scholarly journals Explainable Artificial Intelligence Reveals Novel Insight into Tumor Microenvironment Conditions Linked with Better Prognosis in Patients with Breast Cancer

Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3450
Author(s):  
Debaditya Chakraborty ◽  
Cristina Ivan ◽  
Paola Amero ◽  
Maliha Khan ◽  
Cristian Rodriguez-Aguayo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
T Cells ◽  
Tumor Microenvironment ◽  
Cancer Patients ◽  
Immune Cell ◽  
Survival Rates ◽  
Breast Cancer Patients ◽  
Inflection Points ◽  
Explainable Artificial Intelligence

We investigated the data-driven relationship between immune cell composition in the tumor microenvironment (TME) and the ≥5-year survival rates of breast cancer patients using explainable artificial intelligence (XAI) models. We acquired TCGA breast invasive carcinoma data from the cbioPortal and retrieved immune cell composition estimates from bulk RNA sequencing data from TIMER2.0 based on EPIC, CIBERSORT, TIMER, and xCell computational methods. Novel insights derived from our XAI model showed that B cells, CD8+ T cells, M0 macrophages, and NK T cells are the most critical TME features for enhanced prognosis of breast cancer patients. Our XAI model also revealed the inflection points of these critical TME features, above or below which ≥5-year survival rates improve. Subsequently, we ascertained the conditional probabilities of ≥5-year survival under specific conditions inferred from the inflection points. In particular, the XAI models revealed that the B cell fraction (relative to all cells in a sample) exceeding 0.025, M0 macrophage fraction (relative to the total immune cell content) below 0.05, and NK T cell and CD8+ T cell fractions (based on cancer type-specific arbitrary units) above 0.075 and 0.25, respectively, in the TME could enhance the ≥5-year survival in breast cancer patients. The findings could lead to accurate clinical predictions and enhanced immunotherapies, and to the design of innovative strategies to reprogram the breast TME.

scholarly journals Cellular heterogeneity map of diverse immune and stromal phenotypes within breast tumor microenvironment

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9478
Author(s):  
Yuan Li ◽  
Zuhua Chen ◽  
Long Wu ◽  
Junjie Ye ◽  
Weiping Tao
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
Prognostic Factors ◽  
Tumor Microenvironment ◽  
Cancer Patients ◽  
Breast Tumor ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Breast Cancer Patients ◽  
Normal Tissues

Background Cellular heterogeneity within the tumor microenvironment is essential to tumorigenesis and tumor development. A high-resolution global view of the tumor-infiltrating immune and stromal cells in breast tumors is needed. Methods xCell was used to create a cellular heterogeneity map of 64 cell types in 1,092 breast tumor and adjacent normal tissues. xCell digitally dissects tissue cellular heterogeneity based on gene expression. Integrated statistical analyses were then performed. Results There were noticeable differences between the cell fractions in tumor tissues and normal tissues. Tumors displayed higher proportions of immune cells, including CD4+ Tem, CD8+ naïve T cells, and CD8+ Tcm compared with normal tissues. Immune inhibitory receptors (PD1, CTLA4, LAG3 and TIM3) were co-expressed on certain subtypes of T cells in breast tumors, and PD1 and CTLA4 were both positively correlated with CD8+ Tcm and CD8+ T cells. 28 cell types were significantly associated with overall survival in univariate analysis. CD4+ Tem, CD8+ Tcm, CD8+ T-cells, CD8+ naive T-cells, and B cells were positive prognostic factors but CD4+ naive T-cells were negative prognostic factors for breast cancer patients. TDRD6 and TTK are promising T cell and B cell targets for tumor vaccines. Endothelial cells and fibroblasts were significantly less prevalent in tumor tissues; astrocytes and mesangial cells were negatively correlated with the T stage. Mesangial cells and keratinocytes were found to be favorable prognostic factors and myocytes were negative prognostic factors. Five cell types were found to be independent prognostic factors and we used these to create a reliable prognostic model for breast cancer patients. Cellular heterogeneity was discovered among different breast cancer subtypes by Her2, ER, and PR status. Tri-negative patients had the highest fraction of immune cells while luminal type patients had the lowest. The various cells may have diverse or opposing roles in the prognosis of breast cancer patients. Conclusions We created a uniquecellular map for the diverse heterogeneity of immune and stromal phenotypes within the breast tumor microenvironment. This map may lead to potential therapeutic targets and biomarkers with prognostic utility.

scholarly journals Effects of a Chinese medical herbs complex on cellular immunity and toxicity-related conditions of breast cancer patients

2011 ◽  
Vol 107 (5) ◽  
pp. 712-718 ◽  
Author(s):  
S. R. Zhuang ◽  
H. F. Chiu ◽  
S. L. Chen ◽  
J. H. Tsai ◽  
M. Y. Lee ◽  
...  
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
Placebo Group ◽  
Cancer Treatment ◽  
Cancer Patients ◽  
Immune Cell ◽  
Chinese Herbs ◽  
Controlled Study ◽  
Breast Cancer Patients ◽  
Chinese Medicinal Herb

Rose geranium (Pelargonium graveolens, Geraniaceae) has anti-cancer and anti-inflammatory properties, and promotes wound healing. Similarly,Ganoderma tsugae(Ganodermataceae),Codonopsis pilosula(Campanulaceae) andAngelica sinensis(Apiaceae) are traditional Chinese herbs associated with immunomodulatory functions. In the present study, a randomised, double-blind, placebo-controlled study was conducted to examine whether the Chinese medicinal herb complex, RG-CMH, which represents a mixture of rose geranium and extracts ofG. tsugae, C. pilosula and A. sinensis, can improve the immune cell count of cancer patients receiving chemotherapy and/or radiotherapy to prevent leucopenia and immune impairment that usually occurs during cancer therapy. A total of fifty-eight breast cancer patients who received chemotherapy or radiotherapy were enrolled. Immune cell levels in patient serum were determined before, and following, 6 weeks of cancer treatment for patients receiving either an RG-CMH or a placebo. Administration of RG-CMH was associated with a significant reduction in levels of leucocytes from 31·5 % for the placebo group to 13·4 % for the RG-CMH group. Similarly, levels of neutrophils significantly decreased from 35·6 % for the placebo group to 11·0 % for the RG-CMH group. RG-CMH intervention was also associated with a decrease in levels of T cells, helper T cells, cytotoxic T cells and natural killer cells compared with the placebo group. However, these differences between the two groups were not statistically significant. In conclusion, administration of RG-CMH to patients receiving chemotherapy/radiotherapy may have the capacity to delay, or ease, the reduction in levels of leucocytes and neutrophils that are experienced by patients during cancer treatment.

scholarly journals High WHSC1L1 Expression Reduces Survival Rates in Operated Breast Cancer Patients with Decreased CD8+ T Cells: Machine Learning Approach

2021 ◽  
Vol 11 (7) ◽  
pp. 636
Author(s):  
Hyung-Suk Kim ◽  
Kyueng-Whan Min ◽  
Dong-Hoon Kim ◽  
Byoung-Kwan Son ◽  
Mi-Jung Kwon ◽  
...  
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
Cancer Patients ◽  
Cd8 T Cells ◽  
Survival Rates ◽  
Gradient Boosting ◽  
Breast Cancer Cell Lines ◽  
Breast Cancer Patients ◽  
Cancer Pathogenesis ◽  
Pathway Networks

Nuclear receptor-binding SET domain protein (NSD), a histone methyltransferase, is known to play an important role in cancer pathogenesis. The WHSC1L1 (Wolf-Hirschhorn syndrome candidate 1-like 1) gene, encoding NSD3, is highly expressed in breast cancer, but its role in the development of breast cancer is still unknown. The purpose of this study was to analyze the survival rates and immune responses of breast cancer patients with high WHSC1L1 expression and to validate the results using gradient boosting machine (GBM) in breast cancer. We investigated the clinicopathologic parameters, proportions of immune cells, pathway networks and in vitro drug responses according to WHSC1L1 expression in 456, 1500 and 776 breast cancer patients from the Hanyang University Guri Hospital, METABRIC and TCGA, respectively. High WHSC1L1 expression was associated with poor prognosis, decreased CD8+ T cells and high CD274 expression (encoding PD-L1). In the pathway networks, WHSC1L1 was indirectly linked to the regulation of the lymphocyte apoptotic process. The GBM model with WHSC1L1 showed improved prognostic performance compared with the model without WHSC1L1. We found that VX-11e, CZC24832, LY2109761, oxaliplatin and erlotinib were effective in inhibiting breast cancer cell lines with high WHSC1L1 expression. High WHSC1L1 expression could play potential roles in the progression of breast cancer and targeting WHSC1L1 could be a potential strategy for the treatment of breast cancer.

scholarly journals Abnormal Long Non-Coding RNAs Expression Patterns Have the Potential Ability for Predicting Survival and Treatment Response in Breast Cancer

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 996
Author(s):  
Ana Carolina Pavanelli ◽  
Flavia Rotea Mangone ◽  
Luciana R. C. Barros ◽  
Juliana Machado-Rugolo ◽  
Vera L. Capelozzi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Predictive Value ◽  
Expression Patterns ◽  
Survival Rates ◽  
In Silico Analysis ◽  
Cancer Prognosis ◽  
Response To Treatment ◽  
Breast Cancer Patients ◽  
Non Coding Rnas

Abnormal long non-coding RNAs (lncRNAs) expression has been documented to have oncogene or tumor suppressor functions in the development and progression of cancer, emerging as promising independent biomarkers for molecular cancer stratification and patients’ prognosis. Examining the relationship between lncRNAs and the survival rates in malignancies creates new scenarios for precision medicine and targeted therapy. Breast cancer (BRCA) is a heterogeneous malignancy. Despite advances in its molecular classification, there are still gaps to explain in its multifaceted presentations and a substantial lack of biomarkers that can better predict patients’ prognosis in response to different therapeutic strategies. Here, we performed a re-analysis of gene expression data generated using cDNA microarrays in a previous study of our group, aiming to identify differentially expressed lncRNAs (DELncRNAs) with a potential predictive value for response to treatment with taxanes in breast cancer patients. Results revealed 157 DELncRNAs (90 up- and 67 down-regulated). We validated these new biomarkers as having prognostic and predictive value for breast cancer using in silico analysis in public databases. Data from TCGA showed that compared to normal tissue, MIAT was up-regulated, while KCNQ1OT1, LOC100270804, and FLJ10038 were down-regulated in breast tumor tissues. KCNQ1OT1, LOC100270804, and FLJ10038 median levels were found to be significantly higher in the luminal subtype. The ROC plotter platform results showed that reduced expression of these three DElncRNAs was associated with breast cancer patients who did not respond to taxane treatment. Kaplan–Meier survival analysis revealed that a lower expression of the selected lncRNAs was significantly associated with worse relapse-free survival (RFS) in breast cancer patients. Further validation of the expression of these DELncRNAs might be helpful to better tailor breast cancer prognosis and treatment.

scholarly journals Tumor specific regulatory T cells in the bone marrow of breast cancer patients selectively upregulate the emigration receptor S1P1

2017 ◽  
Vol 66 (5) ◽  
pp. 593-603 ◽  
Author(s):  
Anchana Rathinasamy ◽  
Christoph Domschke ◽  
Yingzi Ge ◽  
Hans-Henning Böhm ◽  
Steffen Dettling ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Bone Marrow ◽  
T Cells ◽  
Regulatory T Cells ◽  
Cancer Patients ◽  
Breast Cancer Patients
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