| Title |
Double-negative (CD27−IgD−) B cells are expanded in NSCLC and inversely correlate with affinity-matured B cell populations
|
|---|---|
| Published in |
Journal of Translational Medicine, February 2018
|
| DOI | 10.1186/s12967-018-1404-z |
| Pubmed ID | |
| Authors |
Sara M. Centuori, Cecil J. Gomes, Samuel S. Kim, Charles W. Putnam, Brandon T. Larsen, Linda L. Garland, David W. Mount, Jesse D. Martinez |
| Abstract |
The presence of B cells in early stage non-small cell lung cancer (NSCLC) is associated with longer survival, however, the role these cells play in the generation and maintenance of anti-tumor immunity is unclear. B cells differentiate into a variety of subsets with differing characteristics and functions. To date, there is limited information on the specific B cell subsets found within NSCLC. To better understand the composition of the B cell populations found in NSCLC we have begun characterizing B cells in lung tumors and have detected a population of B cells that are CD79A+CD27-IgD-. These CD27-IgD-(double-negative) B cells have previously been characterized as unconventional memory B cells and have been detected in some autoimmune diseases and in the elderly population but have not been detected previously in tumor tissue. A total of 15 fresh untreated NSCLC tumors and 15 matched adjacent lung control tissues were dissociated and analyzed by intracellular flow cytometry to detect the B cell-related markers CD79A, CD27 and IgD. All CD79A+B cells subsets were classified as either naïve (CD27-IgD+), affinity-matured (CD27+IgD-), early memory/germinal center cells (CD27+IgD+) or double-negative B cells (CD27-IgD-). Association of double-negative B cells with clinical data including gender, age, smoking status, tumor diagnosis and pathologic differentiation status were also examined using the logistic regression analysis for age and student's t-test for all other variables. Associations with other B cell subpopulations were examined using Spearman's rank correlation. We observed that double-negative B cells were frequently abundant in lung tumors compared to normal adjacent controls (13 out of 15 cases), and in some cases made up a substantial proportion of the total B cell compartment. The presence of double-negative cells was also found to be inversely related to the presence of affinity-matured B cells within the tumor, Spearman's coefficient of - 0.76. This study is the first to observe the presence of CD27-IgD-double-negative B cells in human NSCLC and that this population is inversely correlated with traditional affinity-matured B cell populations. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 63 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 17% |
| Student > Ph. D. Student | 10 | 16% |
| Student > Bachelor | 7 | 11% |
| Student > Master | 5 | 8% |
| Student > Doctoral Student | 3 | 5% |
| Other | 6 | 10% |
| Unknown | 21 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Immunology and Microbiology | 13 | 21% |
| Biochemistry, Genetics and Molecular Biology | 11 | 17% |
| Medicine and Dentistry | 4 | 6% |
| Agricultural and Biological Sciences | 4 | 6% |
| Social Sciences | 2 | 3% |
| Other | 5 | 8% |
| Unknown | 24 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 February 2018.
All research outputs
#15,492,327
of 23,023,224 outputs
Outputs from Journal of Translational Medicine
#2,259
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Outputs of similar age
#291,593
of 474,288 outputs
Outputs of similar age from Journal of Translational Medicine
#48
of 82 outputs
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