Circulating sex steroids coregulate adipose tissue immune cell populations in healthy men

Male hypogonadism results in changes in body composition characterized by increases in fat mass. Resident immune cells influence energy metabolism in adipose tissue and could promote increased adiposity through paracrine effects. We hypothesized that manipulation of circulating sex steroid levels in healthy men would alter adipose tissue immune cell populations. Subjects ( n = 44 men, 19–55 yr of age) received 4 wk of treatment with the gonadotropin-releasing hormone receptor antagonist acyline with daily administration of 1) placebo gel, 2) 1.25 g testosterone gel (1.62%), 3) 5 g testosterone gel, or 4) 5 g testosterone gel with an aromatase inhibitor. Subcutaneous adipose tissue biopsies were performed at baseline and end-of-treatment, and adipose tissue immune cells, gene expression, and intra-adipose estrogen levels were quantified. Change in serum total testosterone level correlated inversely with change in the number of CD3+ (β = −0.36, P = 0.04), CD4+ (β = −0.34, P = 0.04), and CD8+ (β = −0.33, P = 0.05) T cells within adipose tissue. Change in serum 17β-estradiol level correlated inversely with change in the number of adipose tissue macrophages (ATMs) (β = −0.34, P = 0.05). A negative association also was found between change in serum testosterone and change in CD11c+ ATMs (β = −0.41, P = 0.01). Overall, sex steroid deprivation was associated with increases in adipose tissue T cells and ATMs. No associations were found between changes in serum sex steroid levels and changes in adipose tissue gene expression. Circulating sex steroid levels may regulate adipose tissue immune cell populations. These exploratory findings highlight a possible novel mechanism that could contribute to increased metabolic risk in hypogonadal men.

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The endometrial immune environment of women with endometriosis

Human Reproduction Update ◽

10.1093/humupd/dmz018 ◽

2019 ◽

Vol 25 (5) ◽

pp. 565-592 ◽

Cited By ~ 21

Author(s):

Júlia Vallvé-Juanico ◽

Sahar Houshdaran ◽

Linda C Giudice

Keyword(s):

T Cells ◽

Immune System ◽

Natural Killer Cells ◽

Natural Killer ◽

Immune Cells ◽

Immune Cell ◽

Reproductive Age ◽

Cycle Phase ◽

Cell Populations ◽

Killer Cells

Abstract BACKGROUND Endometriosis, a common oestrogen-dependent inflammatory disorder in women of reproductive age, is characterized by endometrial-like tissue outside its normal location in the uterus, which causes pelvic scarring, pain and infertility. While its pathogenesis is poorly understood, the immune system (systemically and locally in endometrium, pelvic endometriotic lesions and peritoneal fluid) is believed to play a central role in its aetiology, pathophysiology and associated morbidities of pain, infertility and poor pregnancy outcomes. However, immune cell populations within the endometrium of women with the disease have had incomplete phenotyping, thereby limiting insight into their roles in this disorder. OBJECTIVE AND RATIONALE The objective herein was to determine reproducible and consistent findings regarding specific immune cell populations and their abundance, steroid hormone responsiveness, functionality, activation states, and markers, locally and systemically in women with and without endometriosis. SEARCH METHODS A comprehensive English language PubMed, Medline and Google Scholar search was conducted with key search terms that included endometriosis, inflammation, human eutopic/ectopic endometrium, immune cells, immune population, immune system, macrophages, dendritic cells (DC), natural killer cells, mast cells, eosinophils, neutrophils, B cells and T cells. OUTCOMES In women with endometriosis compared to those without endometriosis, some endometrial immune cells display similar cycle-phase variation, whereas macrophages (Mø), immature DC and regulatory T cells behave differently. A pro-inflammatory Mø1 phenotype versus anti-inflammatory Mø2 phenotype predominates and natural killer cells display abnormal activity in endometrium of women with the disease. Conflicting data largely derive from small studies, variably defined hormonal milieu and different experimental approaches and technologies. WIDER IMPLICATIONS Phenotyping immune cell subtypes is essential to determine the role of the endometrial immune niche in pregnancy and endometrial homeostasis normally and in women with poor reproductive history and can facilitate development of innovative diagnostics and therapeutics for associated symptoms and compromised reproductive outcomes.

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Integrative transcriptomic analysis of SLE reveals IFN-driven cross-talk between immune cells

10.1101/2020.04.27.065227 ◽

2020 ◽

Author(s):

Bharat Panwar ◽

Benjamin J. Schmiedel ◽

Shu Liang ◽

Brandie White ◽

Enrique Rodriguez ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

Autoimmune Disease ◽

Cross Talk ◽

Immune Cell ◽

Cell Types ◽

Cell Populations ◽

Multiple Cell ◽

Classical Monocytes ◽

Multiple Immune Cell

ABSTRACTThe systemic lupus erythematosus (SLE) is an incurable autoimmune disease disproportionately affecting women and may lead to damage in multiple different organs. The marked heterogeneity in its clinical manifestations is a major obstacle in finding targeted treatments and involvement of multiple immune cell types further increases this complexity. Thus, identifying molecular subtypes that best correlate with disease heterogeneity and severity as well as deducing molecular cross-talk among major immune cell types that lead to disease progression are critical steps in the development of more informed therapies for SLE. Here we profile and analyze gene expression of six major circulating immune cell types from patients with well-characterized SLE (classical monocytes (n=64), T cells (n=24), neutrophils (n=24), B cells (n=20), conventional (n=20) and plasmacytoid (n=22) dendritic cells) and from healthy control subjects. Our results show that the interferon (IFN) response signature was the major molecular feature that classified SLE patients into two distinct groups: IFN-signature negative (IFNneg) and positive (IFNpos). We show that the gene expression signature of IFN response was consistent (i) across all immune cell types, (ii) all single cells profiled from three IFNpos donors using single-cell RNA-seq, and (iii) longitudinal samples of the same patient. For a better understanding of molecular differences of IFNpos versus IFNneg patients, we combined differential gene expression analysis with differential Weighted Gene Co-expression Network Analysis (WGCNA), which revealed a relatively small list of genes from classical monocytes including two known immune modulators, one the target of an approved therapeutic for SLE (TNFSF13B/BAFF: belimumab) and one itself a therapeutic for Rheumatoid Arthritis (IL1RN: anakinra). For a more integrative understanding of the cross-talk among different cell types and to identify potentially novel gene or pathway connections, we also developed a novel gene co-expression analysis method for joint analysis of multiple cell types named integrated WGNCA (iWGCNA). This method revealed an interesting cross-talk between T and B cells highlighted by a significant enrichment in the expression of known markers of T follicular helper cells (Tfh), which also correlate with disease severity in the context of IFNpos patients. Interestingly, higher expression of BAFF from all myeloid cells also shows a strong correlation with enrichment in the expression of genes in T cells that may mark circulating Tfh cells or related memory cell populations. These cell types have been shown to promote B cell class-switching and antibody production, which are well-characterized in SLE patients. In summary, we generated a large-scale gene expression dataset from sorted immune cell populations and present a novel computational approach to analyze such data in an integrative fashion in the context of an autoimmune disease. Our results reveal the power of a hypothesis-free and data-driven approach to discover drug targets and reveal novel cross-talk among multiple immune cell types specific to a subset of SLE patients. This approach is immediately useful for studying autoimmune diseases and is applicable in other contexts where gene expression profiling is possible from multiple cell types within the same tissue compartment.

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Abstract P142: Sex-differences In M1-like Macrophage Counts In Aortic Perivascular Adipose Tissue Precedes High Fat Diet-induced Hypertension In Dahl S Rats

Hypertension ◽

10.1161/hyp.76.suppl_1.p142 ◽

2020 ◽

Vol 76 (Suppl_1) ◽

Author(s):

Ramya Kalyana Kumar ◽

Hannah Garver ◽

Erinn Liamon-Thompson ◽

Gregory D Fink ◽

Stephanie W Watts ◽

...

Keyword(s):

T Cells ◽

Sex Differences ◽

Adipose Tissue ◽

Immune Cells ◽

Immune Cell ◽

Memory T Cells ◽

High Fat ◽

Perivascular Adipose Tissue ◽

Induced Hypertension ◽

Hypertension Development

Perivascular adipose tissue (PVAT) may connect adiposity to hypertension because of its functions and proximity to blood vessels. Immune cells in adipose tissue are proposed to couple adiposity to hypertension development in a sex-specific fashion. It is unknown if sex-differences exist in PVAT’s immune community during the onset of adiposity-induced hypertension. Both sexes of the Dahl S rat strain become equally hypertensive (table) when fed a high fat (HFD) diet. We hypothesized that both sexes have similar immune cell composition in PVAT with the development and progression of HFD-induced hypertension. Male and female Dahl S rats were fed a regular (10% calories from fat; CD) diet or a HFD (60%) from weaning. Thoracic aorta PVAT (APVAT) was harvested at 10 (pre-hypertension), 17 (onset) or 24 (chronic) weeks (w) of diet. Macrophages (subtypes), neutrophils, mast, T (subtypes), B, NK cells were measured by flow cytometry. At 10 w, HFD females had 5X the number of M1-like macrophages vs HFD males. At 17 w, CD females had 10X the number of M2-like macrophages vs CD males. At 17 w and 24 w, males had greater number of CD4 (2X) and CD8 (1.5X) memory T cells vs females, independent of the diet (table). In summary, sex-differences in M1-like macrophage counts in APVAT precedes the development of HFD-induced hypertension in Dahl S rats. The progression of hypertension is associated with memory T cells in males and M2-like macrophages in females. This study is foundational to understand the sex-specific roles of these immune cells in regulating vascular tone in HFD-induced hypertension, underscoring the need for novel sex-specific anti-hypertensive immune modulators.

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A gene expression-based study on immune cell subtypes and glioma prognosis

BMC Cancer ◽

10.1186/s12885-019-6324-7 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 5

Author(s):

Qiu-Yue Zhong ◽

Er-Xi Fan ◽

Guang-Yong Feng ◽

Qi-Ying Chen ◽

Xiao-Xia Gou ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

Data Analysis ◽

Nk Cells ◽

Immune Cells ◽

Prognostic Value ◽

Immune Cell ◽

High Morbidity ◽

Gamma Delta T Cells ◽

Gamma Delta

Abstract Object Glioma is a common malignant tumours in the central nervous system (CNS), that exhibits high morbidity, a low cure rate, and a high recurrence rate. Currently, immune cells are increasingly known to play roles in the suppression of tumourigenesis, progression and tumour growth in many tumours. Therefore, given this increasing evidence, we explored the levels of some immune cell genes for predicting the prognosis of patients with glioma. Methods We extracted glioma data from The Cancer Genome Atlas (TCGA). Using the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm, the relative proportions of 22 types of infiltrating immune cells were determined. In addition, the relationships between the scales of some immune cells and sex/age were also calculated by a series of analyses. A P-value was derived for the deconvolution of each sample, providing credibility for the data analysis (P < 0.05). All analyses were conducted using R version 3.5.2. Five-year overall survival (OS) also showed the effectiveness and prognostic value of each proportion of immune cells in glioma; a bar plot, correlation-based heatmap (corheatmap), and heatmap were used to represent the proportions of immune cells in each glioma sample. Results In total, 703 transcriptomes from a clinical dataset of glioma patients were drawn from the TCGA database. The relative proportions of 22 types of infiltrating immune cells are presented in a bar plot and heatmap. In addition, we identified the levels of immune cells related to prognosis in patients with glioma. Activated dendritic cells (DCs), eosinophils, activated mast cells, monocytes and activated natural killer (NK) cells were positively related to prognosis in the patients with glioma; however, resting NK cells, CD8+ T cells, T follicular helper cells, gamma delta T cells and M0 macrophages were negatively related to prognosis in the patients with glioma. Specifically, the proportions of several immune cells were significantly related to patient age and sex. Furthermore, the level of M0 macrophages was significant in regard to interactions with other immune cells, including monocytes and gamma delta T cells, in glioma tissues through sample data analysis. Conclusion We performed a novel gene expression-based study of the levels of immune cell subtypes and prognosis in glioma, which has potential clinical prognostic value for patients with glioma.

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EPEN-23. A COMPUTATIONAL ANALYSIS OF THE TUMOUR IMMUNE MICROENVIRONMENT IN PAEDIATRIC EPENDYMOMA

Neuro-Oncology ◽

10.1093/neuonc/noaa222.160 ◽

2020 ◽

Vol 22 (Supplement_3) ◽

pp. iii312-iii312

Author(s):

Timothy Ritzmann ◽

Anbarasu Lourdusamy ◽

Andrew Jackson ◽

Lisa Storer ◽

Andrew Donson ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

T Cell ◽

B Cells ◽

Computational Analysis ◽

Immune Cell ◽

Cell Populations ◽

Immune Microenvironment ◽

Tumour Immunity ◽

Follicular Helper

Abstract Ependymoma is the third commonest childhood brain tumour. Relapse is frequent, often fatal and current therapeutic strategies are inadequate. Previous ependymoma research describes an immunosuppressive environment with T-cell exhaustion, indicating a lack of response to T-cell directed immunotherapy. Understanding the immune microenvironment is therefore critical. We present a computational analysis of ependymoma, gene expression derived, immune profiles. Using 465 ependymoma samples from gene expression datasets (GSE64415, GSE50385, GSE100240) and two RNA-seq databases from UK ependymomas, we applied bulk tumour deconvolution methods (CIBERSORT and xCell) to infer immune cell populations. Additionally, we measured checkpoint blockade related mRNAs and used immunohistochemistry to investigate cell populations in ependymoma sections. CIBERSORT indicated high proportions of M2-like macrophages and smaller proportions of activated natural killer (NK) cells, T follicular helper cells, CD4+ memory T-cells and B-cells. xCell overlapped with the M2-like macrophage and CD4+ memory T-cell signatures seen in CIBERSORT. On immunohistochemistry, T and B cells were scarce, with small numbers of CD8+, CD4+ and CD20+ cells in the parenchyma but greater numbers in surrounding regions. CD68 was more highly expressed in the parenchyma. Analysis of nine checkpoint ligands and receptors demonstrated only the TIM3/GAL9 combination was reliably detectable. GAL9 is implicated in tumour interactions with T-cells and macrophages elsewhere, possibly contributing to poorer outcomes. Our study supports the presence of myeloid cells being leading contributors to the ependymoma immune microenvironment. Further work will delineate the extent of myeloid contribution to immunosuppression across molecular subtypes. Modulation of tumour immunity may contribute to better clinical outcomes.

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Quantitative Assessment and Prognostic Associations of the Immune Landscape in Ovarian Clear Cell Carcinoma

Cancers ◽

10.3390/cancers13153854 ◽

2021 ◽

Vol 13 (15) ◽

pp. 3854

Author(s):

Saira Khalique ◽

Sarah Nash ◽

David Mansfield ◽

Julian Wampfler ◽

Ayoma Attygale ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

Spatial Distribution ◽

Cell Carcinoma ◽

Immune Cell ◽

Clear Cell ◽

Clear Cell Carcinoma ◽

Cell Populations ◽

Ovarian Clear Cell Carcinoma ◽

Risk Patients

Ovarian clear cell carcinoma (OCCC) is a rare subtype of epithelial ovarian cancer characterised by a high frequency of loss-of-function ARID1A mutations and a poor response to chemotherapy. Despite their generally low mutational burden, an intratumoural T cell response has been reported in a subset of OCCC, with ARID1A purported to be a biomarker for the response to the immune checkpoint blockade independent of micro-satellite instability (MSI). However, assessment of the different immune cell types and spatial distribution specifically within OCCC patients has not been described to date. Here, we characterised the immune landscape of OCCC by profiling a cohort of 33 microsatellite stable OCCCs at the genomic, gene expression and histological level using targeted sequencing, gene expression profiling using the NanoString targeted immune panel, and multiplex immunofluorescence to assess the spatial distribution and abundance of immune cell populations at the protein level. Analysis of these tumours and subsequent independent validation identified an immune-related gene expression signature associated with risk of recurrence of OCCC. Whilst histological quantification of tumour-infiltrating lymphocytes (TIL, Salgado scoring) showed no association with the risk of recurrence or ARID1A mutational status, the characterisation of TILs via multiplexed immunofluorescence identified spatial differences in immunosuppressive cell populations in OCCC. Tumour-associated macrophages (TAM) and regulatory T cells were excluded from the vicinity of tumour cells in low-risk patients, suggesting that high-risk patients have a more immunosuppressive microenvironment. We also found that TAMs and cytotoxic T cells were also excluded from the vicinity of tumour cells in ARID1A-mutated OCCCs compared to ARID1A wild-type tumours, suggesting that the exclusion of these immune effectors could determine the host response of ARID1A-mutant OCCCs to therapy. Overall, our study has provided new insights into the immune landscape and prognostic associations in OCCC and suggest that tailored immunotherapeutic approaches may be warranted for different subgroups of OCCC patients.

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The Immune Cell Landscape in Renal Allografts

Cell Transplantation ◽

10.1177/0963689721995458 ◽

2021 ◽

Vol 30 ◽

pp. 096368972199545

Author(s):

Jun Lu ◽

Yi Zhang ◽

Jingjing Sun ◽

Shulin Huang ◽

Weizhen Wu ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

T Cell ◽

Immune Cells ◽

Immune Cell ◽

Cell Infiltration ◽

M1 Macrophages ◽

Deconvolution Analysis ◽

Renal Allografts ◽

Antibody Mediated Rejection

Immune cell infiltration plays an important role in the pathophysiology of kidney grafts, but the composition of immune cells is ill-defined. Here, we aimed at evaluating the levels and composition of infiltrating immune cells in kidney grafts. We used CIBERSORT, an established algorithm, to estimate the proportions of 22 immune cell types based on gene expression profiles. We found that non-rejecting kidney grafts were characteristic with high rates of M2 macrophages and resting mast cells. The proportion of M1 macrophages and activated NK cells were increased in antibody-mediated rejection (ABMR). In T cell-mediated rejection (TCMR), a significant increase in CD8 T cell and γδT cell infiltration was observed. CD8 positive T cells were dramatically increased in mixed-ABMR/TCMR. Then, the function of ABMR and TCMR prognostic molecular biomarkers were identified. Finally, we described the gene expression of molecular markers for ABMR diagnosis was elevated and related to the ratio of monocytes and M1 macrophages in ABMR biopsies, while the expression of TCMR diagnosis markers was increased too and positively correlated with γδT cells and activated CD4 memory T cells in TCMR biopsies. Our data suggest that CIBERSORT’s deconvolution analysis of gene expression data provides valuable information on the composition of immune cells in renal allografts.

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Procancerous immune cells in primary tumor is associated with breast cancer recurrence.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.e13042 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. e13042-e13042

Author(s):

Takashi Takeshita ◽

Li Yan ◽

Kazuaki Takabe

Keyword(s):

Gene Expression ◽

T Cells ◽

Immune Cells ◽

Clinical Characteristics ◽

Immune Cell ◽

Cancer Recurrence ◽

Early Death ◽

Late Recurrence ◽

Gene Expression Signatures ◽

Or Gene

e13042 Background: Breast cancer (BC) recurrence is largely determined by cancer factors as well as host factors. It has been implicated that infiltrating immune cells play critical roles in long term survival. We hypothesize that immune cell infiltration profile rather than clinical characteristics or gene expression signatures of the primary tumors associate with the timing of cancer recurrence. Methods: 308 primary BCs in TCGA with cancer recurrence data was divided into; recurrence < 2 years (Early, n = 103), 2-5 years (Late, n = 20), and no recurrence > 5 years (Control, n = 185). 1410 primary BCs in METABRIC with BC specific death data was divided into; death < 10 years (Early Death, n = 499), death > 10 years (Late Death, n = 123), and survived > 10 years (Survivors, n = 788). Results: We found that Early tumors demonstrated more aggressive clinical characteristics such as larger tumor, more lymph node metastases, higher pathological grades, higher Stages, and negative estrogen and progesterone receptors, compared with Control tumors. On the other hand, no clinical characteristics of Late tumors were significantly different from Control tumors, which implicate that clinical characteristics cannot distinguish late recurrence from Control. Gene set enrichment analyses revealed that there was no significant gene sets that enriched with Early nor Late recurrence compared with Control, which implicate that gene expression signatures cannot distinguish recurrent tumor from Control. Utilizing CIBERSORT algorithm, we found that M1 was low and M2 was high macrophages in Early compared from Control. Further, anti-cancer lymphocytes, memory CD4 T cells and gamma delta T cells, were significantly lower, and pro-cancerous regulatory T cells were significantly higher in Early and Late compared from Control. In agreement, cytolytic activity score that assess immune cell killing were significantly lower in Early and Late compared from Control. Interestingly, only elevation of regulatory T cells was similar in METABRIC cohort when Early Death and Late Death were compared with Survivors. Conclusions: We found that not clinical characteristics or gene expression signatures, but pro-cancerous immune cells in primary BC associate with cancer recurrence and breast specific death.

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Gene expression markers of Tumor Infiltrating Leukocytes

10.1101/068940 ◽

2016 ◽

Cited By ~ 5

Author(s):

Patrick Danaher ◽

Sarah Warren ◽

Lucas Dennis ◽

Leonard D’Amico ◽

Andrew White ◽

...

Keyword(s):

Gene Expression ◽

Flow Cytometry ◽

Single Cell ◽

Immune Cells ◽

Immune Cell ◽

Expression Patterns ◽

Cell Populations ◽

Marker Genes ◽

Cell Type ◽

Single Cell Type

AbstractBackgroundAssays of the abundance of immune cell populations in the tumor microenvironment promise to inform immune oncology research and the choice of immunotherapy for individual patients. We propose to measure the intratumoral abundance of various immune cells populations with gene expression. In contrast to IHC and flow cytometry, gene expression assays yield high information content from a clinically practical workflow. Previous studies of gene expression in purified immune cells have reported hundreds of genes showing enrichment in a single cell type, but the utility of these genes in tumor samples is unknown. We describe a novel statistical method for using co-expression patterns in large tumor gene expression datasets to validate previously reported candidate cell type marker genes, and we use this method to winnow previously published gene lists down to a subset of high confidence marker genes.MethodsWe use co-expression patterns in 9986 samples from The Cancer Genome Atlas (TCGA) to validate previously reported cell type marker genes. We compare immune cell scores derived from these genes to measurements from flow cytometry and immunohistochemistry. We characterize the reproducibility of our cell scores in replicate runs of RNA extracted from FFPE tumor tissue.ResultsWe identify a list of 60 marker genes whose expression levels quantify 14 immune cell populations. Cell type scores calculated from these genes are concordant with flow cytometry and IHC readings, show high reproducibility in replicate RNA samples from FFPE tissue, and reveal an intricate picture of the immune infiltrate in TCGA. Most genes previously reported to be enriched in a single cell type have co-expression patterns inconsistent with cell type specificity.ConclusionsDue to their concise gene set, computational simplicity and utility in tumor samples, these cell type gene signatures may be useful in future discovery research and clinical trials to understand how tumors and therapeutic intervention shape the immune response.

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Elucidating the immune infiltration in acne and its comparison with rosacea by integrated bioinformatics analysis

PLoS ONE ◽

10.1371/journal.pone.0248650 ◽

2021 ◽

Vol 16 (3) ◽

pp. e0248650

Author(s):

Lu Yang ◽

Yan-Hong Shou ◽

Yong-Sheng Yang ◽

Jin-Hua Xu

Keyword(s):

Gene Expression ◽

T Cells ◽

Mast Cells ◽

Immune Cells ◽

Plasma Cells ◽

Immune Cell ◽

Healthy Individuals ◽

Lesional Skin ◽

Immune Infiltration ◽

Acne Rosacea

Background Acne vulgaris and rosacea are common inflammatory complications of the skin, both characterized by abnormal infiltration of immune cells. The two diseases can be differentiated based on characteristic profile of the immune cell infiltrates at the periphery of disease lesions. In addition, dysregulated infiltration of immune cells not only occur in the acne lesions but also in non-lesional areas of patients with the disease, thus characterizing the immune infiltration in these sites can further enhance our understanding on the pathogenesis of acne. Methods Five microarray data-sets (GSE108110, GSE53795, GSE65914, GSE14905 and GSE78097) were downloaded from Gene Expression Omnibus. After removing the batch effects and normalizing the data, we applied the CIBERSORT algorithm combined with signature matrix LM22, to describe 22 types of immune cells’ infiltration in acne less than 48 hour (H) old, in comparation with non-lesional skin of acne patients, healthy skin and rosacea (including erythematotelangiectatic rosacea, papulopustular rosacea and phymatous rosacea) and we compared gene expression of Th1 and Th17-related molecules in acne, rosacea and healthy control. Results Compared with the non-lesional skin of acne patients, healthy individuals and rosacea patients, there is a significant increase in infiltration of neutrophils, monocytes and activated mast cells around the acne lesions, less than 48 H after their development. Contrarily, few naive CD4+ T cells, plasma cells, memory B cells and resting mast cells infiltrate acne sites compared to the aforementioned groups of individuals. Moreover, the infiltration of Regulatory T cells (Tregs) in acne lesions is substantially lower, relative to non-lesional sites of acne patients and skin of healthy individuals. In addition, non-lesional sites of acne patients exhibit lower infiltration of activated memory CD4+ T cells, plasma cells, memory B cells, M0 macrophages, neutrophils, resting mast cells but higher infiltration of Tregs and resting dendritic cells relative to skin of healthy individuals. Intriguingly, we found that among the 3 rosacea subtypes, the immune infiltration profile of papulopustular rosacea is the closest to that of acne lesions. In addition, through gene expression analysis of acne, rosacea and skin tissues of healthy individuals, we found a higher infiltration of Th1 and Th17 cells in acne lesions, relative to non-lesional skin areas of acne patients. Conclusions Our study provides new insights into the inflammatory pathogenesis of acne, and the difference between acne and rosacea, which helps in differentiating the two diseases. Our findings also guide on appropriate target therapy of the immune cell infiltrates in the two disease conditions.

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