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Spatial organization of dendritic cells within tumor draining lymph nodes impacts clinical outcome in breast cancer patients.

Chang AY, Bhattacharya N, Mu J, Setiadi AF, Carcamo-Cavazos V, Lee GH, Simons DL, Yadegarynia S, Hemati K, Kapelner A, Ming Z, Krag DN, Schwartz EJ, Chen DZ, Lee PP - J Transl Med (2013)

Bottom Line: Degree of clustering of DCs (in terms of spatial proximity of the cells to each other) was reduced in TDLNs compared to HLNs.The average number of T cells within a standardized radius of a clustered DC was increased compared to that of an unclustered DC, suggesting that DC clustering was associated with T cell interaction.Furthermore, the number of T cells within the radius of a clustered DC was reduced in tumor-positive TDLNs compared to HLNs.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Medicine, Stanford University, 269 Campus Drive, 94305 Stanford, CA, USA. plee@coh.org.

ABSTRACT

Background: Dendritic cells (DCs) are important mediators of anti-tumor immune responses. We hypothesized that an in-depth analysis of dendritic cells and their spatial relationships to each other as well as to other immune cells within tumor draining lymph nodes (TDLNs) could provide a better understanding of immune function and dysregulation in cancer.

Methods: We analyzed immune cells within TDLNs from 59 breast cancer patients with at least 5 years of clinical follow-up using immunohistochemical staining with a novel quantitative image analysis system. We developed algorithms to analyze spatial distribution patterns of immune cells in cancer versus healthy intra-mammary lymph nodes (HLNs) to derive information about possible mechanisms underlying immune-dysregulation in breast cancer. We used the non-parametric Mann-Whitney test for inter-group comparisons, Wilcoxon Matched-Pairs Signed Ranks test for intra-group comparisons and log-rank (Mantel-Cox) test for Kaplan Maier analyses.

Results: Degree of clustering of DCs (in terms of spatial proximity of the cells to each other) was reduced in TDLNs compared to HLNs. While there were more numerous DC clusters in TDLNs compared to HLNs,DC clusters within TDLNs tended to have fewer member DCs and also consisted of fewer cells displaying the DC maturity marker CD83. The average number of T cells within a standardized radius of a clustered DC was increased compared to that of an unclustered DC, suggesting that DC clustering was associated with T cell interaction. Furthermore, the number of T cells within the radius of a clustered DC was reduced in tumor-positive TDLNs compared to HLNs. Importantly, clinical outcome analysis revealed that DC clustering in tumor-positive TDLNs correlated with the duration of disease-free survival in breast cancer patients.

Conclusions: These findings are the first to describe the spatial organization of DCs within TDLNs and their association with survival outcome. In addition, we characterized specific changes in number, size, maturity, and T cell co-localization of such clusters. Strategies to enhance DC function in-vivo, including maturation and clustering, may provide additional tools for developing more efficacious DC cancer vaccines.

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DC clustering and maturation in NSLN+ nodes correlate with duration of disease-free survival. Using the median value of (A) percentage mature DCs or (B) percentage clustered DCs per node as cutoff, patients having NSLN+ nodes (n=19) were divided into two groups (using exclusion criteria mentioned in the Methods section) with those above the median defined by the solid line and those below the median by the dotted line. Kaplan-Meier curves were plotted showing the difference in duration of disease free survival between the two groups. (C) (i) Linear regression analysis between %clustered DCs and %mature DCs in NSLN+ nodes (n=19) (ii) Percentage mature DCs were calculated among clustered as well as unclustered DCs in NSLN+ nodes (n=19) ns denotes p>0.05.
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Figure 6: DC clustering and maturation in NSLN+ nodes correlate with duration of disease-free survival. Using the median value of (A) percentage mature DCs or (B) percentage clustered DCs per node as cutoff, patients having NSLN+ nodes (n=19) were divided into two groups (using exclusion criteria mentioned in the Methods section) with those above the median defined by the solid line and those below the median by the dotted line. Kaplan-Meier curves were plotted showing the difference in duration of disease free survival between the two groups. (C) (i) Linear regression analysis between %clustered DCs and %mature DCs in NSLN+ nodes (n=19) (ii) Percentage mature DCs were calculated among clustered as well as unclustered DCs in NSLN+ nodes (n=19) ns denotes p>0.05.

Mentions: To determine if alterations in DC organization within TDLNs were associated with clinical outcome, survival analyses were performed to examine the relationships between DC parameters and patient disease-free remission. Using the median value of percent mature DCs per node to divide the patients into low (below median) and high (above median) groups, we found that the high group had a statistically significantly longer (p<0.028) duration of survival compared to the low group (Figure 6A). This difference was not observed to be statistically significant in NSLN- nodes. Similarly, we then grouped the patients into low (below median) and high (above median) groups based on the percentage of clustered DCs of all DCs in each node. There was a statistically significant (p=0.034) disease-free survival difference between the two groups (Figure 6B). DC clustering and maturation in NSLN+ nodes both correlated with duration of disease-free survival in our breast cancer patient population. To determine if clinical characteristics or medical treatment provided to groups above and below the median could account for the survival difference, we examined hormone receptor status, Her2/Neu expression, radiation therapy, and chemotherapy regimens of these cohorts. No significant differences were observed between either of the two comparison groups for those variables (Additional file 2, Additional file 3). Importantly, DC clustering was found to be independent of DC maturity status in the NSLN+ group (R2=0.04, p=0.416, Figure 6Ci). Furthermore, the percentage of mature DCs did not differ significantly between unclustered and clustered DC populations (p=0.425, Figure 6Cii). Therefore, DC clustering is not merely a function of maturation or vice versa.


Spatial organization of dendritic cells within tumor draining lymph nodes impacts clinical outcome in breast cancer patients.

Chang AY, Bhattacharya N, Mu J, Setiadi AF, Carcamo-Cavazos V, Lee GH, Simons DL, Yadegarynia S, Hemati K, Kapelner A, Ming Z, Krag DN, Schwartz EJ, Chen DZ, Lee PP - J Transl Med (2013)

DC clustering and maturation in NSLN+ nodes correlate with duration of disease-free survival. Using the median value of (A) percentage mature DCs or (B) percentage clustered DCs per node as cutoff, patients having NSLN+ nodes (n=19) were divided into two groups (using exclusion criteria mentioned in the Methods section) with those above the median defined by the solid line and those below the median by the dotted line. Kaplan-Meier curves were plotted showing the difference in duration of disease free survival between the two groups. (C) (i) Linear regression analysis between %clustered DCs and %mature DCs in NSLN+ nodes (n=19) (ii) Percentage mature DCs were calculated among clustered as well as unclustered DCs in NSLN+ nodes (n=19) ns denotes p>0.05.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3852260&req=5

Figure 6: DC clustering and maturation in NSLN+ nodes correlate with duration of disease-free survival. Using the median value of (A) percentage mature DCs or (B) percentage clustered DCs per node as cutoff, patients having NSLN+ nodes (n=19) were divided into two groups (using exclusion criteria mentioned in the Methods section) with those above the median defined by the solid line and those below the median by the dotted line. Kaplan-Meier curves were plotted showing the difference in duration of disease free survival between the two groups. (C) (i) Linear regression analysis between %clustered DCs and %mature DCs in NSLN+ nodes (n=19) (ii) Percentage mature DCs were calculated among clustered as well as unclustered DCs in NSLN+ nodes (n=19) ns denotes p>0.05.
Mentions: To determine if alterations in DC organization within TDLNs were associated with clinical outcome, survival analyses were performed to examine the relationships between DC parameters and patient disease-free remission. Using the median value of percent mature DCs per node to divide the patients into low (below median) and high (above median) groups, we found that the high group had a statistically significantly longer (p<0.028) duration of survival compared to the low group (Figure 6A). This difference was not observed to be statistically significant in NSLN- nodes. Similarly, we then grouped the patients into low (below median) and high (above median) groups based on the percentage of clustered DCs of all DCs in each node. There was a statistically significant (p=0.034) disease-free survival difference between the two groups (Figure 6B). DC clustering and maturation in NSLN+ nodes both correlated with duration of disease-free survival in our breast cancer patient population. To determine if clinical characteristics or medical treatment provided to groups above and below the median could account for the survival difference, we examined hormone receptor status, Her2/Neu expression, radiation therapy, and chemotherapy regimens of these cohorts. No significant differences were observed between either of the two comparison groups for those variables (Additional file 2, Additional file 3). Importantly, DC clustering was found to be independent of DC maturity status in the NSLN+ group (R2=0.04, p=0.416, Figure 6Ci). Furthermore, the percentage of mature DCs did not differ significantly between unclustered and clustered DC populations (p=0.425, Figure 6Cii). Therefore, DC clustering is not merely a function of maturation or vice versa.

Bottom Line: Degree of clustering of DCs (in terms of spatial proximity of the cells to each other) was reduced in TDLNs compared to HLNs.The average number of T cells within a standardized radius of a clustered DC was increased compared to that of an unclustered DC, suggesting that DC clustering was associated with T cell interaction.Furthermore, the number of T cells within the radius of a clustered DC was reduced in tumor-positive TDLNs compared to HLNs.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Medicine, Stanford University, 269 Campus Drive, 94305 Stanford, CA, USA. plee@coh.org.

ABSTRACT

Background: Dendritic cells (DCs) are important mediators of anti-tumor immune responses. We hypothesized that an in-depth analysis of dendritic cells and their spatial relationships to each other as well as to other immune cells within tumor draining lymph nodes (TDLNs) could provide a better understanding of immune function and dysregulation in cancer.

Methods: We analyzed immune cells within TDLNs from 59 breast cancer patients with at least 5 years of clinical follow-up using immunohistochemical staining with a novel quantitative image analysis system. We developed algorithms to analyze spatial distribution patterns of immune cells in cancer versus healthy intra-mammary lymph nodes (HLNs) to derive information about possible mechanisms underlying immune-dysregulation in breast cancer. We used the non-parametric Mann-Whitney test for inter-group comparisons, Wilcoxon Matched-Pairs Signed Ranks test for intra-group comparisons and log-rank (Mantel-Cox) test for Kaplan Maier analyses.

Results: Degree of clustering of DCs (in terms of spatial proximity of the cells to each other) was reduced in TDLNs compared to HLNs. While there were more numerous DC clusters in TDLNs compared to HLNs,DC clusters within TDLNs tended to have fewer member DCs and also consisted of fewer cells displaying the DC maturity marker CD83. The average number of T cells within a standardized radius of a clustered DC was increased compared to that of an unclustered DC, suggesting that DC clustering was associated with T cell interaction. Furthermore, the number of T cells within the radius of a clustered DC was reduced in tumor-positive TDLNs compared to HLNs. Importantly, clinical outcome analysis revealed that DC clustering in tumor-positive TDLNs correlated with the duration of disease-free survival in breast cancer patients.

Conclusions: These findings are the first to describe the spatial organization of DCs within TDLNs and their association with survival outcome. In addition, we characterized specific changes in number, size, maturity, and T cell co-localization of such clusters. Strategies to enhance DC function in-vivo, including maturation and clustering, may provide additional tools for developing more efficacious DC cancer vaccines.

Show MeSH
Related in: MedlinePlus