Subtype-dependent prognostic relevance of an interferon-induced pathway metagene in node-negative breast cancer

Progression of monoclonal gammopathy of undetermined significance to multiple myeloma is associated with enhanced translational quality control and overall loss of surface antigens

BACKGROUND

Despite significant advancements in treatment strategies, multiple myeloma remains incurable. Additionally, there is a distinct lack of reliable biomarkers that can guide initial treatment decisions and help determine suitable replacement or adjuvant therapies when relapse ensues due to acquired drug resistance.

METHODS

To define specific proteins and pathways involved in the progression of monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM), we have applied super-SILAC quantitative proteomic analysis to CD138 + plasma cells from 9 individuals with MGUS and 37 with MM.

RESULTS

Unsupervised hierarchical clustering defined three groups: MGUS, MM, and MM with an MGUS-like proteome profile (ML) that may represent a group that has recently transformed to MM. Statistical analysis identified 866 differentially expressed proteins between MM and MGUS, and 189 between MM and ML, 177 of which were common between MGUS and ML. Progression from MGUS to MM is accompanied by upregulated EIF2 signaling, DNA repair, and proteins involved in translational quality control, whereas integrin- and actin cytoskeletal signaling and cell surface markers are downregulated.

CONCLUSION

Compared to the premalignant plasma cells in MGUS, malignant MM cells apparently have mobilized several pathways that collectively contribute to ensure translational fidelity and to avoid proteotoxic stress, especially in the ER. The overall reduced expression of immunoglobulins and surface antigens contribute to this and may additionally mediate evasion from recognition by the immune apparatus. Our analyses identified a range of novel biomarkers with potential prognostic and therapeutic value, which will undergo further evaluation to determine their clinical significance.

Grainyhead-like-2, an epithelial master programmer, promotes interferon induction and suppresses breast cancer recurrence

Type-I and -III interferons play a central role in immune rejection of pathogens and tumors, thus promoting immunogenicity and suppressing tumor recurrence. Double strand RNA is an important ligand that stimulates tumor immunity via interferon responses. Differentiation of embryonic stem cells to pluripotent epithelial cells activates the interferon response during development, raising the question of whether epithelial vs. mesenchymal gene signatures in cancer potentially regulate the interferon pathway as well. Here, using genomics and signaling approaches, we show that Grainyhead-like-2 (GRHL2), a master programmer of epithelial cell identity, promotes type-I and -III interferon responses to double-strand RNA. GRHL2 enhanced the activation of IRF3 and relA/NF-kB and the expression of IRF1; a functional GRHL2 binding site in the IFNL1 promoter was also identified. Moreover, time to recurrence in breast cancer correlated positively with GRHL2 protein expression, indicating that GRHL2 is a tumor recurrence suppressor, consistent with its enhancement of interferon responses. These observations demonstrate that epithelial cell identity supports interferon responses in the context of cancer.

A three-gene signature marks the time to locoregional recurrence in luminal-like breast cancer

BACKGROUND

Gene expression profiling (GEP)-based prognostic signatures are being rapidly integrated into clinical decision making for systemic management of breast cancer patients. However, GEP remains relatively underdeveloped for locoregional risk assessment. Yet, locoregional recurrence (LRR), especially early after surgery, is associated with poor survival.

PATIENTS AND METHODS

GEP was carried out on two independent luminal-like breast cancer cohorts of patients developing early (≤5 years after surgery) or late (>5 years) LRR and used, by a training and testing approach, to build a gene signature able to intercept women at risk of developing early LRR. The GEP data of two in silico datasets and of a third independent cohort were used to explore its prognostic value.

RESULTS

Analysis of the first two cohorts led to the identification of three genes, CSTB, CCDC91 and ITGB1, whose expression, derived by principal component analysis, generated a three-gene signature significantly associated with early LRR in both cohorts (P value <0.001 and 0.005, respectively), overcoming the discriminatory capability of age, hormone receptor status and therapy. Remarkably, the integration of the signature with these clinical variables led to an area under the curve of 0.878 [95% confidence interval (CI) 0.810-0.945]. In in silico datasets we found that the three-gene signature retained its association, showing higher values in the early relapsed patients. Moreover, in the third additional cohort, the signature significantly associated with relapse-free survival (hazard ratio 1.56, 95% CI 1.04-2.35).

CONCLUSIONS

Our three-gene signature represents a new exploitable tool to aid treatment choice in patients with luminal-like breast cancer at risk of developing early recurrence.

Polo-like kinase 1 is related with malignant characteristics and inhibits macrophages infiltration in glioma

Background

Tumor immune microenvironment (TIM) plays a critical role in tumorigenesis and progression. Recently, therapies based on modulating TIM have made great breakthroughs in cancer treatment. Polo-like kinase 1 (PLK1) is a crucial regulatory factor of the cell cycle process and its dysregulations often cause various pathological processes including tumorigenesis. However, the detailed mechanisms surrounding the regulation of PLK1 on glioma immune microenvironment remain undefined.

Methods

Public databases and online datasets were used to extract data of PLK1 expression, clinical features, genetic alterations, and biological functions. The EdU, flow cytometry, and macrophage infiltration assays as well as xenograft animal experiments were performed to determine the relationship between PLK1 and glioma immune microenvironment in vivo and in vitro.

Results

PLK1 is always highly expressed in multiple cancers especially in glioma. Univariable and Multivariate proportional hazard Cox analysis showed that PLK1 was a prognostic biomarker for glioma. Simultaneously, highly expressed PLK1 is significantly related to prognosis, histological and genetic features in glioma by analyzing public databases. In addition, the enrichment analysis suggested that PLK1 might related to "immune response", "cell cycle", "DNA replication", and "mismatch repair" in glioma. Immune infiltration analysis demonstrated that highly expressed PLK1 inhibited M1 macrophages infiltration to glioblastoma immune microenvironment by Quantiseq and Xcell databases and negatively related to some chemokines and marker genes of M1 macrophages in glioblastoma. Subsequent experiments confirmed that PLK1 knockdown inhibited the proliferation of glioma cells but increased the M1 macrophages infiltration and polarization. Furthermore, in glioma xenograft mouse models, we showed that inhibiting PLK1 blocked tumor proliferation and increased the M1 macrophages infiltration. Finally, PLK1 methylation analysis and lncRNA-miRNA network revealed the potential mechanism of abnormal PLK1 expression in glioma.

Conclusions

PLK1 inhibits M1 macrophages infiltration into glioma immune microenvironment and is a potential biomarker for glioma.

Investigation of genes and pathways involved in breast cancer subtypes through gene expression meta-analysis

BACKGROUND

Molecular-based studies have revealed heterogeneity in Breast cancer BC while also improving classification and treatment. However, efforts are underway to distinguish between distinct subtypes of breast cancer. In this study, the results of several microarray studies were combined to identify genes and pathways specific to each BC subtype.

METHODS

Meta-analysis of multiple gene expression profile datasets was screened to find differentially expressed genes (DEGs) across subtypes of BC and normal breast tissue samples. Protein-protein interaction network and gene set enrichment analysis were used to identify critical genes and pathways associated with BC subtypes. The differentially expressed genes from meta-analysis was validated using an independent comprehensive breast cancer RNA-sequencing dataset obtained from the Cancer Genome Atlas (TCGA).

RESULTS

We identified 110 DEGs (13 DEGs in all and 97 DEGs in each subtype) across subtypes of BC. All subtypes had a small set of shared DEGs enriched in the Chemokine receptor bind chemokine pathway. Luminal A specific were enriched in the translational elongation process in mitochondria, and the enhanced process in luminal B subtypes was interferon-alpha/beta signaling. Cell cycle and mitotic DEGs were enriched in the basal-like group. All subtype-specific DEG genes (100%) were successfully validated for Luminal A, Luminal B, ERBB2, and Normal-like. However, the validation percentage for Basal-like group was 77.8%.

CONCLUSION

Integrating researches such as a meta-analysis of gene expression might be more effective in uncovering subtype-specific DEGs and pathways than a single-study analysis. It would be more beneficial to increase the number of studies that use matched BC subtypes along with GEO profiling approaches to reach a better result regarding DEGs and reduce probable biases. However, achieving 77.8% overlap in basal-specific genes and complete concordance in specific genes related to other subtypes can implicate the strength of our analysis for discovering the subtype-specific genes.

Clonal populations of a human TNBC model display significant functional heterogeneity and divergent growth dynamics in distinct contexts

Intratumoral heterogeneity has been described for various tumor types and models of human cancer, and can have profound effects on tumor progression and drug resistance. This study describes an in-depth analysis of molecular and functional heterogeneity among subclonal populations (SCPs) derived from a single triple-negative breast cancer cell line, including copy number analysis, whole-exome and RNA sequencing, proteome analysis, and barcode analysis of clonal dynamics, as well as functional assays. The SCPs were found to have multiple unique genetic alterations and displayed significant variation in anchorage independent growth and tumor forming ability. Analyses of clonal dynamics in SCP mixtures using DNA barcode technology revealed selection for distinct clonal populations in different in vitro and in vivo environmental contexts, demonstrating that in vitro propagation of cancer cell lines using different culture conditions can contribute to the establishment of unique strains. These analyses also revealed strong enrichment of a single SCP during the development of xenograft tumors in immune-compromised mice. This SCP displayed attenuated interferon signaling in vivo and reduced sensitivity to the antiproliferative effects of type I interferons. Reduction in interferon signaling was found to provide a selective advantage within the xenograft microenvironment specifically. In concordance with the previously described role of interferon signaling as tumor suppressor, these findings suggest that similar selective pressures may be operative in human cancer and patient-derived xenograft models.

Identification of genes and pathways related to breast cancer metastasis in an integrated cohort

BACKGROUND

Breast cancer is the most common malignant disease in women. Metastasis is the most common cause of death from this cancer. Screening genes related to breast cancer metastasis may help elucidate the mechanisms governing metastasis and identify molecular targets for antimetastatic therapy. The development of advanced algorithms enables us to perform cross-study analysis to improve the robustness of the results.

MATERIALS AND METHODS

Ten data sets meeting our criteria for differential expression analyses were obtained from the Gene Expression Omnibus (GEO) database. Among these data sets, five based on the same platform were formed into a large cohort using the XPN algorithm. Differentially expressed genes (DEGs) associated with breast cancer metastasis were identified using the differential expression via distance synthesis (DEDS) algorithm. A cross-platform method was employed to verify these DEGs in all ten selected data sets. The top 50 validated DEGs are represented with heat maps. Based on the validated DEGs, Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Protein interaction (PPI) networks were constructed to further illustrate the direct and indirect associations among the DEGs. Survival analysis was performed to explore whether these genes can affect breast cancer patient prognosis.

RESULTS

A total of 817 DEGs were identified using the DEDS algorithm. Of these DEGs, 450 genes were validated by the second algorithm. Enriched KEGG pathway terms demonstrated that these 450 DEGs may be involved in the cell cycle and oocyte meiosis in addition to their functions in ECM-receptor interaction and protein digestion and absorption. PPI network analysis for the proteins encoded by the DEGs indicated that these genes may be primarily involved in the cell cycle and extracellular matrix. In particular, several genes played roles in multiple signalling pathways and were related to patient survival. These genes were also observed to be targetable in the CTD2 database.

CONCLUSIONS

Our study analysed multiple cross-platform data sets using two different algorithms, helping elucidate the molecular mechanisms and identify several potential therapeutic targets of metastatic breast cancer. In addition, several genes exhibited promise for applications in targeted therapy against metastasis in future research.

Type I T cells sensitize treatment refractory tumors to chemotherapy through inhibition of oncogenic signaling pathways

BACKGROUND

The most common clinical outcome observed after treatment with immune checkpoint inhibitor antibodies is disease stabilization. Using vaccines to generate high levels of tumor antigen-specific T-helper 1 (Th1), we show that tumors not eradicated by vaccination demonstrate prolonged disease stabilization. We evaluated the mechanism by which type I T cells inhibit disease progression and potentially influence the subsequent clinical response to standard therapy in treatment refractory cancers.

METHODS

We employed a meta-analysis of studies with tumor growth from four different vaccines in two different mammary cancer models. The T-cell subtype and cytokine essential for vaccine-induced tumor inhibition was determined by in vivo neutralization studies and immunohistochemistry. The role of interferon gamma (IFN-γ) in receptor tyrosine kinase and downstream signaling was determined by immunoblotting. The role of suppressor of cytokine signaling 1 (SOCS1) on IFN-γ signaling was evaluated on SOCS1-silenced cells with immunoblotting and immunoprecipitation. The effect of vaccination on growth factor receptor signaling pathways, performed in both luminal (TgMMTVneu) and basal (C3(1)-Tag) mammary cancer models treated with paclitaxel or an anti-HER2-neu monoclonal antibody were assessed via immunoblotting.

RESULTS

Immunization with an epitope-based vaccine targeting a representative tumor antigen resulted in elevated tumor trafficking Tbet+CD4 T cells, decreased tumor proliferation and increased apoptosis compared with control vaccinated mice. The resulting disease stabilization was dependent on IFN-γ-secreting CD4+ T cells. In the presence of excess IFN-γ, SOCS1 became upregulated in tumor cells, bound insulin receptor, insulin like growth factor receptor 1 and epidermal growth factor receptor resulting in profound oncogenic signaling inhibition. Silencing SOCS1 restored growth factor receptor signaling and proliferation and prevented cell death. Similar signaling perturbations were detected in vaccinated mice developing antigen-specific Th1 cells. Vaccination synergized with standard therapies and restored disease sensitivity to treatment with both a neu-specific antibody and paclitaxel in TgMMTVneu and to paclitaxel in C3(1)-Tag. Combination of vaccination and chemotherapy or biological therapy was more effective than monotherapy alone in either model and resulted in complete resolution of disease in some individuals.

CONCLUSIONS

These data suggest the clinical activity of type I T cells extends beyond direct tumor killing and immune therapies designed to increase type I T cells and could be integrated into standard chemotherapy regimens to enhance therapeutic efficacy.

A combination of extracellular matrix- and interferon-associated signatures identifies high-grade breast cancers with poor prognosis

Breast cancer (BC) is a heterogeneous disease in which the tumor microenvironment (TME) seems to impact the clinical outcome. Here, we investigated whether a combination of gene expression signatures relating to both the structural and immune TME aspects can help predict prognosis in women with high‐grade BC (HGBC). Thus, we focused on a combined molecular biomarker variable that involved extracellular matrix (ECM)‐associated gene expression (ECM3 signature) and interferon (IFN)‐associated metagene (IFN metagene) expression. In 97 chemo‐naive HGBCs from the METABRIC dataset, the dichotomous ECM3/IFN (dECIF) variable identified a group of high‐risk patients (ECM3⁺/IFN⁻ vs other; hazard ratio = 3.2, 95% confidence interval: 1.5–6.7). Notably, ECM3⁺/IFN⁻ tumors showed low tumor‐infiltrating lymphocytes, high levels of CD33‐positive cells, absence of PD‐1 expression, or low expression of PD‐L1, as suggested by immune profiles and immune‐histochemical analysis on an independent cohort of 131 HGBCs. To make our results transferable to clinical use, we refined the dECIF biomarker using reduced ECM3 and IFN signatures; notably, the prognostic value of this reduced dECIF was comparable to that of the original dECIF. After validation in a new BC cohort, reduced dECIF was translated into a robust qPCR classifier for real‐world clinical use.

Antibody-Based Targeting of Interferon-Beta-1a Mutein in HER2-Positive Cancer Enhances Antitumor Effects Through Immune Responses and Direct Cell Killing

Type I interferon (IFN) has been approved as an anticancer agent to treat some malignancies. However, IFNs have a short in vivo half-life, systemic toxicity, and poor biophysical properties, which prevent it from being widely used for cancer therapy. This study aimed to construct recombinant IFN-β-1a mutein immunocytokines that comprise a human epidermal growth factor receptor 2 (HER2)-targeting antibody and IFN-β muteins with an additional glycosylation, which can overcome the limitation of the cytokine itself. Hence, the molecular design aims to 1) enhance productivity and biophysical properties by adding secondary glycosylation in IFN-β, 2) increase the therapeutic index of IFN-β therapy by preferential retention at the tumor by possessing high affinity for HER2-expressing cancer cells, and 3) improve the pharmacokinetics and, thus, the convenience of IFN-β administration. The yield of trastuzumab-IFN-β mutein was higher than that of trastuzumab-wild-type IFN-β in the mammalian cell culture system. Trastuzumab-IFN-β mutein showed similar IFN activity and HER2-targeting ability equivalent to that of IFN-β mutein and trastuzumab, respectively. Trastuzumab-IFN-β mutein directly inhibited the growth of HER2-positive gastric cancer cell lines and was more effective than trastuzumab or IFN-β mutein alone. Trastuzumab-IFN-β mutein and IFN-β mutein displayed enhanced immune cell-mediated cytotoxicity. Collectively, trastuzumab-IFN-β mutein may have indirect immune cell-mediated antitumor effects and direct cell growth inhibitory effects. Tumor-targeting effect of trastuzumab-IFN-β mutein was analyzed using in vivo fluorescence imaging. The accumulation of trastuzumab-IFN-β mutein was observed in HER2-positive tumors rather than other tissues except the liver. To evaluate the both direct tumor growth inhibition effect and indirect immune cell-mediated antitumor effect, we tested the effect of trastuzumab-IFN-β mutein in HER2-positive cancer xenograft models using nude mice or humanized mice. Trastuzumab-IFN-β mutein could significantly enhance tumor regression when compared with trastuzumab or IFN-β mutein. In addition, an increase in tumor-infiltrating lymphocytes was observed in the trastuzumab-IFN-β mutein-treated group, implying that the tumor-targeting IFN-β may have an enhanced antitumor effect through increased immune response. Therefore, targeting IFN-β with an anti-HER2 monoclonal antibody makes the immunocytokine more potent than either agent alone. These novel findings suggest that trastuzumab-IFN-β mutein merits clinical evaluation as a new candidate of anticancer therapeutics.

Prognostic Significance of Interferon-γ and Its Signaling Pathway in Early Breast Cancer Depends on the Molecular Subtypes

Interferons are crucial for adaptive immunity and play an important role in the immune landscape of breast cancer. Using microarray-based gene expression analysis, we examined the subtype-specific prognostic significance of interferon-γ (IFN-γ) as a single gene as well as an IFN-γ signature covering the signaling pathway in 461 breast cancer patients. Prognostic significance of IFN-γ, as well as the IFN-γ signature for metastasis-free survival (MFS), were examined using Kaplan-Meier as well as univariate and multivariate Cox regression analyses in the whole cohort and in different molecular subtypes. The independent prognostic significance of IFN-γ as a single gene was limited to basal-like breast cancer (hazard ratio (HR) 2.779, 95% confidence interval (95% CI) 1.117-6.919, p = 0.028). In contrast, the IFN-γ-associated gene signature was an independent prognostic factor in the whole cohort (HR 2.287, 95% CI 1.410-3.633, p < 0.001) as well as in the basal-like (HR 3.458, 95% CI 1.154-10.359, p = 0.027) and luminal B (HR 2.690, 95% CI 1.416-5.112, p = 0.003) molecular subtypes. These results underline the subtype-dependent prognostic influence of the immune system in early breast cancer.

Systems biology comprehensive analysis on breast cancer for identification of key gene modules and genes associated with TNM-based clinical stages

Breast cancer (BC), as one of the leading causes of death among women, comprises several subtypes with controversial and poor prognosis. Considering the TNM (tumor, lymph node, metastasis) based classification for staging of breast cancer, it is essential to diagnose the disease at early stages. The present study aims to take advantage of the systems biology approach on genome wide gene expression profiling datasets to identify the potential biomarkers involved at stage I, stage II, stage III, and stage IV as well as in the integrated group. Three HER2-negative breast cancer microarray datasets were retrieved from the GEO database, including normal, stage I, stage II, stage III, and stage IV samples. Additionally, one dataset was also extracted to test the developed predictive models trained on the three datasets. The analysis of gene expression profiles to identify differentially expressed genes (DEGs) was performed after preprocessing and normalization of data. Then, statistically significant prioritized DEGs were used to construct protein-protein interaction networks for the stages for module analysis and biomarker identification. Furthermore, the prioritized DEGs were used to determine the involved GO enrichment and KEGG signaling pathways at various stages of the breast cancer. The recurrence survival rate analysis of the identified gene biomarkers was conducted based on Kaplan-Meier methodology. Furthermore, the identified genes were validated not only by using several classification models but also through screening the experimental literature reports on the target genes. Fourteen (21 genes), nine (17 genes), eight (10 genes), four (7 genes), and six (8 genes) gene modules (total of 53 unique genes out of 63 genes with involving those with the same connectivity degree) were identified for stage I, stage II, stage III, stage IV, and the integrated group. Moreover, SMC4, FN1, FOS, JUN, and KIF11 and RACGAP1 genes with the highest connectivity degrees were in module 1 for abovementioned stages, respectively. The biological processes, cellular components, and molecular functions were demonstrated for outcomes of GO analysis and KEGG pathway assessment. Additionally, the Kaplan-Meier analysis revealed that 33 genes were found to be significant while considering the recurrence-free survival rate as an alternative to overall survival rate. Furthermore, the machine learning calcification models show good performance on the determined biomarkers. Moreover, the literature reports have confirmed all of the identified gene biomarkers for breast cancer. According to the literature evidence, the identified hub genes are highly correlated with HER2-negative breast cancer. The 53-mRNA signature might be a potential gene set for TNM based stages as well as possible therapeutics with potentially good performance in predicting and managing recurrence-free survival rates at stages I, II, III, and IV as well as in the integrated group. Moreover, the identified genes for the TNM-based stages can also be used as mRNA profile signatures to determine the current stage of the breast cancer.

OSbrca: A Web Server for Breast Cancer Prognostic Biomarker Investigation With Massive Data From Tens of Cohorts

Potential prognostic mRNA biomarkers are exploited to assist in the clinical management and treatment of breast cancer, which is the first life-threatening tumor in women worldwide. However, it is technically challenging for untrained researchers to process high dimensional profiling data to screen and validate the potential prognostic values of genes of interests in multiple cohorts. Our aim is to develop an easy-to-use web server to facilitate the screening, developing, and evaluating of prognostic biomarkers in breast cancers. Herein, we collected more than 7,400 cases of breast cancer with gene expression profiles and clinical follow-up information from The Cancer Genome Atlas and Gene Expression Omnibus data, and built an Online consensus Survival analysis web server for Breast Cancers, abbreviated OSbrca, to generate the Kaplan–Meier survival plot with a hazard ratio and log rank P-value for given genes in an interactive way. To examine the performance of OSbrca, the prognostic potency of 128 previously published biomarkers of breast cancer was reassessed in OSbrca. In conclusion, it is highly valuable for biologists and clinicians to perform the preliminary assessment and validation of novel or putative prognostic biomarkers for breast cancers. OSbrca could be accessed at http://bioinfo.henu.edu.cn/BRCA/BRCAList.jsp.

Interferons α and β in cancer: therapeutic opportunities from new insights

Over the past decade, preclinical and clinical research have confirmed the essential role of interferons for effective host immunological responses to malignant cells. Type I interferons (IFNα and IFNβ) directly regulate transcription of >100 downstream genes, which results in a myriad of direct (on cancer cells) and indirect (through immune effector cells and vasculature) effects on the tumour. New insights into endogenous and exogenous activation of type I interferons in the tumour and its microenvironment have given impetus to drug discovery and patient evaluation of interferon-directed strategies. When combined with prior observations or with other effective modalities for cancer treatment, modulation of the interferon system could contribute to further reductions in cancer morbidity and mortality. This Review discusses new interferon-directed therapeutic opportunities, ranging from cyclic dinucleotides to genome methylation inhibitors, angiogenesis inhibitors, chemoradiation, complexes with neoantigen-targeted monoclonal antibodies, combinations with other emerging therapeutic interventions and associations of interferon-stimulated gene expression with patient prognosis - all of which are strategies that have or will soon enter translational clinical evaluation.

Lung adenocarcinoma-intrinsic GBE1 signaling inhibits anti-tumor immunity

Background

Changes in glycogen metabolism is an essential feature among the various metabolic adaptations used by cancer cells to adjust to the conditions imposed by the tumor microenvironment. Our previous study showed that glycogen branching enzyme (GBE1) is downstream of the HIF1 pathway in hypoxia-conditioned lung cancer cells. In the present study, we investigated whether GBE1 is involved in the immune regulation of the tumor microenvironment in lung adenocarcinoma (LUAD).

Methods

We used RNA-sequencing analysis and the multiplex assay to determine changes in GBE1 knockdown cells. The role of GBE1 in LUAD was evaluated both in vitro and in vivo.

Results

GBE1 knockdown increased the expression of chemokines CCL5 and CXCL10 in A549 cells. CD8 expression correlated positively with CCL5 and CXCL10 expression in LUAD. The supernatants from the GBE1 knockdown cells increased recruitment of CD8⁺ T lymphocytes. However, the neutralizing antibodies of CCL5 or CXCL10 significantly inhibited cell migration induced by shGBE1 cell supernatants. STING/IFN-I pathway mediated the effect of GBE1 knockdown for CCL5 and CXCL10 upregulation. Moreover, PD-L1 increased significantly in shGBE1 A549 cells compared to those in control cells. Additionally, in LUAD tumor tissues, a negative link between PD-L1 and GBE1 was observed. Lastly, blockade of GBE1 signaling combined with anti-PD-L1 antibody significantly inhibited tumor growth in vivo.

Conclusions

GBE1 blockade promotes the secretion of CCL5 and CXCL10 to recruit CD8⁺ T lymphocytes to the tumor microenvironment via the IFN-I/STING signaling pathway, accompanied by upregulation of PD-L1 in LUAD cells, suggesting that GBE1 could be a promising target for achieving tumor regression through cancer immunotherapy in LUAD.

Electronic supplementary material

The online version of this article (10.1186/s12943-019-1027-x) contains supplementary material, which is available to authorized users.

Therapeutic targeting of macrophages enhances chemotherapy efficacy by unleashing type I interferon response

Recent studies have revealed a role for macrophages and neutrophils in limiting chemotherapy efficacy; however, the mechanisms underlying the therapeutic benefit of myeloid-targeting agents in combination with chemotherapy are incompletely understood. Here, we show that targeting tumour-associated macrophages by colony-stimulating factor-1 receptor (CSF-1R) blockade in the K14cre;Cdh1^F/F;Trp53^F/F transgenic mouse model for breast cancer stimulates intratumoural type I interferon (IFN) signalling, which enhances the anticancer efficacy of platinum-based chemotherapeutics. Notably, anti-CSF-1R treatment also increased intratumoural expression of type I IFN-stimulated genes in patients with cancer, confirming that CSF-1R blockade is a powerful strategy to trigger an intratumoural type I IFN response. By inducing an inflamed, type I IFN-enriched tumour microenvironment and by further targeting immunosuppressive neutrophils during cisplatin therapy, antitumour immunity was activated in this poorly immunogenic breast cancer mouse model. These data illustrate the importance of breaching multiple layers of immunosuppression during cytotoxic therapy to successfully engage antitumour immunity in breast cancer.

Immuno-Oncology in the Era of Personalized Medicine

Personalized medicine in oncology utilizes evidence derived from genetic, immune, and proteomic profiling to inform therapeutic options as well as provide prognostic information for each unique individual and their tumor. Our ability to biologically and immunologically define each patient's tumor has been driven by the development of assays characterizing the genomic and proteomic profiles of tumors that in turn have led to the development of large biologic databases and computational tools for the analysis of these large data sets. In Immuno-oncology, the introduction of checkpoint inhibitors and their approval across multiple tumor types has led to the recognition that the majority of patients will not clinically respond to these therapies but will remain at risk for the development of significant immunologic side effects. This challenge highlights the need for the development and validation of both predictive biomarkers for response to such therapies as well as biomarkers prognostic of disease course. Despite extensive investigation into predictive biomarkers using these biologic databases and computational methods, only recently has progress been made in this area. This progress is the first step allowing us to identify patients likely to benefit from these therapies and moving our field closer to a truly personalized approach to the use of immune therapies in oncology.

BAG3 Overexpression and Cytoprotective Autophagy Mediate Apoptosis Resistance in Chemoresistant Breast Cancer Cells

Target-specific treatment modalities are currently not available for triple-negative breast cancer (TNBC), and acquired chemotherapy resistance is a primary obstacle for the treatment of these tumors. Here we employed derivatives of BT-549 and MDA-MB-468 TNBC cell lines that were adapted to grow in the presence of either 5-Fluorouracil, Doxorubicin or Docetaxel in an aim to identify molecular pathways involved in the adaptation to drug-induced cell killing. All six drug-adapted BT-549 and MDA-MB-468 cell lines displayed cross resistance to chemotherapy and decreased apoptosis sensitivity. Expression of the anti-apoptotic co-chaperone BAG3 was notably enhanced in two thirds (4/6) of the six resistant lines simultaneously with higher expression of HSP70 in comparison to parental controls. Doxorubicin-resistant BT-549 (BT-549^rDOX²⁰) and 5-Fluorouracil-resistant MDA-MB-468 (MDA-MB-468^r5-FU²⁰⁰⁰) cells were chosen for further analysis with the autophagy inhibitor Bafilomycin A1 and lentiviral depletion of ATG5, indicating that enhanced cytoprotective autophagy partially contributes to increased drug resistance and cell survival. Stable lentiviral BAG3 depletion was associated with a robust down-regulation of Mcl-1, Bcl-2 and Bcl-xL, restoration of drug-induced apoptosis and reduced cell adhesion in these cells, and these death-sensitizing effects could be mimicked with the BAG3/Hsp70 interaction inhibitor YM-1 and by KRIBB11, a selective transcriptional inhibitor of HSF-1. Furthermore, BAG3 depletion was able to revert the EMT-like transcriptional changes observed in BT-549^rDOX²⁰ and MDA-MB-468^r5-FU²⁰⁰⁰ cells. In summary, genetic and pharmacological interference with BAG3 is capable to resensitize TNBC cells to treatment, underscoring its relevance for cell death resistance and as a target to overcome therapy resistance of breast cancer.

Dissecting Time- from Tumor-Related Gene Expression Variability in Bilateral Breast Cancer

Metachronous (MBC) and synchronous bilateral breast tumors (SBC) are mostly distinct primaries, whereas paired primaries and their local recurrences (LRC) share a common origin. Intra-pair gene expression variability in MBC, SBC, and LRC derives from time/tumor microenvironment-related and tumor genetic background-related factors and pairs represents an ideal model for trying to dissect tumor-related from microenvironment-related variability. Pairs of tumors derived from women with SBC (n = 18), MBC (n = 11), and LRC (n = 10) undergoing local-regional treatment were profiled for gene expression; similarity between pairs was measured using an intraclass correlation coefficient (ICC) computed for each gene and compared using analysis of variance (ANOVA). When considering biologically unselected genes, the highest correlations were found for primaries and paired LRC, and the lowest for MBC pairs. By instead limiting the analysis to the breast cancer intrinsic genes, correlations between primaries and paired LRC were enhanced, while lower similarities were observed for SBC and MBC. Focusing on stromal-related genes, the ICC values decreased for MBC and were significantly different from SBC. These findings indicate that it is possible to dissect intra-pair gene expression variability into components that are associated with genetic origin or with time and microenvironment by using specific gene subsets.

Gene network inherent in genomic big data improves the accuracy of prognostic prediction for cancer patients

Accurate prediction of prognosis is critical for therapeutic decisions regarding cancer patients. Many previously developed prognostic scoring systems have limitations in reflecting recent progress in the field of cancer biology such as microarray, next-generation sequencing, and signaling pathways. To develop a new prognostic scoring system for cancer patients, we used mRNA expression and clinical data in various independent breast cancer cohorts (n=1214) from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO). A new prognostic score that reflects gene network inherent in genomic big data was calculated using Network-Regularized high-dimensional Cox-regression (Net-score). We compared its discriminatory power with those of two previously used statistical methods: stepwise variable selection via univariate Cox regression (Uni-score) and Cox regression via Elastic net (Enet-score). The Net scoring system showed better discriminatory power in prediction of disease-specific survival (DSS) than other statistical methods (p=0 in METABRIC training cohort, p=0.000331, 4.58e-06 in two METABRIC validation cohorts) when accuracy was examined by log-rank test. Notably, comparison of C-index and AUC values in receiver operating characteristic analysis at 5 years showed fewer differences between training and validation cohorts with the Net scoring system than other statistical methods, suggesting minimal overfitting. The Net-based scoring system also successfully predicted prognosis in various independent GEO cohorts with high discriminatory power. In conclusion, the Net-based scoring system showed better discriminative power than previous statistical methods in prognostic prediction for breast cancer patients. This new system will mark a new era in prognosis prediction for cancer patients.

TAM receptor tyrosine kinases as emerging targets of innate immune checkpoint blockade for cancer therapy

Cancer immunotherapy utilizing T-cell checkpoint inhibitors has shown tremendous clinical success. Yet, this mode of treatment is effective in only a subset of patients. Unresponsive patients tend to have non-T-cell-inflamed tumors that lack markers associated with the activation of adaptive anti-tumor immune responses. Notably, elimination of cancer cells by T cells is critically dependent on the optimal activity of innate immune cells. Therefore, identifying new targets that regulate innate immune cell function and promote the engagement of adaptive tumoricidal responses is likely to lead to the development of improved therapies against cancer. Here, we review the TAM receptor tyrosine kinases-TYRO3, AXL, and MERTK-as an emerging class of innate immune checkpoints that participate in key steps of anti-tumoral immunity. Namely, TAM-mediated efferocytosis, negative regulation of dendritic cell activity, and dysregulated production of chemokines collectively favor the escape of malignant cells. Hence, disabling TAM signaling may promote engagement of adaptive immunity and complement T-cell checkpoint blockade.

Prognostic and functional role of subtype-specific tumor-stroma interaction in breast cancer

None of the clinically relevant gene expression signatures available for breast cancer were specifically developed to capture the influence of the microenvironment on tumor cells. Here, we attempted to build subtype‐specific signatures derived from an in vitro model reproducing tumor cell modifications after interaction with activated or normal stromal cells. Gene expression signatures derived from HER2+, luminal, and basal breast cancer cell lines (treated by normal fibroblasts or cancer‐associated fibroblasts conditioned media) were evaluated in clinical tumors by in silico analysis on published gene expression profiles (GEPs). Patients were classified as microenvironment‐positive (μENV+ve), that is, with tumors showing molecular profiles suggesting activation by the stroma, or microenvironment‐negative (μENV−ve) based on correlation of their tumors' GEP with the respective subtype‐specific signature. Patients with estrogen receptor alpha (ER)+/HER2−/μENV+ve tumors were characterized by 2.5‐fold higher risk of developing distant metastases (HR = 2.546; 95% CI: 1.751–3.701, P = 9.84E‐07), while μENV status did not affect, or only suggested the risk of distant metastases, in women with HER2+ (HR = 1.541; 95% CI: 0.788–3.012, P = 0.206) or ER‐/HER2− tumors (HR = 1.894; 95% CI: 0.938–3.824; P = 0.0747), respectively. In ER+/HER2− tumors, the μENV status remained significantly associated with metastatic progression (HR = 2.098; CI: 1.214–3.624; P = 0.00791) in multivariable analysis including size, age, and Genomic Grade Index. Validity of our in vitro model was also supported by in vitro biological endpoints such as cell growth (MTT assay) and migration/invasion (Transwell assay). In vitro‐derived gene signatures tracing the bidirectional interaction with cancer activated fibroblasts are subtype‐specific and add independent prognostic information to classical prognostic variables in women with ER+/HER2− tumors.

Effects of ErbB2 Overexpression on the Proteome and ErbB Ligand-specific Phosphosignaling in Mammary Luminal Epithelial Cells

Most breast cancers arise from luminal epithelial cells, and 25–30% of these tumors overexpress the ErbB2/HER2 receptor that correlates with disease progression and poor prognosis. The mechanisms of ErbB2 signaling and the effects of its overexpression are not fully understood. Herein, stable isotope labeling by amino acids in cell culture (SILAC), expression profiling, and phosphopeptide enrichment of a relevant, non-transformed, and immortalized human mammary luminal epithelial cell model were used to profile ErbB2-dependent differences in protein expression and phosphorylation events triggered via EGF receptor (EGF treatment) and ErbB3 (HRG1β treatment) in the context of ErbB2 overexpression. Bioinformatics analysis was used to infer changes in cellular processes and signaling events. We demonstrate the complexity of the responses to oncogene expression and growth factor signaling, and we identify protein changes relevant to ErbB2-dependent altered cellular phenotype, in particular cell cycle progression and hyper-proliferation, reduced adhesion, and enhanced motility. Moreover, we define a novel mechanism by which ErbB signaling suppresses basal interferon signaling that would promote the survival and proliferation of mammary luminal epithelial cells. Numerous novel sites of growth factor-regulated phosphorylation were identified that were enhanced by ErbB2 overexpression, and we putatively link these to altered cell behavior and also highlight the importance of performing parallel protein expression profiling alongside phosphoproteomic analysis.

The metastasis suppressor RARRES3 as an endogenous inhibitor of the immunoproteasome expression in breast cancer cells

In breast cancer metastasis, the dynamic continuum involving pro- and anti-inflammatory regulators can become compromised. Over 600 genes have been implicated in metastasis to bone, lung or brain but how these genes might contribute to perturbation of immune function is poorly understood. To gain insight, we adopted a gene co-expression network approach that draws on the functional parallels between naturally occurring bone marrow-derived mesenchymal stem cells (BM-MSCs) and cancer stem cells (CSCs). Our network analyses indicate a key role for metastasis suppressor RARRES3, including potential to regulate the immunoproteasome (IP), a specialized proteasome induced under inflammatory conditions. Knockdown of RARRES3 in near-normal mammary epithelial and breast cancer cell lines increases overall transcript and protein levels of the IP subunits, but not of their constitutively expressed counterparts. RARRES3 mRNA expression is controlled by interferon regulatory factor IRF1, an inducer of the IP, and is sensitive to depletion of the retinoid-related receptor RORA that regulates various physiological processes including immunity through modulation of gene expression. Collectively, these findings identify a novel regulatory role for RARRES3 as an endogenous inhibitor of IP expression, and contribute to our evolving understanding of potential pathways underlying breast cancer driven immune modulation.

In-depth characterization of breast cancer tumor-promoting cell transcriptome by RNA sequencing and microarrays

Numerous studies have reported the existence of tumor-promoting cells (TPC) with self-renewal potential and a relevant role in drug resistance. However, pathways and modifications involved in the maintenance of such tumor subpopulations are still only partially understood. Sequencing-based approaches offer the opportunity for a detailed study of TPC including their transcriptome modulation. Using microarrays and RNA sequencing approaches, we compared the transcriptional profiles of parental MCF7 breast cancer cells with MCF7-derived TPC (i.e. MCFS). Data were explored using different bioinformatic approaches, and major findings were experimentally validated. The different analytical pipelines (Lifescope and Cufflinks based) yielded similar although not identical results. RNA sequencing data partially overlapped microarray results and displayed a higher dynamic range, although overall the two approaches concordantly predicted pathway modifications. Several biological functions were altered in TPC, ranging from production of inflammatory cytokines (i.e., IL-8 and MCP-1) to proliferation and response to steroid hormones. More than 300 non-coding RNAs were defined as differentially expressed, and 2,471 potential splicing events were identified. A consensus signature of genes up-regulated in TPC was derived and was found to be significantly associated with insensitivity to fulvestrant in a public breast cancer patient dataset. Overall, we obtained a detailed portrait of the transcriptome of a breast cancer TPC line, highlighted the role of non-coding RNAs and differential splicing, and identified a gene signature with a potential as a context-specific biomarker in patients receiving endocrine treatment.

Cytokine profiling of tumor interstitial fluid of the breast and its relationship with lymphocyte infiltration and clinicopathological characteristics

The tumor microenvironment is composed of many immune cell subpopulations and is an important factor in the malignant progression of neoplasms, particularly breast cancer (BC). However, the cytokine networks that coordinate various regulatory events within the BC interstitium remain largely uncharacterized. Moreover, the data obtained regarding the origin of cytokine secretions, the levels of secretion associated with tumor development, and the possible clinical relevance of cytokines remain controversial. Therefore, we profiled 27 cytokines in 78 breast tumor interstitial fluid (TIF) samples, 43 normal interstitial fluid (NIF) samples, and 25 matched serum samples obtained from BC patients with Luminex xMAP multiplex technology. Eleven cytokines exhibited significantly higher levels in the TIF samples compared with the NIF samples: interleukin (IL)-7, IL-10, fibroblast growth factor-2, IL-13, interferon (IFN)γ-inducible protein (IP-10), IL-1 receptor antagonist (IL-1RA), platelet-derived growth factor (PDGF)-β, IL-1β, chemokine ligand 5 (RANTES), vascular endothelial growth factor, and IL-12. An immunohistochemical analysis further demonstrated that IL-1RA, IP-10, IL-10, PDGF-β, RANTES, and VEGF are widely expressed by both cancer cells and tumor-infiltrating lymphocytes (TILs), whereas IP-10 and RANTES were preferentially abundant in triple-negative breast cancers (TNBCs) compared to Luminal A subtype cancers. The latter observation corresponds with the high level of TILs in the TNBC samples. IL-1β, IL-7, IL-10, and PDGFβ also exhibited a correlation between the TIF samples and matched sera. In a survival analysis, high levels of IL-5, a hallmark T_H2 cytokine, in the TIF samples were associated with a worse prognosis. These findings have important implications for BC immunotherapy research.

Integrated gene and miRNA expression analysis of prostate cancer associated fibroblasts supports a prominent role for interleukin-6 in fibroblast activation

Tumor microenvironment coevolves with and simultaneously sustains cancer progression. In prostate carcinoma (PCa), cancer associated fibroblasts (CAF) have been shown to fuel tumor development and metastasis by mutually interacting with tumor cells. Molecular mechanisms leading to activation of CAFs from tissue-resident fibroblasts, circulating bone marrow-derived fibroblast progenitors or mesenchymal stem cells are largely unknown. Through integrated gene and microRNA expression profiling, we showed that PCa-derived CAF transcriptome strictly resembles that of normal fibroblasts stimulated in vitro with interleukin-6 (IL6), thus proving evidence, for the first time, that the cytokine is able per se to induce most of the transcriptional changes characteristic of patient-derived CAFs. Comparison with publicly available datasets, however, suggested that prostate CAFs may be alternatively characterized by IL6 and TGFβ-related signatures, indicating that either signal, depending on the context, may concur to fibroblast activation. Our analyses also highlighted novel pathways potentially relevant for induction of a reactive stroma. In addition, we revealed a role for muscle-specific miR-133b as a soluble factor secreted by activated fibroblasts to support paracrine activation of non-activated fibroblasts or promote tumor progression.

Overall, we provided insights into the molecular mechanisms driving fibroblast activation in PCa, thus contributing to identify novel hits for the development of therapeutic strategies targeting the crucial interplay between tumor cells and their microenvironment.

Subtype-Specific Metagene-Based Prediction of Outcome after Neoadjuvant and Adjuvant Treatment in Breast Cancer

PURPOSE

In spite of improvements of average benefit from adjuvant/neoadjuvant treatments, there are still individual patients with early breast cancer at high risk of relapse. We explored the association with outcome of robust gene cluster-based metagenes linked to proliferation, ER-related genes, and immune response to identify those high-risk patients.

EXPERIMENTAL DESIGN

A total of 3,847 publicly available gene-expression profiles were analyzed (untreated, N = 826; tamoxifen-treated, N = 685; chemotherapy-treated, N = 1,150). Genes poorly performing in formalin-fixed samples were removed. Outcomes of interest were pathologic-complete response (pCR) and distant metastasis-free survival (DMFS). In ER(+)HER2(-), the proliferation and ER-related metagenes were combined to define three risk groups. In HER2(+) and ER(-)HER2(-) risk groups were defined by tertiles of an immune-related metagene.

RESULTS

The high-proliferation/low-ER group of ER(+)HER2(-) breast cancer had significantly higher pCR rate [OR, 5.01 (1.76-17.99), P = 0.005], but poorer outcome [HR = 3.73 (1.63-8.51), P = 0.0018] than the low-proliferation/high-ER. A similar association with outcome applied to patients with residual disease (RD) after neoadjuvant chemotherapy (P = 0.01). In ER(-)HER2(-) and HER2(+) breast cancer, immune metagene in the high tertile was linked to higher pCR [33.7% vs. 11.6% in high and low tertile, respectively; OR, 3.87 (1.79-8.95); P = 0.0009]. In ER(-)HER2(-), after adjuvant/neoadjuvant chemotherapy, 5-year DMFS was 85.4% for high-tertile immune metagene, and 43.9% for low tertile. The outcome association was similar in patients with RD (P = 0.0055). In HER2(+) breast cancer treated with chemotherapy the association with risk of relapse was not significant.

CONCLUSIONS

We developed metagene-based predictors able to define low and high risk of relapse after adjuvant/neoadjuvant therapy. High-risk patients so defined should be preferably considered for trials with investigational agents.

miR-30e* is an independent subtype-specific prognostic marker in breast cancer

Background:

Breast cancer clinical outcome is affected by tumor molecular features, and the identification of subtype-specific prognostic biomarkers is relevant for breast cancer translational research. Gene expression signatures proved to be able to complement prognostic information provided by classical clinico-pathological features. Recently, microRNAs (miRNAs) have been causally linked to tumorigenesis and cancer progression and have been associated with patient outcome, also in breast cancer.

Methods:

MicroRNAs associated with the development of distant metastasis were identified in a cohort of 92 ESR1+/ERBB2− lymph node-negative breast cancers from patients not receiving adjuvant treatment. Results were confirmed and further investigated in a total of 1246 miRNA and gene expression profiles of the Molecular Taxonomy of Breast Cancer International Consortium data set. Moderated t-test, univariable and multivariable Cox regression models were used for statistical analyses.

Results:

miR-30e* was identified as independent protective prognostic factor in lymph node-negative untreated patients with ESR1+/ERBB2− tumours and retained a significant association with a good prognosis in treated patients with the same tumor subtype as well as in the ERBB2+ subtype, but not in ESR1−/ERBB2− tumours.

Conclusions:

We highlighted a relevant and subtype-specific role in breast cancer for miR-30e* and demonstrated that adding miRNA markers to gene signatures and clinico-pathological features can help for a better prognostication.

Serial expression analysis of breast tumors during neoadjuvant chemotherapy reveals changes in cell cycle and immune pathways associated with recurrence and response

INTRODUCTION

The molecular biology involving neoadjuvant chemotherapy (NAC) response is poorly understood. To elucidate the impact of NAC on the breast cancer transcriptome and its association with clinical outcome, we analyzed gene expression data derived from serial tumor samples of patients with breast cancer who received NAC in the I-SPY 1 TRIAL.

METHODS

Expression data were collected before treatment (T1), 24-96 hours after initiation of chemotherapy (T2) and at surgery (TS). Expression levels between T1 and T2 (T1 vs. T2; n = 36) and between T1 and TS (T1 vs. TS; n = 39) were compared. Subtype was assigned using the PAM50 gene signature. Differences in early gene expression changes (T2 - T1) between responders and nonresponders, as defined by residual cancer burden, were evaluated. Cox proportional hazards modeling was used to identify genes in residual tumors associated with recurrence-free survival (RFS). Pathway analysis was performed with Ingenuity software.

RESULTS

When we compared expression profiles at T1 vs. T2 and at T1 vs. TS, we detected significantly altered expression of 150 and 59 transcripts, respectively. We observed notable downregulation of proliferation and immune-related genes at T2. Lower concordance in subtype assignment was observed between T1 and TS (62 %) than between T1 and T2 (75 %). Analysis of early gene expression changes (T2 - T1) revealed that decreased expression of cell cycle inhibitors was associated with poor response. Increased interferon signaling (TS - T1) and high expression of cell proliferation genes in residual tumors (TS) were associated with reduced RFS.

CONCLUSIONS

Serial gene expression analysis revealed candidate immune and proliferation pathways associated with response and recurrence. Larger studies incorporating the approach described here are warranted to identify predictive and prognostic biomarkers in the NAC setting for specific targeted therapies.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT00033397 . Registered 9 Apr 2002.

Use of formalin-fixed paraffin-embedded samples for gene expression studies in breast cancer patients

To obtain gene expression profiles from samples collected in clinical trials, we conducted a pilot study to assess feasibility and estimate sample attrition rates when profiling formalin-fixed, paraffin-embedded specimens. Ten matched fresh-frozen and fixed breast cancer samples were profiled using the Illumina HT-12 and Ref-8 chips, respectively. The profiles obtained with Ref 8, were neither technically nor biologically reliable since they failed to yield the expected separation between estrogen receptor positive and negative samples. With the use of Affymetrix HG-U133 2.0 Plus chips on fixed samples and a quantitative polymerase chain reaction -based sample pre-assessment step, results were satisfactory in terms of biological reliability, despite the low number of present calls (M = 21%±5). Compared with the Illumina DASL WG platform, Affymetrix data showed a wider interquartile range (1.32 vs 0.57, P<2.2 E-16,) and larger fold changes. The Affymetrix chips were used to run a pilot study on 60 fixed breast cancers. By including in the workflow the sample pre-assessment steps, 96% of the samples predicted to give good results (44/46), were in fact rated as satisfactory from the point of view of technical and biological meaningfulness. Our gene expression profiles showed strong agreement with immunohistochemistry data, were able to reproduce breast cancer molecular subtypes, and allowed the validation of an estrogen receptor status classifier derived in frozen samples. The approach is therefore suitable to profile formalin-fixed paraffin-embedded samples collected in clinical trials, provided that quality controls are run both before (sample pre-assessment) and after hybridization on the array.

Molecular portrait of breast cancer in China reveals comprehensive transcriptomic likeness to Caucasian breast cancer and low prevalence of luminal A subtype

The recent dramatic increase in breast cancer incidence across China with progressive urbanization and economic development has signaled the urgent need for molecular and clinical detailing of breast cancer in the Chinese population. Our analyses of a unique transethnic collection of breast cancer frozen specimens from Shanghai Fudan Cancer Center (Chinese Han) profiled simultaneously with an analogous Caucasian Italian series revealed consistent transcriptomic data lacking in batch effects. The prevalence of Luminal A subtype was significantly lower in Chinese series, impacting the overall prevalence of estrogen receptor (ER)-positive disease in a large cohort of Chinese/Caucasian patients. Unsupervised and supervised comparison of gene and microRNA (miRNA) profiles of Chinese and Caucasian samples revealed extensive similarity in the comprehensive taxonomy of transcriptional elements regulating breast cancer biology. Partition of gene expression data using gene lists relevant to breast cancer as "intrinsic" and "extracellular matrix" genes identified Chinese and Caucasian subgroups with equivalent global gene and miRNA profiles. These findings indicate that in the Chinese and Caucasian groups, breast neoplasia and the surrounding stromal characteristics undergo the same differentiation and molecular processes. Transcriptional similarity across transethnic cohorts may simplify translational medicine approaches and clinical management of breast cancer patients worldwide.

The STING pathway and the T cell-inflamed tumor microenvironment

A major subset of patients with advanced solid tumors show a spontaneous T cell-inflamed tumor microenvironment, which has prognostic import and is associated with clinical response to immunotherapies. As such, understanding the mechanisms governing the generation of spontaneous T cell responses in only a subset of patients is critical for advancing immunotherapeutic approaches further. Here, we discuss the characteristics of T cell-inflamed versus non-inflamed tumors, including a type I interferon (IFN) signature associated with T cell priming against tumor antigens. We review recent findings that have pointed towards the STING (stimulator of interferon genes) pathway of cytosolic DNA sensing as an important innate immune sensing mechanism driving type I IFN production in the tumor context. Knowledge of this pathway is guiding the further development of novel immunotherapeutic strategies.

Subtype-dependent prognostic relevance of an interferon-induced pathway metagene in node-negative breast cancer

The majority of gene expression signatures developed to predict the likelihood to relapse in breast cancer (BC) patients assigns a high risk score to patients with Estrogen Receptor (ER) negative or highly proliferating tumors. We aimed to identify a signature of differentially expressed (DE) metagenes, rather than single DE genes, associated with distant metastases beyond classical risk factors. We used 105 gene expression profiles from consecutive BCs to identify metagenes whose prognostic role was defined on an independent series of 92 ESR1+/ERBB2- node-negative BCs (42 cases developing metastases within 5 years from diagnosis and 50 cases metastasis-free for more than 5 years, comparable for age, tumor size, ER status and surgery). Findings were validated on publicly available datasets of 684 node-negative BCs including all the subtypes. Only a metagene containing interferon-induced genes (IFN metagene) proved to be predictive of distant metastasis in our series of patients with ESR1+/ERBB2- tumors (P = 0.029), and such a finding was validated on 457 ESR1+/ERBB2- BCs from public datasets (P = 0.0424). Conversely, the IFN metagene was associated with a low risk of metastasis in 104 ERBB2+ tumors (P = 0.0099) whereas it did not prove to significantly affect prognosis in 123 ESR1-/ERBB2- tumors (P = 0.2235). A complex prognostic interaction was revealed in ESR1+/ERBB2- and ERBB2+ tumors when the association between the IFN metagene and a T-cell metagene was considered. The study confirms the importance of analyzing prognostic variables separately within BC subtypes, highlights the advantages of using metagenes rather than genes, and finally identifies in node-negative ESR1+/ERBB2- BCs, the unfavorable role of high IFN metagene expression.