Aggressive breast cancer in western Kenya has early onset, high proliferation, and immune cell infiltration

Abstract

Background: Breast cancer incidence and mortality vary significantly among different nations and racial groups. African nations have the highest breast cancer mortality rates in the world, even though the incidence rates are below those of many nations. Differences in disease progression suggest that aggressive breast tumors may harbor a unique molecular signature to promote disease progression. However, few studies have investigated the pathology and clinical markers expressed in breast tissue from regional African patient populations.

Methods: We collected 68 malignant and 89 non-cancerous samples from Kenyan breast tissue. To characterize the tumors from these patients, we constructed tissue microarrays (TMAs) from these tissues. Sections from these TMAs were stained and analyzed using immunohistochemistry to detect clinical breast cancer markers, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 receptor (HER2) status, Ki67, and immune cell markers.

Results: Thirty-three percent of the tumors were triple negative (ER-, PR-, HER2-), 59% were ER+, and almost all tumors analyzed were HER2-. Seven percent of the breast cancer patients were male, and 30% were <40 years old at diagnosis. Cancer tissue had increased immune cell infiltration with recruitment of CD163+ (M2 macrophage), CD25+ (regulatory T lymphocyte), and CD4+ (T helper) cells compared to non-cancer tissue.

Conclusions: We identified clinical biomarkers that may assist in identifying therapy strategies for breast cancer patients in western Kenya. Estrogen receptor status in particular should lead initial treatment strategies in these breast cancer patients. Increased CD25 expression suggests a need for additional treatment strategies designed to overcome immune suppression by CD25+ cells in order to promote the antitumor activity of CD8+ cytotoxic T cells.

Keywords: Breast cancer; CD163; CD25; Estrogen receptor; Kenya.

Fig. 1

Pathology of Kenyan breast cancer tissue samples. a Experimental design flowchart for this study. Samples were collected, analyzed for pathology, processed to create a tissue microarray, stained for clinical marker immunohistochemistry, and quantified by statistical analysis. b Pie chart representations of the distribution of cancer (left) and benign/not cancer (right) pathologies in Kenyan breast tissues analyzed after H&E staining. Most of these patients were diagnosed with invasive ductal carcinoma (IDC) and mucinous IDC. Most benign samples fell into the category that includes benign mammary, inflammatory tissue, and fibrocystic disease. (C) H&E staining of representative Kenyan breast cancer samples analyzed for pathology. Both Patient 1 and Patient 2 have invasive ductal carcinoma (IDC). Patient 2 has significant immune cell infiltration

Fig. 2

Heterogeneous expression of ER, PR, and HER2 receptors and increased proliferation. a Representative tissue samples from cancer and not cancer tissues that were stained for HER2, ER, and PR receptor expression. Examples of tissue that stained positively and negatively for the receptors are included. b Representative cancer and not cancer samples stained for the Ki67 proliferation marker. c Data plot analysis of Ki67 positive cells in ER+ vs. ER- tissue samples. Ki67 staining is significantly different between tissues from not cancer, ER+, and ER- breast samples (P < 0.0001, ANOVA) in ER- tissue samples, indicating high grade and an increase in cellular proliferation. The following combinations were significantly different by one-sided t-test: P = 2.834e-05 (ER+ vs. not cancer), 4.576e-06 (ER- vs. not cancer), and P = 0.0009 (ER- vs. ER+). The bar represents the median of all samples in the indicated cohort and includes any unstained samples

Fig. 3

Kenyan breast cancer tissue samples have increased macrophage infiltration in primary breast tumors. a Data plot analysis of IHC analysis for the macrophage lineage utilizing a CD68 antibody. Quantitative analysis of the staining indicates a significant increase in percent of CD68+ stained area (P < 0.0001; Mann-Whitney). b Data plot of IHC analysis for the M2 macrophage lineage utilizing a CD163 antibody. Quantitative analysis of the IHC staining revealed a significant increase in percent of CD163 stained area (P ≤ 0.0001; Mann-Whitney) in M2 macrophages in cancerous Kenyan breast tissues versus noncancerous Kenyan breast tissues. c Immunohistochemistry of representative noncancer and cancer samples for both general macrophage lineage (CD68) and the M2 macrophage lineage (CD163). Because the graphs are a log scale, any samples with unstained sections (i.e., zero) are not included in the graph. The bar represents the median of all samples in the indicated cohort and includes any unstained samples

Fig. 4

Distribution of CD4+, CD8+, and CD20+ cells in Kenyan breast cancer tissue samples. a Data analysis comparing the not cancer and cancer samples stained for T helper cell presence using a CD4 antibody. Significant increase was seen in T helper cell infiltration in the cancer samples shown by a higher percentage of CD4+ stained cell area (P = 0.03; Mann-Whitney). b Data analysis comparing noncancerous and cancerous samples stained for CD8+ cytotoxic T cells. No significant difference was seen in cytotoxic T cell infiltration in the cancerous samples, as shown by percentage of positively stained cell area (n.s.; Mann-Whitney). c Data analysis comparing the noncancerous to the cancerous samples stained for CD20+ B cells. No significant difference was seen in CD20+ cell infiltration in the cancerous samples, as shown by percentage of CD20+ stained cell area (n.s.; Mann-Whitney). d Immunohistochemistry of CD4, CD8, and CD20 in representative cancer and not cancer tissue samples.Because the graphs are log scale, any samples with unstained sections (i.e., zero) are not included in the graph. The bar represents the median of all samples in the indicated cohort and includes any unstained samples

Fig. 5

Increased infiltration of regulatory T cells in Kenyan breast cancer tissue. a Data analysis comparing the noncancerous and cancerous samples stained for CD25+ regulatory T cells. A significant increase was seen in regulatory T cell infiltration in the cancer samples, as shown by a higher percentage of positively stained cells (P = 0.03; Mann-Whitney), increased number of positively stained cells per area (P = 0.01; Mann-Whitney), and a higher percentage of CD25 stain per area (P = 0.0001; Mann-Whitney). Because the graph is a log scale, any samples with unstained sections (i.e., zero) are not included in the graph. The bar represents the median of all samples in the indicated cohort and includes any unstained samples. b Representative cancer and not cancer tissue samples stained for CD25. c Proposed T cell mechanism of action in Kenyan breast cancer model. (Top) Without a strong presence of regulatory T cells (e.g., benign Kenyan tissue), cytotoxic and T helper cells are able to combat and suppress the cancer cell, leading to increased apoptosis and loss of proliferation. (Bottom) When T regulatory cells are present (e.g., Kenyan breast cancer tissue), they block cytotoxic and helper T cells from fighting off the cancer cells