Abstract 5405: Immuno-phenotyping reveals cell types present in circulation of breast cancer patients and elucidates their funstional potential

Abstract To better understand the heterogeneity of tumor microenvironment (TME) and establish a prognostic model for breast cancer in clinical practice, the leukocyte infiltrations of 22 cell types of interest from 2620 breast cancer patients were quantitatively estimated using deconvolution algorithms, and three TME subtypes with distinct molecular and clinical features were identified by unsupervised clustering approach. Then, we carried out systematic analyses to illustrate the contributing mechanisms for differential phenotypes, which suggested that the divergences were distinguished by cell cycle dysfunction, variation of cytotoxic T lymphocytes activity. Next, through dimensionally reduction and selection based on random-forest analysis, least absolute shrinkage and selection operator (LASSO) analysis, and uni- and multivariate COX regression analysis, a total of 15 significant genes were proposed to construct the prognostic immune-related score (pIRS) system and, in combinations with clinicopathological characteristics, a predictive model was ultimately built with well performance for survival of breast cancer patients. Comparative analyses demonstrated that proactivity of CD8 T lymphocytes and hyper-angiogenesis could be attributed to distinct prognostic outcomes. In conclusion, we retrieved three TME phenotypes and the curated prognostic model based on pIRS system for breast cancer. This model is justified for validation and optimized in the coming future.

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CETSA-based target engagement of taxanes as biomarkers for efficacy and resistance

Scientific Reports ◽

10.1038/s41598-019-55526-8 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 3

Author(s):

Anette Langebäck ◽

Smaranda Bacanu ◽

Henriette Laursen ◽

Lisanne Mout ◽

Takahiro Seki ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Patients ◽

Cell Lines ◽

Drug Efficacy ◽

Cell Types ◽

Specific Cell ◽

Target Engagement ◽

Breast Cancer Patients ◽

Acquired Drug Resistance ◽

Pdx Models

AbstractThe use of taxanes has for decades been crucial for treatment of several cancers. A major limitation of these therapies is inherent or acquired drug resistance. A key to improved outcome of taxane-based therapies is to develop tools to predict and monitor drug efficacy and resistance in the clinical setting allowing for treatment and dose stratification for individual patients. To assess treatment efficacy up to the level of drug target engagement, we have established several formats of tubulin-specific Cellular Thermal Shift Assays (CETSAs). This technique was evaluated in breast and prostate cancer models and in a cohort of breast cancer patients. Here we show that taxanes induce significant CETSA shifts in cell lines as well as in animal models including patient-derived xenograft (PDX) models. Furthermore, isothermal dose response CETSA measurements allowed for drugs to be rapidly ranked according to their reported potency. Using multidrug resistant cancer cell lines and taxane-resistant PDX models we demonstrate that CETSA can identify taxane resistance up to the level of target engagement. An imaging-based CETSA format was also established, which in principle allows for taxane target engagement to be accessed in specific cell types in complex cell mixtures. Using a highly sensitive implementation of CETSA, we measured target engagement in fine needle aspirates from breast cancer patients, revealing a range of different sensitivities. Together, our data support that CETSA is a robust tool for assessing taxane target engagement in preclinical models and clinical material and therefore should be evaluated as a prognostic tool during taxane-based therapies.

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Radiation-induced chromosome aberrations in two cell types of healthy donors and breast cancer patients

European Journal of Cancer ◽

10.1016/s0959-8049(99)81163-0 ◽

1999 ◽

Vol 35 ◽

pp. S191

Author(s):

H. Schmidberger ◽

P. Virsik-Peuckert ◽

M. Rave-Fränk ◽

C.F. Hess

Keyword(s):

Breast Cancer ◽

Cancer Patients ◽

Chromosome Aberrations ◽

Cell Types ◽

Breast Cancer Patients ◽

Healthy Donors ◽

Radiation Induced

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

PeerJ ◽

10.7717/peerj.9478 ◽

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.

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