Molecular anatomy of breast cancer stroma and its prognostic value in estrogen receptor-positive and -negative cancers

Breast cancers with high proliferation and low ER-related signalling have poor prognosis and unique molecular features with implications for therapy

BACKGROUND

Luminal breast cancers with high proliferation (MKShi) and low ER-related signalling (ERSlo) have a poor prognosis. We investigated treatment responses and molecular features of MKShi/ERSlo tumours to inform potential therapies.

METHODS

Gene expression data from patients who received neoadjuvant chemotherapy (NAC) without (MDACC, N = 199) or with pembrolizumab (I-SPY2, N = 40), or endocrine therapy (NET) without (POETIC, N = 172) or with palbociclib (NeoPalAna, N = 32) were analyzed to assess treatment response by MKS/ERS-subgroups. TCGA was used to assess the mutational landscape and biomarkers associated with palbociclib-resistance (Cyclin-E, RBsig, IRPR) and immunotherapy-response (TMB, TILs, T-cell inflamed) by MKS/ERS-subgroups.

RESULTS

Compared to MKShi/ERShi tumours, MKShi/ERSlo tumours had higher pathological response rates to NAC (22% vs 8%, p = 0.06) but a higher recurrence risk (4-year metastasis-free survival 70% vs 94%, p = 0.01). MKShi/ERSlo tumours frequently harboured TP53 (34%) and PIK3CA (33%) mutations, and showed high expression of Cyclin-E, RBsig and IRPR, high TMB and elevated TIL and T-cell inflamed metagene expression. MKShi/ERSlo tumours retained high proliferation after NET with or without palbociclib but had higher pathological complete response rates when pembrolizumab was added to NAC (42% vs 21%, p = 0.07).

CONCLUSIONS

MKShi/ERSlo tumours have dismal outcomes and are enriched in chemotherapy-sensitive but ET- and palbociclib-resistant tumours. Biomarker analysis and clinical data suggest a potential role for immunotherapy in this group.

Defined extracellular matrix compositions support stiffness-insensitive cell spreading and adhesion signaling

Integrin-dependent adhesion to the extracellular matrix (ECM) mediates mechanosensing and signaling in response to altered microenvironmental conditions. In order to provide tissue- and organ-specific cues, the ECM is composed of many different proteins that temper the mechanical properties and provide the necessary structural diversity. Despite most human tissues being soft, the prevailing view from predominantly in vitro studies is that increased stiffness triggers effective cell spreading and activation of mechanosensitive signaling pathways. To address the functional coupling of ECM composition and matrix rigidity on compliant substrates, we developed a matrix spot array system to screen cell phenotypes against different ECM mixtures on defined substrate stiffnesses at high resolution. We applied this system to both cancer and normal cells and surprisingly identified ECM mixtures that support stiffness-insensitive cell spreading on soft substrates. Employing the motor-clutch model to simulate cell adhesion on biochemically distinct soft substrates, with varying numbers of available ECM-integrin-cytoskeleton (clutch) connections, we identified conditions in which spreading would be supported on soft matrices. Combining simulations and experiments, we show that cell spreading on soft is supported by increased clutch engagement on specific ECM mixtures and even augmented by the partial inhibition of actomyosin contractility. Thus, "stiff-like" spreading on soft is determined by a balance of a cell's contractile and adhesive machinery. This provides a fundamental perspective for in vitro mechanobiology studies, identifying a mechanism through which cells spread, function, and signal effectively on soft substrates.

Prognostic Impact of CD38- and IgκC-Positive Tumor-Infiltrating Plasma Cells in Triple-Negative Breast Cancer

Due to a higher mutational load, triple-negative breast cancer (TNBC) is characterized by a higher immunogenicity compared to other subtypes. In this context, we analyzed the prognostic significance of tumor-infiltrating plasma cells in a cohort of 107 triple-negative breast cancer patients. Tumor-infiltrating plasma cells were analyzed via immunohistochemistry using the plasma cell markers CD38 and IgκC. The prognostic impact of the CD38 and IgκC expression was evaluated using the Kaplan-Meier plots and Cox regression analyses. A Spearman-Rho correlation coefficient was used to evaluate a possible association between plasma cell infiltration and the BRCA mutation status. The study cohort consisted of 107 patients with early-stage TNBC, who were treated between 2009 and 2016 at the Department of Gynecology and Obstetrics, University Medical Center Mainz, Germany. The median follow-up was five years. The Kaplan-Meier survival analysis showed that higher tumor infiltration with CD38-positive plasma cells was associated with significantly longer metastasis-free survival (MFS) (p = 0.039 Log Rank). In the multivariate Cox regression analysis for metastasis-free survival, in which additional clinicopathological factors (age, tumor size, nodal status, and grading) were considered, CD38 was identified as an independent prognostic factor within the analyzed cohort (HR 0.438, 95% CI 0.195-0.983; p = 0.045). In addition to the CD38 expression, the nodal status was also identified as an independent prognostic factor in multivariate Cox regression. Regarding the IgκC expression, a higher IgκC expression was shown to be associated with a better outcome, although this effect was not statistically significant. Furthermore, we were able to show a significant correlation between plasma cell infiltration and the BRCA mutation status. A favorable prognostic significance of tumor-infiltrating plasma cells could be demonstrated in triple-negative breast cancer immunohistochemically analyzed for the CD38 and IgκC expression. CD38 was identified as an independent prognostic factor via multivariate Cox regression.

Construction of a prognostic model for triple-negative breast cancer based on immune-related genes, and associations between the tumor immune microenvironment and immunological therapy

BACKGROUND

Triple-negative breast cancer (TNBC) is the subtype of breast cancer with the worst prognosis, and it is highly heterogeneous. There is growing evidence that the tumor immune microenvironment (TIME) plays a crucial role in tumor development, maintenance, and treatment responses. Notably however, the full effects of the TIME on prognosis, TIME characteristics, and immunotherapy responses in TNBC patients have not been fully elucidated.

METHODS

Gene Expression Omnibus and The Cancer Genome Atlas data were used to data analysis. Single-cell sequencing and tissue microarray analysis were used to investigate gene expression. The concentrations and distributions of immune cell types were determined and analyzed using the CIBERSORT strategy. Tumor immune dysfunction and exclusion score and the IMvigor210 cohort were used to estimate the sensitivity of TNBC patients with different prognostic statuses to immune checkpoint treatment.

RESULTS

Five immune-related genes associated with TNBC prognosis (IL6ST, NR2F1, CKLF, TCF7L2, and HSPA2) was identified and a prognostic evaluation model was constructed based on those genes. The respective areas under the curve of the prognostic nomogram model at 3 and 5 years were 0.791 and 0.859. The group with a lower nomogram score, with a better prognosis survival status and clinical treatment benefit rate.

CONCLUSION

A prognostic model for TNBC that was closely related to the immune landscape and therapeutic responses was constructed. This model may help clinicians to make more precise and personalized treatment decisions pertaining to TNBC patients.

The PD-1 single-nucleotide polymorphism rs11568821 and rs2227981 as a novel prognosis model in a triple-negative breast cancer patient

INTRODUCTION

The aim of the study is to determine the relationship between polymorphisms rs11568821 C/T and at rs2227981 G/A in the programmed cell death 1 gene (PDCD1) and the clinicopathologic characteristics of triple negative breast cancer patient (TNBC).

MATERIAL AND METHODS

The study included 30 TNBC patients and 30 healthy controls. Genotyping was performed with allelic discrimination using PCR with TaqMan SNP Genotyping Assays.

RESULTS

The presence of CC/CT in rs11568821and GG/AG in rs2227981 were not associated with the risk of progression of TNBC. The correlation between rs11568821 minor allele distribution and risk of TNBC has borderline significance (p = 0.0619). The rs2227981 polymorphism has a significant association with grade G (G3, p = 0.0229). There was a trend toward significance (p = 0.063448) in the minor allele presentation and Ki67 > 20% for rs2227981. Other clinical features (e.g. age, TNM stage) did not significantly correlate with the rs11568821 or the rs2227981 polymorphism.

CONCLUSION

rs2227981 is associated with grading; hence PDCD1 can be used as a prognostic marker in TNBC.

Combining the guidelines and multiphoton imaging methods to improve the prognostic value of tumor-infiltrating lymphocytes in breast cancer

Multiphoton microscopy (MPM) was introduced to label-freely obtain tumor-infiltrating lymphocytes (TILs) images from a total of 611 patients, and the prognostic value of TILs in breast cancer was assessed by the MPM method (TILs-MPM) and guidelines method proposed by the International Immuno-Oncology Biomarker Working Group (TILs-WG), respectively. Moreover, the clinical (CLI) model, TILs-WG + TILs-MPM model, and full model (CLI + TILs-WG + TILs-MPM) were developed to investigate the prognostic value of TILs. The results show that TILs-WG performs better in estrogen receptor (ER)-negative subgroup, and TILs-MPM is comparable with TILs-WG in the ER-negative subgroup, but has the best performance in the ER-positive subgroup. Furthermore, the TILs-WG + TILs-MPM model can significantly improve the prognostic power compared with the TILs-WG model, and the full model has excellent performance, with high area under the curve (AUC) and hazard ratio (HR) in both ER-positive, ER-negative subgroups, and the complete cohort. Our results suggest that the combination of TILs-WG with TILs-MPM model can greatly improve the prognostic value of TILs.

Chromatin Remodeling Enzyme Cluster Predicts Prognosis and Clinical Benefit of Therapeutic Strategy in Breast Cancer

The treatment provided for breast cancer depends on the expression of hormone receptors, human epidermal growth factor receptor-2 (HER2), and cancer staging. Surgical intervention, along with chemotherapy or radiation therapy, is the mainstay of treatment. Currently, precision medicine has led to personalized treatment using reliable biomarkers for the heterogeneity of breast cancer. Recent studies have shown that epigenetic modifications contribute to tumorigenesis through alterations in the expression of tumor suppressor genes. Our aim was to investigate the role of epigenetic modifications in genes involved in breast cancer. A total of 486 patients from The Cancer Genome Atlas Pan-cancer BRCA project were enrolled in our study. Hierarchical agglomerative clustering analysis further divided the 31 candidate genes into 2 clusters according to the optimal number. Kaplan–Meier plots showed worse progression-free survival (PFS) in the high-risk group of gene cluster 1 (GC1). In addition, the high-risk group showed worse PFS in GC1 with lymph node invasion, which also presented a trend of better PFS when chemotherapy was combined with radiotherapy than when chemotherapy was administered alone. In conclusion, we developed a novel panel using hierarchical clustering that high-risk groups of GC1 may be promising predictive biomarkers in the clinical treatment of patients with breast cancer.

A Comprehensive Landscape of Imaging Feature-Associated RNA Expression Profiles in Human Breast Tissue

The expression abundance of transcripts in nondiseased breast tissue varies among individuals. The association study of genotypes and imaging phenotypes may help us to understand this individual variation. Since existing reports mainly focus on tumors or lesion areas, the heterogeneity of pathological image features and their correlations with RNA expression profiles for nondiseased tissue are not clear. The aim of this study is to discover the association between the nucleus features and the transcriptome-wide RNAs. We analyzed both microscopic histology images and RNA-sequencing data of 456 breast tissues from the Genotype-Tissue Expression (GTEx) project and constructed an automatic computational framework. We classified all samples into four clusters based on their nucleus morphological features and discovered feature-specific gene sets. The biological pathway analysis was performed on each gene set. The proposed framework evaluates the morphological characteristics of the cell nucleus quantitatively and identifies the associated genes. We found image features that capture population variation in breast tissue associated with RNA expressions, suggesting that the variation in expression pattern affects population variation in the morphological traits of breast tissue. This study provides a comprehensive transcriptome-wide view of imaging-feature-specific RNA expression for healthy breast tissue. Such a framework could also be used for understanding the connection between RNA expression and morphology in other tissues and organs. Pathway analysis indicated that the gene sets we identified were involved in specific biological processes, such as immune processes.

Modification of Breast Cancer Milieu with Chemotherapy plus Dendritic Cell Vaccine: An Approach to Select Best Therapeutic Strategies

BACKGROUND

The addition of dendritic cell vaccines (DCV) to NAC could induce immune responses in those patients with residual disease (RD) by transforming the tumor microenvironment.

METHODS

Core diagnostic biopsies and surgical specimens from 80 patients (38 in the vaccinated group plus NAC (VG) and 42 in the control group (CG, treated only with NAC) were selected. We quantify TILs (CD8, CD4 and CD45RO) using immunohistochemistry and the automated cellular imaging system (ACIS III) in paired samples.

RESULTS

A CD8 rise in TNBC samples was observed after NAC plus DCV, changing from 4.48% in the biopsy to 6.70% in the surgical specimen, not reaching statistically significant differences (p = 0.11). This enrichment was seen in up to 67% of TNBC patients in the experimental arm as compared with the CG (20%). An association between CD8 TILs before NAC (4% cut-off point) and pathological complete response in the VG was found in the univariate and multivariate analysis (OR = 1.41, IC95% 1.05-1.90; p = 0.02, and OR = 2.0, IC95% 1.05-3.9; p = 0.03, respectively).

CONCLUSION

Our findings suggest that patients with TNBC could benefit from the stimulation of the antitumor immune system by using DCV together with NAC.

Facts and Perspectives: Implications of tumor glycolysis on immunotherapy response in triple negative breast cancer

Triple negative breast cancer (TNBC) is an aggressive disease that is difficult to treat and portends a poor prognosis in many patients. Recent efforts to implement immune checkpoint inhibitors into the treatment landscape of TNBC have led to improved outcomes in a subset of patients both in the early stage and metastatic settings. However, a large portion of patients with TNBC remain resistant to immune checkpoint inhibitors and have limited treatment options beyond cytotoxic chemotherapy. The interplay between the anti-tumor immune response and tumor metabolism contributes to immunotherapy response in the preclinical setting, and likely in the clinical setting as well. Specifically, tumor glycolysis and lactate production influence the tumor immune microenvironment through creation of metabolic competition with infiltrating immune cells, which impacts response to immune checkpoint blockade. In this review, we will focus on how glucose metabolism within TNBC tumors influences the response to immune checkpoint blockade and potential ways of harnessing this information to improve clinical outcomes.

Predictive value of immune genomic signatures from breast cancer cohorts containing data for both response to neoadjuvant chemotherapy and prognosis after surgery

BACKGROUND

Previous studies of immune genomic signatures (IGSs) in breast cancer have attempted to predict the response to chemotherapy or prognosis and were performed using different patient cohorts. The purpose of this study was to evaluate the predictive functions of various IGSs using the same patient cohort that included data for response to chemotherapy as well as the prognosis after surgery.

METHODS

We applied five previously described IGS models in a public dataset of 508 breast cancer patients treated with neoadjuvant chemotherapy. The prognostic and predictive values of each model were evaluated, and their correlations were compared.

RESULTS

We observed a high proportion of expression concordance among the IGS models (r: 0.56-1). Higher scores of IGSs were detected in aggressive breast cancer subtypes (basal and HER2-enriched) (P < 0.001). Four of the five IGSs could predict chemotherapy responses and two could predict 5-year relapse-free survival in cases with hormone receptor-positive (HR +) tumors. However, the models showed no significant differences in their predictive abilities for hormone receptor-negative (HR-) tumors.

CONCLUSIONS

IGSs are, to some extent, useful for predicting prognosis and chemotherapy response; moreover, they show substantial agreement for specific breast cancer subtypes. However, it is necessary to identify more compelling biomarkers for both prognosis and response to chemotherapy in HR- and HER2 + cases.

Identification of a 5-gene-risk score model for predicting luminal A-invasive lobular breast cancer survival

Breast cancer is a devastating malignancy, among which the luminal A (LumA) breast cancer is the most common subtype. In the present study, we used a comprehensive bioinformatics approach in the hope of identifying novel prognostic biomarkers for LumA breast cancer patients. Transcriptomic profiling of 611 LumA breast cancer patients was downloaded from TCGA database. Differentially expressed genes (DEGs) between tumor samples and controls were first identified by differential expression analysis, before being used for the weighted gene co-expression network analysis. The subsequent univariate Cox regression and LASSO algorithm were used to uncover key prognostic genes for constructing multivariate Cox regression model. Patients were stratified into high-risk and low-risk groups according to the risk score, and subjected to multiple downstream analyses including survival analysis, gene set enrichment analysis (GSEA), inference on immune cell infiltration and analysis of mutation burden. Receiving operator curve analysis was also performed. A total of 7071 DEGs were first identified by edgeR package, pink module was found significantly associated with invasive lobular carcinoma (ILC). 105 prognostic genes and 9 predictors were identified, allowing the identification of a 5-key prognostic genes (LRRC77P, CA3, BAMBI, CABP1, ATP8A2) after intersection. These 5 genes, and the resulting Cox model, displayed good prognostic performance. Furthermore, distinct differences existed between two risk-score stratified groups at various levels. The identified 5-gene prognostic model will help deepen the understanding of the molecular and immunological mechanisms that affect the survival of LumA-ILC patients and guide and proper monitoring of these patients.

The Multi-Omic Landscape of Primary Breast Tumors and Their Metastases: Expanding the Efficacy of Actionable Therapeutic Targets

Breast cancer (BC) mortality is almost exclusively due to metastasis, which is the least understood aspect of cancer biology and represents a significant clinical challenge. Although we have witnessed tremendous advancements in the treatment for metastatic breast cancer (mBC), treatment resistance inevitably occurs in most patients. Recently, efforts in characterizing mBC revealed distinctive genomic, epigenomic and transcriptomic (multi-omic) landscapes to that of the primary tumor. Understanding of the molecular underpinnings of mBC is key to understanding resistance to therapy and the development of novel treatment options. This review summarizes the differential molecular landscapes of BC and mBC, provides insights into the genomic heterogeneity of mBC and highlights the therapeutically relevant, multi-omic features that may serve as novel therapeutic targets for mBC patients.

PD-L1 protein expression in relation to recurrence score values in early-stage ER + breast cancer

PURPOSE

We assessed associations between PD-L1 protein expression, RS, tumor grade, and stromal tumor-infiltrating lymphocyte (TIL) count in early-stage ER + cancers.

METHODS

FFPE tissue blocks of 213 patients with RS in 2012-2017 were identified. PD-L1 immunohistochemistry was performed with SP142 assay, cases with ≥ 1% tumor-infiltrating immune cell positivity in the tumor area were considered PD-L1 + . TIL scores were determined following the international TIL counting guidelines. PD-L1 expression positivity rates were compared across RS (< 11, 11-25, > 25) and TIL categories (< 10%, 10-29%, > 30%), and tumor grade using Wilcoxon and Chi-square tests. Multivariate analysis was performed using logistic regression.

RESULTS

PD-L1 and TIL results were available for 201 and 203 patients. Overall, 53% of cases were PD-L1 +. PD-L1 expression was higher among cases with RS > 25, versus RS < 11 (p = 0.00019) and RS 11-25 (p = 0.0017). PD-L1 positivity also correlated with TIL score, tumor grade, and tumor size. Among cancers with TIL > 30%, 92% were PD-L1 + versus 44% PD-L1 + among TIL < 10% (p = 2.8 × 10^-6). Grade 3 cancers had higher PD-L1 positivity (79% PD-L1 +) versus grade 2 (49% PD-L1 +) or 1 tumors (48% PD-L1 +) (p = 0.00047). T2 and T3 tumors had more frequent PD-L1 positivity (67% and 83%, respectively) versus T1 cancers (46%) (p = 0.008). In multivariate analysis, only TIL and RS remained as independent predictors of PD-L1 positivity.

CONCLUSION

PD-L1 expression is significantly more frequent and higher in larger tumors (T2, T3), grade 3 cancers, and in cancers with RS > 25. PD-L1 expression also correlates with TIL score.

Tumor immune microenvironment of self-identified African American and non-African American triple negative breast cancer

Differences in the tumor immune microenvironment may result in differences in prognosis and response to treatment in cancer patients. We hypothesized that differences in the tumor immune microenvironment may exist between African American (AA) and NonAA patients, due to ancestry-related or socioeconomic factors, that may partially explain differences in clinical outcomes. We analyzed clinically matched triple-negative breast cancer (TNBC) tissues from self-identified AA and NonAA patients and found that stromal TILs, PD-L1 IHC-positivity, mRNA expression of immune-related pathways, and immunotherapy response predictive signatures were significantly higher in AA samples (p < 0.05; Fisher's Exact Test, Mann-Whitney Test, Permutation Test). Cancer biology and metabolism pathways, TAM-M2, and Immune Exclusion were significantly higher in NonAA samples (p < 0.05; Permutation Test, Mann-Whitney Test). There were no differences in somatic tumor mutation burden. Overall, there is greater immune infiltration and inflammation in AA TNBC and these differences may impact response to immune checkpoint inhibitors and other therapeutic agents that modulate the immune microenvironment.

Can granulysin provide prognostic value in primary breast cancer?

BACKGROUND

Granulysin (GNLY) is a cytolytic and proinflammatory molecule which also acts as an immune alarmin. The multifunctional nature of this molecule has made it challenging to define its full potential as a biomarker in breast cancer.

AIM

To evaluate the prognostic value of intratumoral GNLY in primary breast cancer patients and its association with established clinicopathological parameters.

PATIENTS AND METHODS

The study included 69 node-negative breast cancer patients with known clinicopathological parameters, all of whom had not received any prior hormonal or chemotherapeutic systemic therapy that would interfere with the course of disease. The median follow-up period was 144 months. Steroid hormone receptor status was determined by ligand-binding assay and HER2 status by chromogenic in situ hybridisation (CISH). Intratumoral GNLY mRNA levels were determined by RT-qPCR. Prognostic performance was evaluated by the receiver operating characteristic (ROC), Cox proportional hazards regression and Kaplan-Meier analysis. Classification of patients into GNLY^low and GNLY^high subgroups was performed by the use of the outcome-oriented cut-off point categorisation approach.

RESULTS

There was a significant difference between GNLY values of patients without any recurrences and those with local or distant recurrences (Mann-Whitney test, p = 0.05 and p = 0.02, respectively). None of the tested parameters showed prognostic significance for local and distant recurrences when combined. When distant metastases and local recurrences were separated as events, the best prognostic performance was observed for GNLY as compared with any clinicopathological parameter (AUC=0.24 and p = 0.04 for local events; AUC=0.71 and p = 0.03 for distant events). Local recurrence incidence was 0% for the GNLY^high subgroup and 19% for the GNLY^low subgroup; however distant recurrence incidence was 24% for the GNLY^high subgroup but only 3% for the GNLY^low subgroup (Kaplan-Meier analysis). A significant positive correlation was found between intratumoral ER and GNLY levels, and a significant negative correlation between tumour grade and GNLY levels.

CONCLUSION

High levels of granulysin prognosticate low risk of local recurrence but a high risk of distant metastasis in primary, untreated, breast cancer patients.

B Cell Function in the Tumor Microenvironment

The tumor microenvironment (TME) is a heterogeneous, complex organization composed of tumor, stroma, and endothelial cells that is characterized by cross talk between tumor and innate and adaptive immune cells. Over the last decade, it has become increasingly clear that the immune cells in the TME play a critical role in controlling or promoting tumor growth. The function of T lymphocytes in this process has been well characterized. On the other hand, the function of B lymphocytes is less clear, although recent data from our group and others have strongly indicated a critical role for B cells in antitumor immunity. There are, however, a multitude of populations of B cells found within the TME, ranging from naive B cells all the way to terminally differentiated plasma cells and memory B cells. Here, we characterize the role of B cells in the TME in both animal models and patients, with an emphasis on dissecting how B cell heterogeneity contributes to the immune response to cancer.

Identification of molecular subtypes and a novel prognostic model of diffuse large B-cell lymphoma based on a metabolism-associated gene signature

Background

Diffuse large B cell lymphoma (DLBCL) is the most common lymphoma in adults. Metabolic reprogramming in tumors is closely related to the immune microenvironment. This study aimed to explore the interactions between metabolism-associated genes (MAGs) and DLBCL prognosis and their potential associations with the immune microenvironment.

Methods

Gene expression and clinical data on DLBCL patients were obtained from the GEO database. Metabolism-associated molecular subtypes were identified by consensus clustering. A prognostic risk model containing 14 MAGs was established using Lasso-Cox regression in the GEO training cohort. It was then validated in the GEO internal testing cohort and TCGA external validation cohort. GO, KEGG and GSVA were used to explore the differences in enriched pathways between high- and low-risk groups. ESTIMATE, CIBERSORT, and ssGSEA analyses were used to assess the immune microenvironment. Finally, WGCNA analysis was used to identify two hub genes among the 14 model MAGs, and they were preliminarily verified in our tissue microarray (TMA) using multiple fluorescence immunohistochemistry (mIHC).

Results

Consensus clustering divided DLBCL patients into two metabolic subtypes with significant differences in prognosis and the immune microenvironment. Poor prognosis was associated with an immunosuppressive microenvironment. A prognostic risk model was constructed based on 14 MAGs and it was used to classify the patients into two risk groups; the high-risk group had poorer prognosis and an immunosuppressive microenvironment characterized by low immune score, low immune status, high abundance of immunosuppressive cells, and high expression of immune checkpoints. Cox regression, ROC curve analysis, and a nomogram indicated that the risk model was an independent prognostic factor and had a better prognostic value than the International Prognostic Index (IPI) score. The risk model underwent multiple validations and the verification of the two hub genes in TMA indicated consistent results with the bioinformatics analyses.

Conclusions

The molecular subtypes and a risk model based on MAGs proposed in our study are both promising prognostic classifications in DLBCL, which may provide novel insights for developing accurate targeted cancer therapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03393-9.

Immune-Based Therapy in Triple-Negative Breast Cancer: From Molecular Biology to Clinical Practice

Triple-negative breast cancer (TNBC) has been considered for many years an orphan disease in terms of therapeutic options, with conventional chemotherapy (CT) still representing the mainstay of treatment in the majority of patients. Although breast cancer (BC) has been historically considered a "cold tumor", exciting progress in the genomic field leading to the characterization of the molecular portrait and the immune profile of TNBC has opened the door to novel therapeutic strategies, including Immune Checkpoint Inhibitors (ICIs), Poly ADP-Ribose Polymerase (PARP) inhibitors and Antibody Drug Conjugates (ADCs). In particular, compared to standard CT, the immune-based approach has been demonstrated to improve progression-free survival (PFS) and overall survival (OS) in metastatic PD-L1-positive TNBC and the pathological complete response rate in the early setting, regardless of PD-L1 expression. To date, PD-L1 has been widely used as a predictor of the response to ICIs; however, many patients do not benefit from the addition of immunotherapy. Therefore, PD-L1 is not a reliable predictive biomarker of the response, and its accuracy remains controversial due to the lack of a consensus about the assay, the antibody, and the scoring system to adopt, as well as the spatial and temporal heterogeneity of the PD-L1 status. In the precision medicine era, there is an urgent need to identify more sensitive biomarkers in the BC immune oncology field other than just PD-L1 expression. Through the characterization of the tumor microenvironment (TME), the analysis of peripheral blood and the evaluation of immune gene signatures, novel potential biomarkers have been explored, such as the Tumor Mutational Burden (TMB), Microsatellite Instability/Mismatch Repair Deficiency (MSI/dMMR) status, genomic and epigenomic alterations and tumor-infiltrating lymphocytes (TILs). This review aims to summarize the recent knowledge on BC immunograms and on the biomarkers proposed to support ICI-based therapy in TNBC, as well as to provide an overview of the potential strategies to enhance the immune response in order to overcome the mechanisms of resistance.

A Novel IGLC2 Gene Linked With Prognosis of Triple-Negative Breast Cancer

Background

Immunoglobulin-related genes are associated with the favorable prognosis of triple-negative breast cancer (TNBC) patients. We aimed to analyze the function and prognostic value of immunoglobulin lambda constant 2 (IGLC2) in TNBC patients.

Methods

We knocked down the gene expression of IGLC2 (IGLC2-KD) in MDA-MB-231 cells to evaluate the proliferation, migration, and invasion of tumors via 3-(4,5-Dimethythiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay, wound healing, and transwell cell migration assay respectively. Relapse-free survival (RFS) and distant metastasis-free survival (DMFS) analyses were conducted using the KM plotter online tool. The GSE76275 data set was used to analyze the association of IGLC2 and clinical characteristics. A pathway enrichment analysis was conducted using the next-generation sequencing data of wild-type and IGLC2-KD MDA-MB-231 cells.

Results

The low gene expression of IGLC2 was related to unfavorable RFS, DMFS. The high expression of IGLC2 was exhibited in the basal-like immune-activated (BLIA) TNBC molecular subtype, which was immune-activated and showed excellent response to immune therapy. IGLC2 was positively correlated with programmed death-ligand 1 (PD-L1) as shown by Spearman correlation (r = 0.25, p < 0.0001). IGLC2 had a strong prognostic effect on lymph node-negative TNBC (RFS range: 0.31, q value= 8.2e-05; DMFS = 0.16, q value = 8.2e-05) but had no significance on lymph node-positive ones. The shRNA-mediated silencing of IGLC2 increased the proliferation, migration, and invasion of MDA-MB-231 cells. The results of pathway enrichment analysis showed that IGLC2 is related to the PI3K-Akt signaling pathway, MAPK signaling pathway, and extracellular matrix–receptor interaction. We confirmed that MDA-MB-231 tumor cells expressed IGLC2, subverting the traditional finding of generation by immune cells.

Conclusions

IGLC2 linked with the proliferation, migration, and invasion of MDA-MB-231 cells. A high expression of IGLC2 was related to favorable prognosis for TNBC patients. IGLC2 may serve as a biomarker for the identification of TNBC patients who can benefit the most from immune checkpoint blockade treatment.

Gene Expression Profiling in Early Breast Cancer-Patient Stratification Based on Molecular and Tumor Microenvironment Features

Patients with early-stage hormone receptor-positive, human epidermal growth factor receptor 2-negative (HER2−) breast cancer (BC) are typically treated with surgery, followed by adjuvant systemic endocrine therapy with or without adjuvant chemotherapy and radiation therapy. Current guidelines regarding the use of adjuvant systemic therapy depend on clinical and pathological factors, such as the morphological assessment of tumor subtype; histological grade; tumor size; lymphovascular invasion; and lymph node status combined with estrogen receptor, progesterone receptor, and HER2 biomarker profiles assessed using immunohistochemistry and in situ hybridization. Additionally, the prognostic and predictive value of tumor-infiltrating lymphocytes and their composition is emerging as a key marker in triple negative (TNBC) and HER2-enriched molecular breast tumor subtypes. However, all these factors do not necessarily reflect the molecular heterogeneity and complexity of breast cancer. In the last two decades, gene expression signatures or profiling (GEP) tests have been developed to predict the risk of disease recurrence and estimate the potential benefit of receiving adjuvant systemic chemotherapy in patients with luminal breast cancer. GEPs have been utilized to help physicians to refine decision-making process, complementing clinicopathological parameters, and can now be used to classify the risk of recurrence and tailoring personalized treatments. Several clinical trials using GEPs validate the increasing value of such assays in different clinical settings, addressing relevant clinical endpoints. Finally, the recent approval of immune checkpoint inhibitors in TNBC and the increasing use of immunotherapy in different molecular BC populations highlight the opportunity to refine current GEPs by including a variety of immune-related genes that may help to improve predicting drug response and finetune prognosis.

Cross-Platform in-silico Analyses Exploring Tumor Immune Microenvironment with Prognostic Value in Triple-Negative Breast Cancer

INTRODUCTION

Only a proportion of triple-negative breast cancer (TNBC) is immunotherapy-responsive. We hypothesized that the tumor microenvironment (TME) influences the outcomes of TNBC and investigated the relevant signaling pathways.

MATERIALS AND METHODS

Immune score (IS) and stromal score (SS) were calculated using the ESTIMATE and correlated with the overall survival (OS) in TNBC. RNA-seq data from 115 TNBC samples and 112 normal adjacent tissues were retrieved. Validations in the methylation levels in 10 TNBC and five non-TNBC cell lines were obtained. Cox model overall survival (OS) validated the derived transcription factor (TF) genes in cBioPortal breast cancer patients.

RESULTS

SS-low predicts a higher OS compared with SS-high patients (P = 0.0081 IS-high/SS-low patients had better OS (P = 0.045) than IS-low/SS-high patients. More macrophages were polarized to the M2 state in patients with IS-low/SS-high patients (P < 0.001). Moreover, CIBERSORTx showed more CD8+ cytotoxic T-cells in IS-high/SS-low patients (p = 0.0286) and more resting NK cells in the IS-low/SS-high TME (P = 0.0108). KEGG pathway analysis revealed that overexpressed genes were enriched in the IL-17 and cytokine-cytokine receptor interaction pathways. The lncRNA DRAIC, a tumor suppressor, was consistently deactivated in the 10 TNBC cell lines. On the cBioPortal platform, we validated that 13% of ER-negative, HER2-unamplified BC harbored IL17RA deep deletion and 25% harbored TRAF3IP2 amplification. On cBioPortal datasets, the nine altered TF genes derived from the X2K analysis showed significantly worse relapse-free survival in 2377 patients and OS in 4819 invasive BC patients than in the unaltered cohort.

CONCLUSION

Of note, the results of this integrated in silico study can only be generalized to approximately 17% of patients with TNBC, in which infiltrating stromal cells and immune cells play a determinant prognostic role.

Combined mRNAs and clinical factors model on predicting prognosis in patients with triple-negative breast cancer

OBJECTIVE

Triple-negative breast cancer (TNBC) is aggressive cancer usually diagnosed in young women with no effective prognosis prediction model to use. The present study was performed to develop a useful prognostic model for predicting overall survival (OS) for TNBC patients.

METHODS

The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases were used as training and validation data sets, respectively, in which the gene expression levels and clinical prognostic information of TNBC were collected. Differentially expressed genes (DEGs) between TNBC and non-TNBC (NTNBC) were identified with the thresholds of false discovery rate < 0.05 and |log2 Fold Change| > 1. DEGs in AmiGO2 and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were retained for further study. Univariate, multivariate Cox, and logistic regression analysis were conducted for detecting DEG signature with the threshold of log-rank P < 0.05. The prognosis models of mRNA signature, clinical factors were constructed and compared.

RESULTS

One five-DEG signature, including CHST4, COCH, CST9, SOX11, and TDGF1 was identified in DEG prognosis model. Stratified analysis showed that the patients aged over 60, with higher pathologic stage (III-IV) and recurrence induced a significantly lower survival rate than those aged below 60, lower pathologic stage and without recurrence. Compared with patients with low-risk scores, those presented high-risk scores demonstrated significantly lower survival rate in the subgroup aged over 60 [HR = 3.780 (1.801-7.933), P < 0.0001]. For patients who obtained a higher pathologic stage and recurrence, high-risk scores were correlated with a significantly lower survival rate than patients with low-risk scores. The five-mRNA signature combined with clinical model (AUC = 0.950) predicted better than single clinical model (AUC = 0.795) or five-mRNA signature model (AUC = 0.823).

CONCLUSION

Our present study identified a prognostic prediction model (combined with five-mRNA signature and clinical factors) for TNBC patients receiving immunotherapy, which will benefit future research and clinical therapies.

Endocrine resistance in breast cancer: from molecular mechanisms to therapeutic strategies

Estrogen receptor-positive (ER +) breast cancer accounts for approximately 75% of all breast cancers. Endocrine therapies, including selective ER modulators (SERMs), aromatase inhibitors (AIs), and selective ER down-regulators (SERDs) provide substantial clinical benefit by reducing the risk of disease recurrence and mortality. However, resistance to endocrine therapies represents a major challenge, limiting the success of ER + breast cancer treatment. Mechanisms of endocrine resistance involve alterations in ER signaling via modulation of ER (e.g., ER downregulation, ESR1 mutations or fusions); alterations in ER coactivators/corepressors, transcription factors (TFs), nuclear receptors and epigenetic modulators; regulation of signaling pathways; modulation of cell cycle regulators; stress signaling; and alterations in tumor microenvironment, nutrient stress, and metabolic regulation. Current therapeutic strategies to improve outcome of endocrine-resistant patients in clinics include inhibitors against mechanistic target of rapamycin (mTOR), cyclin-dependent kinase (CDK) 4/6, and the phosphoinositide 3-kinase (PI3K) subunit, p110α. Preclinical studies reveal novel therapeutic targets, some of which are currently tested in clinical trials as single agents or in combination with endocrine therapies, such as ER partial agonists, ER proteolysis targeting chimeras (PROTACs), next-generation SERDs, AKT inhibitors, epidermal growth factor receptor 1 and 2 (EGFR/HER2) dual inhibitors, HER2 targeting antibody-drug conjugates (ADCs) and histone deacetylase (HDAC) inhibitors. In this review, we summarize the established and emerging mechanisms of endocrine resistance, alterations during metastatic recurrence, and discuss the approved therapies and ongoing clinical trials testing the combination of novel targeted therapies with endocrine therapy in endocrine-resistant ER + breast cancer patients.

Treatment landscape of triple-negative breast cancer - expanded options, evolving needs

Tumour heterogeneity and a long-standing paucity of effective therapies other than chemotherapy have contributed to triple-negative breast cancer (TNBC) being the subtype with the least favourable outcomes. In the past few years, advances in omics technologies have shed light on the relevance of the TNBC microenvironment heterogeneity, unveiling a close dynamic relationship with cancer cell features. An improved understanding of tumour-immune system co-evolution supports the need to adopt a more comprehensive view of TNBC as an ecosystem that encompasses the intrinsic and extrinsic features of cancer cells. This new appreciation of the biology of TNBC has already led to the development of novel targeted agents, including PARP inhibitors, antibody-drug conjugates and immune-checkpoint inhibitors, which are revolutionizing the therapeutic landscape and providing new opportunities both for patients with early-stage TNBC and for those with advanced-stage disease. The current therapeutic scenario is only the tip of the iceberg, as hundreds of new compounds and combinations are in development. The translation of these experimental therapies into clinical benefit is a welcome and ongoing challenge. In this Review, we describe the current and upcoming therapeutic landscape of TNBC and discuss how an integrated view of the TNBC ecosystem can define different levels of risk and provide improved opportunities for tailoring treatment.

Prognostic Impact of Immunoglobulin Kappa C in Breast Cancer Patients Treated with Adjuvant Chemotherapy

Introduction

Immunoglobulin κC (IGKC)-positive tumor-infiltrating plasma cells are associated with better prognosis in node-negative breast cancer patients without adjuvant systemic therapy. In the present study we evaluated the prognostic significance of IGKC in breast cancer patients treated with adjuvant chemotherapy ± tamoxifen.

Methods

IGKC expression was immunohistochemically analyzed in 193 breast cancer patients who were treated with adjuvant chemotherapy, either with cyclophosphamide, methotrexate, and 5-fluorouracil (CMF) or 5-fluorouracil, epirubicin, and cyclophosphamide (FEC) between 1993 and 2001 with a median follow-up of 11 years. The prognostic impact of IGKC expression was evaluated by Kaplan-Meier survival analyses as well as uni- and multivariate Cox regression. An interaction term was used to investigate a possible association between tamoxifen treatment and prognostic effect of IGKC expression.

Results

Kaplan-Meier analyses identified IGKC as a prognostic marker for metastasis-free survival (MFS): higher IGKC expression was associated with a better outcome (p = 0.02, log rank). Results of univariate Cox regression confirmed the prognostic impact of IGKC expression: patients with a strong IGKC expression had a longer MFS (hazard ratio [HR] 1.931; 95% confidence interval [CI] 1.087-3.431; p = 0.025). Multivariate Cox regression analysis showed the independent prognostic significance of IGKC expression (HR 2.070; 95% CI 1.088-3.938; p = 0.027). The interaction term confirmed a significant interaction between tamoxifen treatment and the prognostic impact of IGKC expression (p_interaction = 0.04).

Conclusion

IGKC expression had an independent prognostic impact in early breast cancer patients who received adjuvant chemotherapy. There was a significant interaction with the use of tamoxifen.

Immunomodulating Therapies in Breast Cancer-From Prognosis to Clinical Practice

The role of the immune system in breast cancer has been debated for decades. The advent of technologies such as next generation sequencing (NGS) has elucidated the crucial interplay between somatic mutations in tumors leading to neoantigens and immune responses with increased tumor-infiltrating lymphocytes and improved prognosis of breast cancer patients. In particular, triple-negative breast cancer (TNBC) has a higher mutational burden compared to other breast cancer subtypes. In addition, higher levels of tumor-associated antigens suggest that immunotherapies are a promising treatment option, specifically for TNBC. Indeed, higher concentrations of tumor-infiltrating lymphocytes are associated with better prognosis and response to chemotherapy in TNBC. An important target within the cancer immune cell cycle is the "immune checkpoint". Immune checkpoint inhibitors (ICPis) block the interaction of certain cell surface proteins that act as "brakes" on immune responses. Recent studies have shown that ICPis improve survival in both early and advanced TNBC. However, this comes at the price of increased toxicity, particularly immune-mediated toxicity. As an alternative approach, individualized mRNA vaccination strategies against tumor-associated neoantigens represent another promising approach leading to neoantigen-specific immune responses. These novel strategies should help to improve treatment outcomes, especially for patients with triple negative breast cancer.

Prognostic Impact of Immunoglobulin Kappa C (IGKC) in Early Breast Cancer

We studied the prognostic impact of tumor immunoglobulin kappa C (IGKC) mRNA expression as a marker of the humoral immune system in the FinHer trial patient population, where 1010 patients with early breast cancer were randomly allocated to either docetaxel-containing or vinorelbine-containing adjuvant chemotherapy. HER2-positive patients were additionally allocated to either trastuzumab or no trastuzumab. Hormone receptor-positive patients received tamoxifen. IGKC was evaluated in 909 tumors using quantitative real-time polymerase chain reaction, and the influence on distant disease-free survival (DDFS) was examined using univariable and multivariable Cox regression and Kaplan-Meier estimates. Interactions were analyzed using Cox regression. IGKC expression, included as continuous variable, was independently associated with DDFS in a multivariable analysis also including age, molecular subtype, grade, and pT and pN stage (HR 0.930, 95% CI 0.870-0.995, p = 0.034). An independent association with DDFS was also found in a subset analysis of triple-negative breast cancers (TNBC) (HR 0.843, 95% CI 0.724-0.983, p = 0.029), but not in luminal (HR 0.957, 95% CI 0.867-1.056, p = 0.383) or HER2-positive (HR 0.933, 95% CI 0.826-1.055, p = 0.271) cancers. No significant interaction between IGKC and chemotherapy or trastuzumab administration was detected (Pinteraction = 0.855 and 0.684, respectively). These results show that humoral immunity beneficially influences the DDFS of patients with early TNBC.

Survival analysis across the entire transcriptome identifies biomarkers with the highest prognostic power in breast cancer

Introduction

Extensive research is directed to uncover new biomarkers capable to stratify breast cancer patients into clinically relevant cohorts. However, the overall performance ranking of such marker candidates compared to other genes is virtually absent. Here, we present the ranking of all survival related genes in chemotherapy treated basal and estrogen positive/HER2 negative breast cancer.

Methods

We searched the GEO repository to uncover transcriptomic datasets with available follow-up and clinical data. After quality control and normalization, samples entered an integrated database. Molecular subtypes were designated using gene expression data. Relapse-free survival analysis was performed using Cox proportional hazards regression. False discovery rate was computed to combat multiple hypothesis testing. Kaplan-Meier plots were drawn to visualize the best performing genes.

Results

The entire database includes 7,830 unique samples from 55 independent datasets. Of those with available relapse-free survival time, 3,382 samples were estrogen receptor-positive and 696 were basal. In chemotherapy treated ER positive/ERBB2 negative patients the significant prognostic biomarker genes achieved hazard rates between 1.76 and 3.33 with a p value below 5.8E−04. The significant prognostic genes in adjuvant chemotherapy treated basal breast cancer samples reached hazard rates between 1.88 and 3.61 with a p value below 7.2E−04. Our integrated platform was extended enabling the validation of future biomarker candidates.

Conclusions

A reference ranking for all genes in two chemotherapy treated breast cancer cohorts is presented. The results help to neglect those with unlikely clinical significance and to focus future research on the most promising candidates.

Meta-Analysis of Microdissected Breast Tumors Reveals Genes Regulated in the Stroma but Hidden in Bulk Analysis

Transcriptome data provide a valuable resource for the study of cancer molecular mechanisms, but technical biases, sample heterogeneity, and small sample sizes result in poorly reproducible lists of regulated genes. Additionally, the presence of multiple cellular components contributing to cancer development complicates the interpretation of bulk transcriptomic profiles. To address these issues, we collected 48 microarray datasets derived from laser capture microdissected stroma or epithelium in breast tumors and performed a meta-analysis identifying robust lists of differentially expressed genes. This was used to create a database with carefully harmonized metadata that we make freely available to the research community. As predicted, combining the results of multiple datasets improved statistical power. Moreover, the separate analysis of stroma and epithelium allowed the identification of genes with different contributions in each compartment, which would not be detected by bulk analysis due to their distinct regulation in the two compartments. Our method can be profitably used to help in the discovery of biomarkers and the identification of functionally relevant genes in both the stroma and the epithelium. This database was made to be readily accessible through a user-friendly web interface.

Identification of gastric cancer subtypes based on pathway clustering

Gastric cancer (GC) is highly heterogeneous in the stromal and immune microenvironment, genome instability (GI), and oncogenic signatures. However, a classification of GC by combining these features remains lacking. Using the consensus clustering algorithm, we clustered GCs based on the activities of 15 pathways associated with immune, DNA repair, oncogenic, and stromal signatures in three GC datasets. We identified three GC subtypes: immunity-deprived (ImD), stroma-enriched (StE), and immunity-enriched (ImE). ImD showed low immune infiltration, high DNA damage repair activity, high tumor aneuploidy level, high intratumor heterogeneity (ITH), and frequent TP53 mutations. StE displayed high stromal signatures, low DNA damage repair activity, genomic stability, low ITH, and poor prognosis. ImE had strong immune infiltration, high DNA damage repair activity, high tumor mutation burden, prevalence of microsatellite instability, frequent ARID1A mutations, elevated PD-L1 expression, and favorable prognosis. Based on the expression levels of four genes (TAP2, SERPINB5, LTBP1, and LAMC1) in immune, DNA repair, oncogenic, and stromal pathways, we developed a prognostic model (IDOScore). The IDOScore was an adverse prognostic factor and correlated inversely with immunotherapy response in cancer. Our identification of new GC subtypes provides novel insights into tumor biology and has potential clinical implications for the management of GCs.

Neoadjuvant durvalumab plus weekly nab-paclitaxel and dose-dense doxorubicin/cyclophosphamide in triple-negative breast cancer

The goal of this Phase I/II trial is to assess the safety and efficacy of administering durvalumab concurrent with weekly nab-paclitaxel and dose-dense doxorubicin/cyclophosphamide (ddAC) neoadjuvant therapy for stages I-III triple-negative breast cancer. The primary endpoint is pathologic complete response (pCR:ypT0/is, ypN0). The response was correlated with PDL1 expression and stromal tumor-infiltrating lymphocytes (sTILs). Two dose levels of durvalumab (3 and 10 mg/kg) were assessed. PD-L1 was assessed using the SP263 antibody; ≥1% immune and tumor cell staining was considered positive; sTILs were calculated as the area occupied by mononuclear inflammatory cells over the total intratumoral stromal area. 59 patients were evaluable for toxicity and 55 for efficacy in the Phase II study (10 mg/kg dose). No dose-limiting toxicities were observed in Phase I. In Phase II, pCR rate was 44% (95% CI: 30-57%); 18 patients (31%) experienced grade 3/4 treatment-related adverse events (AE), most frequently neutropenia (n = 4) and anemia (n = 4). Immune-related grade 3/4 AEs included Guillain-Barre syndrome (n = 1), colitis (n = 2), and hyperglycemia (n = 2). Of the 50 evaluable patients for PD-L1, 31 (62%) were PD-L1 positive. pCR rates were 55% (95% CI: 0.38-0.71) and 32% (95% CI: 0.12-0.56) in the PD-L1 positive and negative groups (p = 0.15), respectively. sTIL counts were available on 52 patients and were significantly higher in the pCR group (p = 0.0167). Concomitant administration of durvalumab with sequential weekly nab-paclitaxel and ddAC neoadjuvant chemotherapy resulted in a pCR rate of 44%; pCR rates were higher in sTIL-high cancers.

BTF3 promotes stemness and inhibits TypeⅠInterferon signaling pathway in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a major challenge in clinical practice due to its aggressiveness and lack of targeted treatment. Cancer stem-like traits contribute to tumorigenesis and immune privilege of TNBC. However, the relationship of stemness and immunosurveillance remains unclear. Here, we demonstrate that BTF3 expression is related with stem-like properties in TNBC cells. BTF3 modulates stemness, migration and proliferation of TNBC in vitro. Bioinformatics analysis revealed that interferon signaling pathways and IRF7, both of which participate in the immune escape of TNBC, are closely related to BTF3 in TNBC cells. Knockdown of BTF3 activates IRF7 expression through increased degradation of BMI1, a protein that can represses IRF7 transcription by directly binding to its promotor region. BTF3 links stem-like traits and the interferon signaling pathway, revealing the potential connection of stemness and immunomodulation in TNBC. Clinically, we suggest that BTF3 is predictive of poor prognosis in patients with TNBC. Together, our findings highlight an important role of BTF3 in regulating the progression of TNBC cells.

A four-gene signature in the tumor microenvironment that significantly associates with the prognosis of patients with breast cancer

Breast cancer (BRCA) is a highly heterogeneous disease due to the complicated microenvironment in the tumor, making the treatment benefits varied. Therefore, this study aims to identify a gene signature in the tumor microenvironment (TME) associated with the prognosis of BRCA patients. We downloaded the immune, stromal, and proliferation (ISP)-associated genes from the literature on BRCA. mRNA expression and clinical information obtained from The Cancer Genome Atlas (TCGA) were performed to identify the initial biomarker. Furthermore, we validated the robustness of the gene signature in the independent validation data set GSE20685. A four-gene signature in TME, including CD74, MMP9, RPA3, and SHCBP1, was constructed to predict the overall survival of BRCA. The survival time of the high-risk group was significantly worse than that of the low-risk group. Univariate and multivariate Cox regression analysis showed that our four-gene ISP signature was an independent prognostic factor in TCGA and GSE20685 data sets. The AUC suggested that our four-gene ISP signature was comparable to TNM classification at predicting the overall survival of BRCA patients. Interestingly, BRCA patients with high-risk scores were more likely to be associated with stromal and proliferation of cancer. In contrast, those with high-risk scores were more likely to be associated with tumor immunity-related pathway. We found an innovative biomarker in TME to predict the prognosis of BRCA. This signal might reflect the imbalance of TME and provide potential biomarkers for the individualized and precise treatment of BRCA.

A DNA Methylation-Based Panel for the Prognosis and Dagnosis of Patients With Breast Cancer and Its Mechanisms

Objective

To identify DNA methylation related biomarkers in patients with breast cancer (BC).

Materials and Methods

A total of seven BC methylation studies including 1,438 BC patients or breast tissues were included in this study. An elastic net regularized Cox proportional hazards regression (CPH) model was used to build a multi-5′-C-phosphate-G-3′ methylation panel. The diagnosis and prognosis power of the panel was evaluated and validated using a Kaplan–Meier curve, univariate and multivariable CPH, subgroup analysis. A nomogram containing the panel was developed. The relationships between the panel-based methylation risk and the immune landscape and genomic metrics were investigated.

Results

Sixty-eight CpG sites were significantly correlated with the overall survival (OS) of BC patients, and based on the result of penalized CPH, a 28-CpG site based multi CpG methylation panel was found. The prognosis and diagnosis role of the panel was validated in the discovery set, validation set, and six independent cohorts, which indicated that higher methylation risk was associated with poor OS, and the panel outperformed currently available biomarkers and remained an independent factor after adjusting for other clinical features. The methylation risk was negatively correlated with innated and adaptive immune cells, and positively correlated with total mutation load, SCNA, and MATH.

Conclusions

We validated a multi CpG methylation panel that could independently predict the OS of BC patients. The Th2-mediated tumor promotion effect—suppression of innate and adaptive immunity—participated in the progression of high-risk BC. Patients with high methylation risk were associated with tumor heterogeneity and poor survival.

Prognostic implications of the expression levels of different immunoglobulin heavy chain-encoding RNAs in early breast cancer

The extent and composition of the immune response in a breast cancer is one important prognostic factor for the disease. The aim of the current work was to refine the analysis of the humoral component of an immune response in breast tumors by quantifying mRNA expression of different immunoglobulin classes and study their association with prognosis. We used RNA-Seq data from two local population-based breast cancer cohorts to determine the expression of IGJ and immunoglobulin heavy (IGH) chain-encoding RNAs. The association with prognosis was investigated and public data sets were used to corroborate the findings. Except for IGHE and IGHD, mRNAs encoding heavy chains were generally detected at substantial levels and correlated with other immune-related genes. High IGHG1 mRNA was associated with factors related to poor prognosis such as estrogen receptor negativity, HER2 amplification, and high grade, whereas high IGHA2 mRNA levels were primarily associated with lower age at diagnosis. High IGHA2 and IGJ mRNA levels were associated with a more favorable prognosis both in univariable and multivariable Cox models. When adjusting for other prognostic factors, high IGHG1 mRNA levels were positively associated with improved prognosis. To our knowledge, these results are the first to demonstrate that expression of individual Ig class types has prognostic implications in breast cancer.

Age-related mutational signature negatively associated with immune activity and survival outcome in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is characterized by broad genomic and transcriptional heterogeneity and results in a worse prognosis than other breast cancer types. Here, we integrated genomic and transcriptomic data combined with clinicopathologic information from 538 patients with TNBC and identified four novel significantly mutated genes (SMGs), namely, KDM6A, CD86, RBM47, and IFNGR1. A mutational signature (known as age-related signature 1) featured by enrichment of C > T mutations at NpCpG trinucleotides was associated with worse survival in TNBC (HR, 1.76 [95% CI, 1.07-2.90]; P = .025). We also analyzed gene transcriptomic profiles of TNBC samples and identified immune regulation-related gene pathways (e.g., antigen processing presentation and interferon signaling), and the cell cycle was significantly altered in samples with different signature 1 activity groups. The analysis further revealed that signature 1 was associated with decreased tumor immunogenicity and immunocyte infiltration in TNBC. This negative correlation was also observed in lung adenocarcinoma and prostate cancer samples. Furthermore, we found that patients with mutational signature 1 were markedly associated with decreased tumor mutation burden, even after controlling for age, grade, histological type, lymph node status, mutations in BRCA1/2 and ATR, and APOBEC and homologous recombination repair deficiency signatures (OR, 0.19 [95% CI, 0.11-0.32]; P < .001). Overall, this study identified previously unreported SMGs and re-annotated that age-related signature 1 was associated with a weakened immune microenvironment and predictive of poor survival in TNBC, offering opportunities to stratify patients into optimal treatment plans based on genomic subtyping.

Immunological Differences Between Immune-Rich Estrogen Receptor-Positive and Immune-Rich Triple-Negative Breast Cancers

PURPOSE

A subset of estrogen receptor–positive (ER-positive) breast cancer (BC) contains high levels of tumor-infiltrating lymphocytes (TILs), similar to triple-negative BC (TNBC). The majority of immuno-oncology trials target TNBCs because of the greater proportion of TIL-rich TNBCs. The extent to which the immune microenvironments of immune-rich ER-positive BC and TNBC differ is unknown.

PATIENTS AND METHODS

RNA sequencing data from The Cancer Genome Atlas (TCGA; n = 697 ER-positive BCs; n = 191 TNBCs) were used for discovery; microarray expression data from Molecular Taxonomy of Breast Cancer International Consortium (METABRIC; n = 1,186 ER-positive BCs; n = 297 TNBCs) was used for validation. Patients in the top 25th percentile of a previously published total TIL metagene score distribution were considered immune rich. We compared expression of immune cell markers, immune function metagenes, and immuno-oncology therapeutic targets among immune-rich subtypes.

RESULTS

Relative fractions of resting mast cells (TCGA P_adj = .009; METABRIC P_adj = 4.09E-15), CD8⁺ T cells (TCGA P_adj = .015; METABRIC P_adj = 0.390), and M2-like macrophages (TCGA P_adj= 4.68E-05; METABRIC P_adj = .435) were higher in immune-rich ER-positive BCs, but M0-like macrophages (TCGA P_adj = 0.015; METABRIC P_adj = .004) and M1-like macrophages (TCGA P_adj = 9.39E-08; METABRIC P_adj = 6.24E-11) were higher in immune-rich TNBCs. Ninety-one immune-related genes (eg, CXCL14, CSF3R, TGF-B3, LRRC32/GARP, TGFB-R2) and a transforming growth factor β (TGF-β) response metagene were significantly overexpressed in immune-rich ER-positive BCs, whereas 41 immune-related genes (eg, IFNG, PD-L1, CTLA4, MAGEA4) were overexpressed in immune-rich TNBCs in both discovery and validation data sets. TGF-β pathway member genes correlated negatively with expression of immune activation markers (IFNG, granzyme-B, perforin) and positively with M2-like macrophages (IL4, IL10, and MMP9) and regulatory T-cell (FOXP3) markers in both subtypes.

CONCLUSION

Different immunotherapy strategies may be optimal in immune-rich ER-positive BC and TNBC. Drugs targeting the TGF-β pathway and M2-like macrophages are promising strategies in immune-rich ER-positive BCs to augment antitumor immunity.

Immunotherapy and targeted therapy combinations in metastatic breast cancer

Immunotherapy is emerging as a new treatment modality in breast cancer. After long-standing use of endocrine therapy and targeted biological therapy, improved understanding of immune evasion by cancer cells and the discovery of selective immune checkpoint inhibitors have created novel opportunities for treatment. Single-drug therapies with monoclonal antibodies against programmed death-1 (PD-1) and programmed death ligand-1 (PD-L1) have shown little efficacy in patients with metastatic breast cancer, in part because of the low number of tumour-infiltrating lymphocytes in most breast cancers. There is growing interest in the development of combinations of immunotherapy and molecularly targeted therapies for metastatic breast cancer. In this Personal View, we review the available data and ongoing efforts to establish the safety and efficacy of immunotherapeutic approaches in combination with HER2-targeted therapy, inhibitors of cyclin-dependent kinases 4 and 6, angiogenesis inhibitors, poly(ADP-ribose) polymerase inhibitors, as well as chemotherapy and radiotherapy.

HIF1A expression correlates with increased tumor immune and stromal signatures and aggressive phenotypes in human cancers

BACKGROUND

Although many studies have revealed essential roles of HIF1A (hypoxia inducible factor 1 subunit alpha) in regulating various pathways associated with cancer development, a systematic investigation of associations of HIF1A expression with tumor immunity, the tumor microenvironment and other tumor phenotypes in pan-cancer is lacking.

METHODS

Using cancer genomics datasets of 10 cancer cohorts from the Cancer Genome Atlas (TCGA) program, we investigated associations of HIF1A expression with tumor immune and stromal signatures, and various tumor phenotypes, including cell proliferation, stemness, epithelial-mesenchymal transition (EMT), tumor purity, oncogenic signaling, and clinical outcomes.

RESULTS

HIF1A upregulation was found to be associated with increased immune and stromal signatures, aggressive phenotypes, and worse survival rates in various cancers. Moreover, HIF1A upregulation was not only associated with activation of various oncogenic signaling pathways, but also with increased tumor suppressive signatures, including apoptosis and anti-tumor immune response, indicative of a dual role of HIF1A in cancer development. However, HIF1A expression showed a stronger correlation with immune-inhibiting signatures than with immune-promoting signatures. Furthermore, HIF1A expression was found to be positively associated with both tumor immune infiltration and PD-L1 expression, indicating that tumors with elevated expression of HIF1A may exhibit a more active immunotherapy response. This indication was substantiated in a kidney cancer cohort receiving anti-PD-1/PD-L1 immunotherapy.

CONCLUSIONS

HIF1A upregulation correlates with increased tumor immune and stromal signatures and aggressive phenotypes in human cancers. Our analysis may provide new insights into the role of HIF1A in tumor biology and clinical management.

Multi-Gene Prognostic Signatures and Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in ER-positive, HER2-negative Breast Cancer Patients

Determining which patients with early-stage breast cancer should receive chemotherapy is an important clinical issue. Chemotherapy has several adverse side effects, impacting on quality of life, along with significant economic consequences. There are a number of multi-gene prognostic signatures for breast cancer recurrence but there is less evidence that these prognostic signatures are predictive of therapy benefit. Biomarkers that can predict patient response to chemotherapy can help avoid ineffective over-treatment. The aim of this work was to assess if the OncoMasTR prognostic signature can predict pathological complete response (pCR) to neoadjuvant chemotherapy, and to compare its predictive value with other prognostic signatures: EndoPredict, Oncotype DX and Tumor Infiltrating Leukocytes. Gene expression datasets from ER-positive, HER2-negative breast cancer patients that had pre-treatment biopsies, received neoadjuvant chemotherapy and an assessment of pCR were obtained from the Gene Expression Omnibus repository. A total of 813 patients with 66 pCR events were included in the analysis. OncoMasTR, EndoPredict, Oncotype DX and Tumor Infiltrating Leukocytes numeric risk scores were approximated by applying the gene coefficients to the corresponding mean probe expression values. OncoMasTR, EndoPredict and Oncotype DX prognostic scores were moderately well correlated according to the Pearson's correlation coefficient. Association with pCR was estimated using logistic regression. The odds ratio for a 1 standard deviation increase in risk score, adjusted for cohort, were similar in magnitude for all four signatures. Additionally, the four signatures were significant predictors of pCR. OncoMasTR added significant predictive value to EndoPredict, Oncotype DX and Tumor Infiltrating Leukocytes signatures as determined by bivariable and trivariable analysis. In this in silico analysis, OncoMasTR, EndoPredict, Oncotype DX, and Tumor Infiltrating Leukocytes were significantly predictive of pCR to neoadjuvant chemotherapy in ER-positive and HER2-negative breast cancer patients.

Transcriptome analysis of tongue cancer based on high‑throughput sequencing

Tongue cancer is one of the most common types of cancer, but its molecular etiology and pathogenesis remain unclear. The aim of the present study was to elucidate the pathogenesis of tongue cancer and investigate novel potential diagnostic and therapeutic targets. Four matched pairs of tongue cancer and paracancerous tissues were collected for RNA sequencing (RNA-Seq), and the differentially expressed genes were analyzed. The RNA-Seq data of tongue cancer tissues were further analyzed using bioinformatics and reverse transcription-quantitative PCR analysis. The sequenced reads were quantified and qualified in accordance with the analysis demands. The transcriptomes of the tongue cancer tissues and paired paracancerous tissues were analyzed, and 1,700 upregulated and 2,249 downregulated genes were identified. Gene Ontology analysis uncovered a significant enrichment in the terms associated with extracellular matrix (ECM) organization, cell adhesion and collagen catabolic processes. Kyoto Encyclopedia of Genes and Genomes analysis demonstrated that these differentially expressed genes were mainly enriched in the focal adhesion pathway, ECM-receptor interaction pathway, phosphoinositide 3-kinase (PI3K)-Akt pathway, and cell adhesion molecules. Comprehensive analyses of the gene tree and pathway network revealed that the majority of cell cycle genes were upregulated, while the majority of the genes associated with intracellular response, cell adhesion and cell differentiation were downregulated. The ECM-receptor interaction, focal adhesion kinase (FAK) and PI3K-Akt pathways were closely associated with one another and held key positions in differential signaling pathways. The ECM-receptor, FAK and PI3K-Akt signaling pathways were found to synergistically promote tongue cancer occurrence and progression, and may serve as potential diagnostic and therapeutic targets for this type of cancer.

Development of an Immune-Related Prognostic Signature in Breast Cancer

BACKGROUND

Although increased early detection, diagnosis and treatment have improved the outcome of breast cancer patients, prognosis estimation still poses challenges due to the disease heterogeneity. Accumulating data indicated an evident correlation between tumor immune microenvironment and clinical outcomes.

OBJECTIVE

To construct an immune-related signature that can estimate disease prognosis and patient survival in breast cancer.

METHODS

Gene expression profiles and clinical data of breast cancer patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, which were further divided into a training set (n = 499), a testing set (n = 234) and a Meta-validation set (n = 519). In the training set, immune-related genes were recognized using combination of gene expression data and ESTIMATE algorithm-derived immune scores. An immune-related prognostic signature was generated with LASSO Cox regression analysis. The prognostic value of the signature was validated in the testing set and the Meta-validation set.

RESULTS

A total of 991 immune-related genes were identified. Twelve genes with non-zero coefficients in LASSO analysis were used to construct an immune-related prognostic signature. The 12-gene signature significantly stratified patients into high and low immune risk groups in terms of overall survival independent of clinical and pathologic factors. The signature also significantly stratified overall survival in clinical defined groups, including stage I/II disease. Several biological processes, such as immune response, were enriched among genes in the immune-related signature. The percentage of M2 macrophage infiltration was significantly different between low and high immune risk groups. Time-dependent ROC curves indicated good performance of our signature in predicting the 1-, 3- and 5-year overall survival for patients from the full TCGA cohort. Furthermore, the composite signature derived by integrating immune-related signature with clinical factors, provided a more accurate estimation of survival relative to molecular signature alone.

CONCLUSION

We developed a 12-gene prognostic signature, providing novel insights into the identification of breast cancer with a high risk of death and assessment of the possibility of immunotherapy incorporation in personalized breast cancer management.

Emerging immune gene signatures as prognostic or predictive biomarkers in breast cancer

Several multigene assays have been developed to predict the risk of distant recurrence and response to adjuvant therapy in early breast cancer. However, the prognostic or predictive value of current proliferation gene signature-based assays are limited to hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2-) early breast cancer. Considerable discordance between the different assays in classifying patients into risk groups has also been reported, thus raising questions about the clinical utility of these assays for individual patients. Therefore, there still remains a need for better prognostic or predictive biomarkers for breast cancer. The role of immune cells comprising tumor microenvironment in tumor progression has been recognized. Accumulating evidences have shown that immune gene signatures and tumor-infiltrating lymphocytes (TILs) can be prognostic or predictive factors in breast cancer, particularly with regard to HER2+ and triple-negative breast cancer. In this review, I summarize current multigene assays for breast cancer and discuss recent progress in identifying novel breast cancer biomarkers, focusing on the emerging importance of immune gene signatures and TILs as prognostic or predictive biomarkers.

Low pretreatment lymphocyte/monocyte ratio is associated with the better efficacy of neoadjuvant chemotherapy in breast cancer patients

The combination of some parameters, including the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR) and neutrophil to monocyte ratio (NMR), which are associated with patient prognosis, our goal is to find the best indicator to predict the efficacy of neoadjuvant chemotherapy（NAC）in breast cancer patients. A cohort of 808 breast cancer patients treated with NAC and subsequent surgery was analyzed retrospectively. In addition, 2424 people without breast cancer served as the normal group, which included three-fold more individuals compared with the breast cancer group. Receiver operating characteristics (ROC) curves were used to determine the optimal cutoff values of inflammatory markers and compare their predictive capacity. No significant differences in age, PLR, LMR and NMR were noted between the normal group and the patient group. However, the mean value of the NLR was significantly increased in breast cancer patients (2.28) compared with the normal population (2.04) (P < .05). The LMR was significantly associated with age (P = .003), menopausal status (P = .004), cT category (P = .017), cN category (P = .024) and response to NAC (P = .001). The multivariate analysis indicated that among these inflammatory markers, the LMR (6.1 < vs ≥ 6.1) was the only independent predictive factor for the efficacy of NAC (OR = 1.771, 95% CI = 1.273-2.464, P = .001). A low LMR is considered a favorable predicative factor of the efficacy of NAC in breast cancer patients.

Tumor-infiltrating lymphocytes and CD8+ T cells predict survival of triple-negative breast cancer

PURPOSE

Tumor inflammatory response was evaluated as a prognostic feature in triple-negative breast cancer (TNBC) and compared with the clinical prognosticators of breast cancer and selected biomarkers of cancer cell proliferation.

METHODS

TNBC patients (n = 179) with complete clinical data and up to 18-year follow-up were obtained from Auria biobank, Turku University Hospital, Turku, Finland. Tumor-infiltrating lymphocytes (TILs) and several subtypes of inflammatory cells detected with immunohistochemistry were evaluated in different tumor compartments in full tissue sections and tissue microarrays.

RESULTS

Deficiency of stromal TILs and low number of CD8⁺ T cells independently predicted mortality in TNBC (HR 2.4, p 0.02 and HR 2.1, p 0.02, respectively). Each 10% decrease in stromal TILs resulted in 20% increased risk of mortality. An average of 13.2-year survival difference was observed between the majority (> 75%) of patients with low (< 14% of TILs) vs high (≥ 14% of TILs) frequency of CD8⁺ T cells. The prognostic value of TILs and CD8⁺ T cells varied when evaluated in different tumor compartments. TILs and CD8⁺ T cells were significantly associated with Securin and Separase, essential regulators of metaphase-anaphase transition of the cell cycle.

DISCUSSION

TILs and CD8⁺ T cells provide additional prognostic value to the established clinical prognostic markers in TNBC. However, possible clinical applications would still benefit from systematic guidelines for evaluating tumor inflammatory response. Increasing understanding on the interactions between the regulation of cancer cell proliferation and inflammatory response may in future advance treatment of TNBC.

Distinct gene expression profiles between primary breast cancers and brain metastases from pair-matched samples

Our objectives were to determine whether clinic-pathological markers and immune-related gene signatures in breast cancer exhibit any change upon brain metastasis and whether previously reported genes significantly associated with brain metastases and the epithelial-mesenchymal transition (EMT) were reproducible and consistent in our dataset. Sixteen pair-matched samples from primary breast cancers and brain metastases diagnosed were collected from the Japan Clinical Oncology Group Breast Cancer Study Group. Gene expression profiles for immune-, brain metastases-, and EMT-related genes were compared between primary breast cancers and brain metastases. Potential therapeutic target genes of 41 FDA-approved or under-investigation agents for brain metastases were explored. Immune-related signatures exhibited significantly lower gene expression in brain metastases than in primary breast cancers. No significant differences were detected for the majority of genes associated with brain metastases and EMT in the two groups. Among 41 therapeutic target candidates, VEGFA and DNMT3A demonstrated significantly higher gene expression in brain metastases. We found that distinct patterns of gene expression exist between primary breast cancers and brain metastases. Further studies are needed to explore whether these distinct expression profiles derive from or underlie disease status and compare these features between metastases to the brain and other sites.

Tumor infiltrating B-cells signal functional humoral immune responses in breast cancer

Tumor-infiltrating B-cells (TIL-B) in breast cancer (BC) have previously been associated with improved clinical outcomes; however, their role(s) in tumor immunity is not currently well known. This study confirms and extends the correlation between higher TIL-B densities and positive outcomes through an analysis of HER2-positive and triple-negative BC patients from the BIG 02-98 clinical trial (10yr mean follow-up). Fresh tissue analyses identify an increase in TIL-B density in untreated primary BC compared to normal breast tissues, which is associated with global, CD4+ and CD8+ TIL, higher tumor grades, higher proliferation and hormone receptor negativity. All B-cell differentiation stages are detectable but significant increases in memory TIL-B are consistently present. BC with higher infiltrates are specifically characterized by germinal center TIL-B, which in turn are correlated with TFH TIL and antibody-secreting TIL-B principally located in tertiary lymphoid structures. Some TIL-B also interact directly with tumor cells. Functional analyses reveal TIL-B are responsive to BCR stimulation ex vivo, express activation markers and produce cytokines and immunoglobulins despite reduced expression of the antigen-presenting molecules HLA-DR and CD40. Overall, these data support the concept that ongoing humoral immune responses are generated by TIL-B and help to generate effective anti-tumor immunity at the tumor site.