A comprehensive single-cell map of T cell exhaustion-associated immune environments in human breast cancer

Immune checkpoint therapy in breast cancer remains restricted to triple negative patients, and long-term clinical benefit is rare. The primary aim of immune checkpoint blockade is to prevent or reverse exhausted T cell states, but T cell exhaustion in breast tumors is not well understood. Here, we use single-cell transcriptomics combined with imaging mass cytometry to systematically study immune environments of human breast tumors that either do or do not contain exhausted T cells, with a focus on luminal subtypes. We find that the presence of a PD-1high exhaustion-like T cell phenotype is associated with an inflammatory immune environment with a characteristic cytotoxic profile, increased myeloid cell activation, evidence for elevated immunomodulatory, chemotactic, and cytokine signaling, and accumulation of natural killer T cells. Tumors harboring exhausted-like T cells show increased expression of MHC-I on tumor cells and of CXCL13 on T cells, as well as altered spatial organization with more immature rather than mature tertiary lymphoid structures. Our data reveal fundamental differences between immune environments with and without exhausted T cells within luminal breast cancer, and show that expression of PD-1 and CXCL13 on T cells, and MHC-I - but not PD-L1 - on tumor cells are strong distinguishing features between these environments

AKT1 (E17K) mutation profiling in breast cancer: prevalence, concurrent oncogenic alterations, and blood-based detection.

BACKGROUND: The single hotspot mutation AKT1 [G49A:E17K] has been described in several cancers, with the highest incidence observed in breast cancer. However, its precise role in disease etiology remains unknown. METHODS: We analyzed more than 600 breast cancer tumor samples and circulating tumor DNA for AKT1 (E17K) and alterations in other cancer-associated genes using Beads, Emulsions, Amplification, and Magnetics digital polymerase chain reaction technology and targeted exome sequencing. RESULTS: Overall AKT1 (E17K) mutation prevalence was 6.3 % and not correlated with age or menopausal stage. AKT1 (E17K) mutation frequency tended to be lower in patients with grade 3 disease (1.9 %) compared with those with grade 1 (11.1 %) or grade 2 (6 %) disease. In two cohorts of patients with advanced metastatic disease, 98.0 % (n = 50) and 97.1 % (n = 35) concordance was obtained between tissue and blood samples for the AKT1 (E17K) mutation, and mutation capture rates of 66.7 % (2/3) and 85.7 % (6/7) in blood versus tissue samples were observed. Although AKT1-mutant tumor specimens were often found to harbor concurrent alterations in other driver genes, a subset of specimens harboring AKT1 (E17K) as the only known driver alteration was also identified. Initial follow-up survival data suggest that AKT1 (E17K) could be associated with increased mortality. These findings warrant additional long-term follow-up. CONCLUSIONS: The data suggest that AKT1 (E17K) is the most likely disease driver in certain breast cancer patients. Blood-based mutation detection is achievable in advanced-stage disease. These findings underpin the need for a further enhanced-precision medicine paradigm in the treatment of breast cancer

Cancer-associated fibroblast classification in single-cell and spatial proteomics data

Abstract Cancer-associated fibroblasts (CAFs) are a diverse cell population within the tumour microenvironment, where they have critical effects on tumour evolution and patient prognosis. To define CAF phenotypes, we analyse a single-cell RNA sequencing (scRNA-seq) dataset of over 16,000 stromal cells from tumours of 14 breast cancer patients, based on which we define and functionally annotate nine CAF phenotypes and one class of pericytes. We validate this classification system in four additional cancer types and use highly multiplexed imaging mass cytometry on matched breast cancer samples to confirm our defined CAF phenotypes at the protein level and to analyse their spatial distribution within tumours. This general CAF classification scheme will allow comparison of CAF phenotypes across studies, facilitate analysis of their functional roles, and potentially guide development of new treatment strategies in the future

A comprehensive single-cell map of T cell exhaustion-associated immune environments in human breast cancer

Immune checkpoint therapy in breast cancer remains restricted to triple negative patients, and long-term clinical benefit is rare. The primary aim of immune checkpoint blockade is to prevent or reverse exhausted T cell states, but T cell exhaustion in breast tumors is not well understood. Here, we use single-cell transcriptomics combined with imaging mass cytometry to systematically study immune environments of human breast tumors that either do or do not contain exhausted T cells, with a focus on luminal subtypes. We find that the presence of a PD-1high exhaustion-like T cell phenotype is associated with an inflammatory immune environment with a characteristic cytotoxic profile, increased myeloid cell activation, evidence for elevated immunomodulatory, chemotactic, and cytokine signaling, and accumulation of natural killer T cells. Tumors harboring exhausted-like T cells show increased expression of MHC-I on tumor cells and of CXCL13 on T cells, as well as altered spatial organization with more immature rather than mature tertiary lymphoid structures. Our data reveal fundamental differences between immune environments with and without exhausted T cells within luminal breast cancer, and show that expression of PD-1 and CXCL13 on T cells, and MHC-I – but not PD-L1 – on tumor cells are strong distinguishing features between these environments.ISSN:2041-172

Compared DNA and RNA quality of breast cancer biobanking samples after long-term storage protocols in − 80 °C and liquid nitrogen

Molecular investigations are crucial for further developments in precision medicine. RNA sequencing, alone or in combination with further omic-analyses, resulted in new therapeutic strategies. In this context, biobanks represent infrastructures to store tissue samples and body fluids in combination with clinical data to promote research for new predictive and prognostic biomarkers as well as therapeutic candidate molecules. Until today, the optimal storage conditions are a matter of debate especially with view to the storage temperature. In this unique approach we compared parallel samples from the same tumour, one half stored at - 80 degrees C and one half in the vapor phase of liquid nitrogen, with almost identical pre-analytical conditions. We demonstrated that RNA isolated from breast cancer samples revealed significantly higher RINe-values after 10 years of storage in the vapor phase of liquid nitrogen compared to storage at - 80 degrees C. In contrast, no significant difference was found regarding the DIN-values after DNA isolation. Morphological changes of the nucleus and cytoplasm, especially in the samples stored at - 80 degrees C, gave insights to degenerative effects, most possibly due to the storage protocol and its respective peculiarities. In addition, our results indicate that exact point-to point documentation beginning at the sample preparation is mandatory

Promoter hypermethylation of the tumor- suppressor genes ITIH5, DKK3, and RASSF1A as novel biomarkers for blood-based breast cancer screening

Abstract Introduction: For early detection of breast cancer, the development of robust blood-based biomarkers that accurately reflect the host tumor is mandatory. We investigated DNA methylation in circulating free DNA (cfDNA) from blood of breast cancer patients and matched controls to establish a biomarker panel potentially useful for early detection of breast cancer. Methods: We examined promoter methylation of seven putative tumor-suppressor genes (SFRP1, SFRP2, SFRP5, ITIH5, WIF1, DKK3, and RASSF1A) in cfDNA extracted from serum. Clinical performance was first determined in a test set (n = 261 sera). In an independent validation set (n = 343 sera), we validated the most promising genes for further use in early breast cancer detection. Sera from 59 benign breast disease and 58 colon cancer patients were included for additional specificity testing. Results: Based on the test set, we determined ITIH5 and DKK3 promoter methylation as candidate biomarkers with the best sensitivity and specificity. In both the test and validation set combined, ITIH5 and DKK3 methylation achieved 41% sensitivity with a specificity of 93% and 100% in healthy and benign disease controls, respectively. Combination of these genes with RASSF1A methylation increased the sensitivity to 67% with a specificity of 69% and 82% in healthy controls and benign disease controls, respectively

Promoter hypermethylation of the tumor-suppressor genes ITIH5, DKK3, and RASSF1A as novel biomarkers for blood-based breast cancer screening

Introduction For early detection of breast cancer, the development of robust blood-based biomarkers that accurately reflect the host tumor is mandatory. We investigated DNA methylation in circulating free DNA (cfDNA) from blood of breast cancer patients and matched controls to establish a biomarker panel potentially useful for early detection of breast cancer. Methods We examined promoter methylation of seven putative tumor-suppressor genes (SFRP1, SFRP2, SFRP5, ITIH5, WIF1, DKK3, and RASSF1A) in cfDNA extracted from serum. Clinical performance was first determined in a test set (n = 261 sera). In an independent validation set (n = 343 sera), we validated the most promising genes for further use in early breast cancer detection. Sera from 59 benign breast disease and 58 colon cancer patients were included for additional specificity testing. Results Based on the test set, we determined ITIH5 and DKK3 promoter methylation as candidate biomarkers with the best sensitivity and specificity. In both the test and validation set combined, ITIH5 and DKK3 methylation achieved 41% sensitivity with a specificity of 93% and 100% in healthy and benign disease controls, respectively. Combination of these genes with RASSF1A methylation increased the sensitivity to 67% with a specificity of 69% and 82% in healthy controls and benign disease controls, respectively. Conclusions Tumor-specific methylation of the three-gene panel (ITIH5, DKK3, and RASSF1A) might be a valuable biomarker for the early detection of breast cancer