一致的。为了进一步巩固我们的结果,我们进行了100次向下取样分析,每次随机选择80%的样本进行预后分析。就细胞密度和细胞分数而言,与 PFS 显著相关的细胞类型数量(FDR &lt;0.05)平均分别只有 0.01 和 0.02(补充图 S4A)。相比之下,我们平均发现了 9.37 对重要的细胞-细胞对。此外,我们从所有图像中随机抽取了 80% 的细胞,并重新计算细胞分数进行预后分析,重复 100 次。平均每次发现 9.74 个重要的细胞对,而使用细胞分数和细胞密度则没有发现明显的关联(补充图 S4B)。总之,我们的研究证实,在 LUAD 中,预后价值与 TME 中特定细胞类型之间的相对丰度关系更密切,而不是 IMC 图像所显示的绝对细胞密度或细胞分数。这一发现强调了TME中不同免疫细胞之间相互作用的预后意义,尤其是免疫抑制细胞和免疫刺激细胞之间的免疫平衡。基于对免疫细胞相互作用的微妙理解,这些见解对开发靶向疗法和对LUAD患者进行分层具有重要意义。李建荣收集数据集。程超和李建荣进行了分析。李建荣绘制图表。程超和李建荣解释结果并撰写手稿。程超指导了该项目。本研究得到了德克萨斯州癌症预防研究所(CPRIT)(RR180061给CC)和美国国立卫生研究院国家癌症研究所(1R01CA269764给CC)的支持。CC 是 CPRIT 癌症研究学者。
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来源期刊
Cancer Communications
Cancer Communications Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
25.50
自引率
4.30%
发文量
153
审稿时长
4 weeks
期刊介绍: Cancer Communications is an open access, peer-reviewed online journal that encompasses basic, clinical, and translational cancer research. The journal welcomes submissions concerning clinical trials, epidemiology, molecular and cellular biology, and genetics.
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