Gene modules and response to neoadjuvant chemotherapy in breast cancer subtypes: a pooled analysis

Rapid autopsies to enhance metastatic research: the UPTIDER post-mortem tissue donation program

Research on metastatic cancer has been hampered by limited sample availability. Here we present the breast cancer post-mortem tissue donation program UPTIDER and show how it enabled sampling of a median of 31 (range: 5-90) metastases and 5-8 liquids per patient from its first 20 patients. In a dedicated experiment, we show the mild impact of increasing time after death on RNA quality, transcriptional profiles and immunohistochemical staining in tumor tissue samples. We show that this impact can be counteracted by organ cooling. We successfully generated ex vivo models from tissue and liquid biopsies from distinct histological subtypes of breast cancer. We anticipate these and future findings of UPTIDER to elucidate mechanisms of disease progression and treatment resistance and to provide tools for the exploration of precision medicine strategies in the metastatic setting.

Tumor Intrinsic Subtypes and Gene Expression Signatures in Early-Stage ERBB2/HER2-Positive Breast Cancer: A Pooled Analysis of CALGB 40601, NeoALTTO, and NSABP B-41 Trials

Importance

Biologic features may affect pathologic complete response (pCR) and event-free survival (EFS) after neoadjuvant chemotherapy plus ERBB2/HER2 blockade in ERBB2/HER2-positive early breast cancer (EBC).

Objective

To define the quantitative association between pCR and EFS by intrinsic subtype and by other gene expression signatures in a pooled analysis of 3 phase 3 trials: CALGB 40601, NeoALTTO, and NSABP B-41.

Design, Setting, and Participants

In this retrospective pooled analysis, 1289 patients with EBC received chemotherapy plus either trastuzumab, lapatinib, or the combination, with a combined median follow-up of 5.5 years. Gene expression profiling by RNA sequencing was obtained from 758 samples, and intrinsic subtypes and 618 gene expression signatures were calculated. Data analyses were performed from June 1, 2020, to January 1, 2023.

Main Outcomes and Measures

The association of clinical variables and gene expression biomarkers with pCR and EFS were studied by logistic regression and Cox analyses.

Results

In the pooled analysis, of 758 women, median age was 49 years, 12% were Asian, 6% Black, and 75% were White. Overall, pCR results were associated with EFS in the ERBB2-enriched (hazard ratio [HR], 0.45; 95% CI, 0.29-0.70; P < .001) and basal-like (HR, 0.19; 95% CI, 0.04-0.86; P = .03) subtypes but not in luminal A or B tumors. Dual trastuzumab plus lapatinib blockade over trastuzumab alone had a trend toward EFS benefit in the intention-to-treat population; however, in the ERBB2-enriched subtype there was a significant and independent EFS benefit of trastuzumab plus lapatinib vs trastuzumab alone (HR, 0.47; 95% CI, 0.27-0.83; P = .009). Overall, 275 of 618 gene expression signatures (44.5%) were significantly associated with pCR and 9 of 618 (1.5%) with EFS. The ERBB2/HER2 amplicon and multiple immune signatures were significantly associated with pCR. Luminal-related signatures were associated with lower pCR rates but better EFS, especially among patients with residual disease and independent of hormone receptor status. There was significant adjusted HR for pCR ranging from 0.45 to 0.81 (higher pCR) and 1.21-1.94 (lower pCR rate); significant adjusted HR for EFS ranged from 0.71 to 0.94.

Conclusions and relevance

In patients with ERBB2/HER2-positive EBC, the association between pCR and EFS differed by tumor intrinsic subtype, and the benefit of dual ERBB2/HER2 blockade was limited to ERBB2-enriched tumors. Immune-activated signatures were concordantly associated with higher pCR rates and better EFS, whereas luminal signatures were associated with lower pCR rates.

Canonical Kaiso target genes define a functional signature that associates with breast cancer survival and the invasive lobular carcinoma histological type

Invasive lobular carcinoma (ILC) is a low- to intermediate-grade histological breast cancer type caused by mutational inactivation of E-cadherin function, resulting in the acquisition of anchorage independence (anoikis resistance). Most ILC cases express estrogen receptors, but options are limited in relapsed endocrine-refractory disease as ILC tends to be less responsive to standard chemotherapy. Moreover, ILC can relapse after >15 years, an event that currently cannot be predicted. E-cadherin inactivation leads to p120-catenin-dependent relief of the transcriptional repressor Kaiso (ZBTB33) and activation of canonical Kaiso target genes. Here, we examined whether an anchorage-independent and ILC-specific transcriptional program correlated with clinical parameters in breast cancer. Based on the presence of a canonical Kaiso-binding consensus sequence (cKBS) in the promoters of genes that are upregulated under anchorage-independent conditions, we defined an ILC-specific anoikis resistance transcriptome (ART). Converting the ART genes into human orthologs and adding published Kaiso target genes resulted in the Kaiso-specific ART (KART) 33-gene signature, used subsequently to study correlations with histological and clinical variables in primary breast cancer. Using publicly available data for ERPOS Her2NEG breast cancer, we found that expression of KART was positively associated with the histological ILC breast cancer type (p < 2.7E-07). KART expression associated with younger patients in all invasive breast cancers and smaller tumors in invasive ductal carcinoma of no special type (IDC-NST) (<2 cm, p < 6.3E-10). We observed associations with favorable long-term prognosis in both ILC (hazard ratio [HR] = 0.51, 95% CI = 0.29-0.91, p < 3.4E-02) and IDC-NST (HR = 0.79, 95% CI = 0.66-0.93, p < 1.2E-04). Our analysis thus defines a new mRNA expression signature for human breast cancer based on canonical Kaiso target genes that are upregulated in E-cadherin deficient ILC. The KART signature may enable a deeper understanding of ILC biology and etiology. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

MAGI1 Prevents Senescence and Promotes the DNA Damage Response in ER+ Breast Cancer

MAGI1 acts as a tumor suppressor in estrogen receptor-positive (ER+) breast cancer (BC), and its loss correlates with a more aggressive phenotype. To identify the pathways and events affected by MAGI1 loss, we deleted the MAGI1 gene in the ER+ MCF7 BC cell line and performed RNA sequencing and functional experiments in vitro. Transcriptome analyses revealed gene sets and biological processes related to estrogen signaling, the cell cycle, and DNA damage responses affected by MAGI1 loss. Upon exposure to TNF-α/IFN-γ, MCF7 MAGI1 KO cells entered a deeper level of quiescence/senescence compared with MCF7 control cells and activated the AKT and MAPK signaling pathways. MCF7 MAGI1 KO cells exposed to ionizing radiations or cisplatin had reduced expression of DNA repair proteins and showed increased sensitivity towards PARP1 inhibition using olaparib. Treatment with PI3K and AKT inhibitors (alpelisib and MK-2206) restored the expression of DNA repair proteins and sensitized cells to fulvestrant. An analysis of human BC patients' transcriptomic data revealed that patients with low MAGI1 levels had a higher tumor mutational burden and homologous recombination deficiency. Moreover, MAGI1 expression levels negatively correlated with PI3K/AKT and MAPK signaling, which confirmed our in vitro observations. Pharmacological and genomic evidence indicate HDACs as regulators of MAGI1 expression. Our findings provide a new view on MAGI1 function in cancer and identify potential treatment options to improve the management of ER+ BC patients with low MAGI1 levels.

Prognostic and Predictive Value of Immune-Related Gene Expression Signatures vs Tumor-Infiltrating Lymphocytes in Early-Stage ERBB2/HER2-Positive Breast Cancer: A Correlative Analysis of the CALGB 40601 and PAMELA Trials

Importance

Both tumor-infiltrating lymphocytes (TILs) assessment and immune-related gene expression signatures by RNA profiling predict higher pathologic complete response (pCR) and improved event-free survival (EFS) in patients with early-stage ERBB2/HER2-positive breast cancer. However, whether these 2 measures of immune activation provide similar or additive prognostic value is not known.

Objective

To examine the prognostic ability of TILs and immune-related gene expression signatures, alone and in combination, to predict pCR and EFS in patients with early-stage ERBB2/HER2-positive breast cancer treated in 2 clinical trials.

Design, Setting, and Participants

In this prognostic study, a correlative analysis was performed on the Cancer and Leukemia Group B (CALGB) 40601 trial and the PAMELA trial. In the CALGB 40601 trial, 305 patients were randomly assigned to weekly paclitaxel with trastuzumab, lapatinib, or both for 16 weeks. The primary end point was pCR, with a secondary end point of EFS. In the PAMELA trial, 151 patients received neoadjuvant treatment with trastuzumab and lapatinib for 18 weeks. The primary end point was the ability of the HER2-enriched subtype to predict pCR. The studies were conducted from October 2013 to November 2015 (PAMELA) and from December 2008 to February 2012 (CALGB 40601). Data analyses were performed from June 1, 2020, to January 1, 2022.

Main Outcomes and Measures

Immune-related gene expression profiling by RNA sequencing and TILs were assessed on 230 CALGB 40601 trial pretreatment tumors and 138 PAMELA trial pretreatment tumors. The association of these biomarkers with pCR (CALGB 40601 and PAMELA) and EFS (CALGB 40601) was studied by logistic regression and Cox analyses.

Results

The median age of the patients was 50 years (IQR, 42-50 years), and 305 (100%) were women. Of 202 immune signatures tested, 166 (82.2%) were significantly correlated with TILs. In both trials combined, TILs were significantly associated with pCR (odds ratio, 1.01; 95% CI, 1.01-1.02; P = .02). In addition to TILs, 36 immune signatures were significantly associated with higher pCR rates. Seven of these signatures outperformed TILs for predicting pCR, 6 of which were B-cell related. In a multivariable Cox model adjusted for clinicopathologic factors, including PAM50 intrinsic tumor subtype, the immunoglobulin G signature, but not TILs, was independently associated with EFS (immunoglobulin G signature-adjusted hazard ratio, 0.63; 95% CI, 0.42-0.93; P = .02; TIL-adjusted hazard ratio, 1.00; 95% CI, 0.98-1.02; P = .99).

Conclusions and Relevance

Results of this study suggest that multiple B-cell-related signatures were more strongly associated with pCR and EFS than TILs, which largely represent T cells. When both TILs and gene expression are available, the prognostic value of immune-related signatures appears to be superior.

Schlafen 12 Slows TNBC Tumor Growth, Induces Luminal Markers, and Predicts Favorable Survival

The Schlafen 12 (SLFN12) protein regulates triple-negative breast cancer (TNBC) growth, differentiation, and proliferation. SLFN12 mRNA expression strongly correlates with TNBC patient survival. We sought to explore SLFN12 overexpression effects on in vivo human TNBC tumor xenograft growth and performed RNA-seq on xenografts to investigate related SLFN12 pathways. Stable SLFN12 overexpression reduced tumorigenesis, increased tumor latency, and reduced tumor volume. RNA-seq showed that SLFN12 overexpressing xenografts had higher luminal markers levels, suggesting that TNBC cells switched from an undifferentiated basal phenotype to a more differentiated, less aggressive luminal phenotype. SLFN12-overexpressing xenografts increased less aggressive BC markers, HER2 receptors ERBB2 and EGFR expression, which are not detectable by immunostaining in TNBC. Two cancer progression pathways, the NAD signaling pathway and the superpathway of cholesterol biosynthesis, were downregulated with SLFN12 overexpression. RNA-seq identified gene signatures associated with SLFN12 overexpression. Higher gene signature levels indicated good survival when tested on four independent BC datasets. These signatures behaved differently in African Americans than in Caucasian Americans, indicating a possible biological difference between these races that could contribute to the worse survival observed in African Americans with BC. These results suggest an increased SLFN12 expression modulates TNBC aggressiveness through a gene signature that could offer new treatment targets.

Immunotherapy in triple-negative breast cancer: Insights into tumor immune landscape and therapeutic opportunities

Triple-negative breast cancer (TNBC) is a clinically aggressive subtype of breast cancer that represents 15-20% of breast tumors and is more prevalent in young pre-menopausal women. It is the subtype of breast cancers with the highest metastatic potential and recurrence at the first 5 years after diagnosis. In addition, mortality increases when a complete pathological response is not achieved. As TNBC cells lack estrogen, progesterone, and HER2 receptors, patients do not respond well to hormone and anti-HER2 therapies, and conventional chemotherapy remains the standard treatment. Despite efforts to develop targeted therapies, this disease continues to have a high unmet medical need, and there is an urgent demand for customized diagnosis and therapeutics. As immunotherapy is changing the paradigm of anticancer treatment, it arises as an alternative treatment for TNBC patients. TNBC is classified as an immunogenic subtype of breast cancer due to its high levels of tumor mutational burden and presence of immune cell infiltrates. This review addresses the implications of these characteristics for the diagnosis, treatment, and prognosis of the disease. Herein, the role of immune gene signatures and tumor-infiltrating lymphocytes as biomarkers in TNBC is reviewed, identifying their application in patient diagnosis and stratification, as well as predictors of efficacy. The expression of PD-L1 expression is already considered to be predictive of response to checkpoint inhibitor therapy, but the challenges regarding its value as biomarker are described. Moreover, the rationales for different formats of immunotherapy against TNBC currently under clinical research are discussed, and major clinical trials are highlighted. Immune checkpoint inhibitors have demonstrated clinical benefit, particularly in early-stage tumors and when administered in combination with chemotherapy, with several regimens approved by the regulatory authorities. The success of antibody-drug conjugates and research on other emerging approaches, such as vaccines and cell therapies, will also be addressed. These advances give hope on the development of personalized, more effective, and safe treatments, which will improve the survival and quality of life of patients with TNBC.

Complex Disease Individual Molecular Characterization Using Infinite Sparse Graphical Independent Component Analysis

Identifying individual mechanisms involved in complex diseases, such as cancer, is essential for precision medicine. Their characterization is particularly challenging due to the unknown relationships of high-dimensional omics data and their inter-patient heterogeneity. We propose to model individual gene expression as a combination of unobserved molecular mechanisms (molecular components) that may differ between the individuals. Considering a baseline molecular profile common to all individuals, these molecular components may represent molecular pathways differing from the population background. We defined an infinite sparse graphical independent component analysis (isgICA) to identify these molecular components. This model relies on double sparseness: the source matrix sparseness defines the subset of genes involved in each molecular component, whereas the weight matrix sparseness identifies the subset of molecular components associated with each patient. As the number of molecular components is unknown but likely high, we simultaneously inferred it and the weight matrix sparseness using the beta-Bernoulli process (BBP). We simulated data from a double sparse ICA with 10/30 components with specific sparseness structures for 100/500 individuals and 500/1000/5000 genes with different noise variance levels to evaluate the reconstruction of the latent structures by our model. For all simulations, the isgICA was able to reconstruct with higher accuracy than 2 state-of-the-art methods (ica and fastICA) the number of components, the weight and source matrix sparsenesses (correlation simulated/estimated >.8). Applying our model to the expression of 1063 genes of 614 breast cancer patients, the isgICA identified 22 components. According to the source matrix, 7 of these 22 components seemed to be specifically related to 3 known molecular pathways with a prognostic effect in early breast cancer (immune system, proliferation, and stroma invasion). This proposed algorithm provides an insight into individual molecular heterogeneity to better understand complex disease mechanisms.

Cross-Resistance Among Sequential Cancer Therapeutics: An Emerging Issue

Over the past two decades, cancer treatment has benefited from having a significant increase in the number of targeted drugs approved by the United States Food and Drug Administration. With the introduction of targeted therapy, a great shift towards a new era has taken place that is characterized by reduced cytotoxicity and improved clinical outcomes compared to traditional chemotherapeutic drugs. At present, targeted therapies and other systemic anti-cancer therapies available (immunotherapy, cytotoxic, endocrine therapies and others) are used alone or in combination in different settings (neoadjuvant, adjuvant, and metastatic). As a result, it is not uncommon for patients affected by an advanced malignancy to receive subsequent anti-cancer therapies. In this challenging complexity of cancer treatment, the clinical pathways of real-life patients are often not as direct as predicted by standard guidelines and clinical trials, and cross-resistance among sequential anti-cancer therapies represents an emerging issue. In this review, we summarize the main cross-resistance events described in the diverse tumor types and provide insight into the molecular mechanisms involved in this process. We also discuss the current challenges and provide perspectives for the research and development of strategies to overcome cross-resistance and proceed towards a personalized approach.

Protein expression of the gp78 E3-ligase predicts poor breast cancer outcome based on race

Women of African ancestry suffer higher rates of breast cancer mortality compared to all other groups in the United States. Though the precise reasons for these disparities remain unclear, many recent studies have implicated a role for differences in tumor biology. Using an epitope-validated antibody against the endoplasmic reticulum-associated degradation (ERAD) E3 ubiquitin ligase, gp78, we show that elevated levels of gp78 in patient breast cancer cells predict poor survival. Moreover, high levels of gp78 are associated with poor outcomes in both ER-positive and ER-negative tumors, and breast cancers expressing elevated amounts of gp78 protein are enriched in gene expression pathways that influence cell cycle, metabolism, receptor-mediated signaling, and cell stress response pathways. In multivariate analysis adjusted for subtype and grade, gp78 protein is an independent predictor of poor outcomes in women of African ancestry. Furthermore, gene expression signatures, derived from patients stratified by gp78 protein expression, are strong predictors of recurrence and pathological complete response in retrospective clinical trial data and share many common features with gene sets previously identified to be overrepresented in breast cancers based on race. These findings implicate a prominent role for gp78 in tumor progression and offer new insights into our understanding of racial differences in breast cancer outcomes.

Expression of NOTCH1, NOTCH4, HLA-DMA and HLA-DRA is synergistically associated with T cell exclusion, immune checkpoint blockade efficacy and recurrence risk in ER-negative breast cancer

PURPOSE

Reliable biomarkers to predict the outcome and treatment response of estrogen receptor (ER)-negative breast cancer (BC) are urgently needed. Since immune-related signaling plays an important role in the tumorigenesis of ER-negative BC, we asked whether Notch genes, alone or in combination with other immune genes, can be used to predict the clinical outcome and immune checkpoint blockade (ICB) for this type of cancer.

METHODS

We analyzed transcriptome data of 6918 BC samples from five independent cohorts, 81 xenograft triple-negative BC tumors that respond differently to ICB treatment and 754 samples of different cancer types from patients treated with ICB agents.

RESULTS

We found that among four Notch genes, the expression levels of NOTCH1 and NOTCH4 were positively associated with recurrence of ER-negative BC, and that combined expression of these two genes (named Notch14) further enhanced this association, which was comparable with that of the Notch pathway signature. Analysis of 1182 immune-related genes revealed that the expression levels of most HLA genes, particularly HLA-DMA and -DRA, were reversely associated with recurrence in ER-negative BC with low, but not high Notch14 expression. A combined expression signature of NOTCH1, NOTCH4, HLA-DMA and HLA-DRA was more prognostic for ER-negative and triple-negative BCs than previously reported immune-related signatures. Furthermore, we found that the expression levels of these four genes were also synergistically associated with T cell exclusion score, infiltration of specific T cells and ICB efficacy in ER-negative BC, thereby providing a potential molecular mechanism for the synergistic effect of these genes on BC.

CONCLUSIONS

Our data indicate that a gene signature composed of NOTCH1, NOTCH4, HLA-DMA and HLA-DRA may serve as a potential promising biomarker for predicting ICB therapy efficacy and recurrence in ER-negative/triple-negative BCs.

Tumor-Infiltrating Lymphocytes Improve Magee Equation-Based Prediction of Pathologic Complete Response in HR-Positive/HER2-Negative Breast Cancer

OBJECTIVES

Magee equation 3 (ME3) is predictive of the pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in patients with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer but with insufficient predictive performance. This study was designed to improve predictive ability by combining ME3 with additional clinicopathologic markers.

METHODS

We retrospectively enrolled 460 patients with HR-positive/HER2-negative breast cancer from 2 centers. We obtained baseline characteristics, the ME3 score, and the number of stromal tumor-infiltrating lymphocytes (sTILs). After performing a logistic regression analysis, a predictive nomogram was built and validated externally.

RESULTS

ME3 score (adjusted odds ratio [OR], 1.14 [95% confidence interval (CI), 1.10-1.17]; P < .001) and TILs (adjusted OR, 5.21 [95% CI, 3.33-8.14]; P < .001) were independently correlated with pCR. The nomogram (named ME3+) was established using ME3 and sTILs, and it demonstrated an area under the curve of 0.816 and 0.862 in internal and external validation, respectively, outperforming the ME3 score alone. sTILs and ME3 scores were also found to be positively correlated across the entire cohort (P < .001).

CONCLUSIONS

The combination of sTILs and ME3 score potentially shows better performance for predicting pCR than ME3 alone. Larger validations are required for widespread application of ME3+ nomogram in NAC settings for HR-positive/HER2-negative breast cancer.

Clinical and Molecular Characteristics of ER-Positive Ultralow Risk Breast Cancer Tumors Identified by the 70-Gene Signature

The metastatic potential of estrogen receptor (ER)-positive breast cancers is heterogenous and distant recurrences occur months to decades after primary diagnosis. We have previously shown that patients with tumors classified as ultralow risk by the 70-gene signature have a minimal long-term risk of fatal breast cancer. Here, we evaluate the previously unexplored underlying clinical and molecular characteristics of ultralow risk tumors in 538 ER-positive patients from the Stockholm tamoxifen randomized trial (STO-3). Out of the 98 ultralow risk tumors, 89% were luminal A molecular subtype, whereas 26% of luminal A tumors were of ultralow risk. Compared with other ER-positive tumors, ultralow risk tumors were significantly (Fisher's test, P<0.05) more likely to be of smaller tumor size, lower grade, progesterone receptor (PR)-positive, human epidermal growth factor 2 (HER2)-negative and have low Ki-67 levels (proliferation-marker). Moreover, ultralow risk tumors showed significantly lower expression scores of multi-gene modules associated with the AKT/mTOR-pathway, proliferation (AURKA), HER2/ERBB2-signaling, IGF1-pathway, PTEN-loss, and immune response (IMMUNE1 and IMMUNE2), and higher expression scores of the PIK3CA-mutation-associated module. Furthermore, 706 genes were significantly (FDR<0.001) differentially expressed in ultralow risk tumors, including lower expression of genes involved in immune response, PI3K/Akt/mTOR-pathway, histones, cell cycle, DNA repair, apoptosis, and higher expression of genes coding for epithelial-to-mesenchymal transition, and homeobox proteins, among others. In conclusion, ultralow risk tumors, associated with minimal long-term risk of fatal disease, differ from other ER-positive tumors, including luminal A molecular subtype tumors. Identification of these characteristics is important to improve our prediction of non-fatal versus fatal breast cancer. This article is protected by copyright. All rights reserved.

Evaluation of tumor immune contexture among intrinsic molecular subtypes helps to predict outcome in early breast cancer

Background

The prognosis of early breast cancer is linked to clinic-pathological stage and the molecular characteristics of intrinsic tumor cells. In some patients, the amount and quality of tumor-infiltrating immune cells appear to affect long term outcome. We aimed to propose a new tool to estimate immune infiltrate, and link these factors to patient prognosis according to breast cancer molecular subtypes.

Methods

We performed in silico analyses in more than 2800 early breast cancer transcriptomes with corresponding clinical annotations. We first developed a new gene expression deconvolution algorithm that accurately estimates the quantity of immune cell populations (tumor immune contexture, TIC) in tumors. Then, we studied associations between these immune profiles and relapse-free and overall survival among the different intrinsic molecular subtypes of breast cancer defined by PAM50 classification.

Results

TIC estimates the abundance of 15 immune cell subsets. Both myeloid and lymphoid subpopulations show different spread among intrinsic molecular breast cancer subtypes. A high abundance of myeloid cells was associated with poor outcome, while lymphoid cells were associated with favorable prognosis. Unsupervised clustering describing the 15 immune cell subsets revealed four subgroups of breast tumors associated with distinct patient survival, but independent from PAM50. Adding this information to clinical stage and PAM50 strongly improves the prediction of relapse or death.

Conclusions

Our findings make it possible to refine the survival stratification of early patients with breast cancer by incorporating TIC in addition to PAM50 and clinical tumor burden in a prognostic model validated in training and validation cohorts.

NEFM DNA methylation correlates with immune infiltration and survival in breast cancer

Background

This study aims to determine whether NEFM (neurofilament medium) DNA methylation correlates with immune infiltration and prognosis in breast cancer (BRCA) and to explore NEFM-connected immune gene signature.

Methods

NEFM transcriptional expression was analyzed in BRCA and normal breast tissues using Oncomine and Tumor Immune Estimation Resource (TIMER) databases. The relationship between NEFM DNA methylation and NEFM transcriptional expression was investigated in TCGA. Potential influence of NEFM DNA methylation/expression on clinical outcome was evaluated using TCGA BRCA, The Human Protein Atlas and Kaplan–Meier plotter databases. Association of NEFM transcriptional expression/DNA methylation with cancer immune infiltration was investigated using TIMER and TISIDB databases.

Results

High expression of NEFM correlated with better overall survival (OS) and recurrence-free survival (RFS) in TCGA BRCA and Kaplan–Meier plotter, whereas NEFM DNA methylation with worse OS in TCGA BRCA. NEFM transcriptional expression negatively correlated with DNA methylation. NEFM DNA methylation significantly negatively correlated with infiltrating levels of B, CD8⁺ T/CD4⁺ T cells, macrophages, neutrophils and dendritic cells in TIMER and TISIDB. NEFM expression positively correlated with macrophage infiltration in TIMER and TISIDB. After adjusted with tumor purity, NEFM expression weekly negatively correlated with infiltration level of B cells, whereas positively correlated with CD8⁺ T cell infiltration in TIMER gene modules. NEFM expression/DNA methylation correlated with diverse immune markers in TCGA and TISIDB.

Conclusions

NEFM low-expression/DNA methylation correlates with poor prognosis. NEFM expression positively correlates with macrophage infiltration. NEFM DNA methylation strongly negatively correlates with immune infiltration in BRCA. Our study highlights novel potential functions of NEFM expression/DNA methylation in regulation of tumor immune microenvironment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01096-4.

Neoadjuvant immunotherapy in breast cancer: a paradigm shift?

Despite advances in clinical management, a proportion of patients with early-stage triple-negative breast cancer (TNBC) recur after local treatment. The concept of neoadjuvant systemic therapy has been widely adopted to improve clinical outcomes of patients with TNBC and other breast tumour types. Recently, promising data were reported from the first prospective phase III, randomised trial assessing neoadjuvant chemotherapy combined with the programmed cell death protein 1 (PD-1) inhibitor pembrolizumab versus placebo in patients with early-stage TNBC. The addition of pembrolizumab resulted in a significant increase in pathologic complete response (pCR) rates. Similarly, in the IMpassion031 trial, the use of atezolizumab in combination with neoadjuvant chemotherapy in patients with early-stage TNBC led to improved pCR rates compared to placebo, regardless of programmed death ligand 1 (PD-L1) expression. Ongoing trials are testing other PD-1/PD-L1 inhibitors in combination with neoadjuvant chemotherapy in TNBC and other tumour subtypes. However, not all patients benefit from the addition of immunotherapy, while a proportion of patients experiences serious adverse events. It is critical to identify predictive biomarkers of response, to accurately select patients who will benefit from immunotherapy, thus sparing the rest from ineffective treatments with unnecessary toxicity and treatment costs. In this review, we summarise the literature on reported and ongoing neoadjuvant clinical trials evaluating immunotherapy in breast cancer.

Mechanisms of CDK4/6 Inhibitor Resistance in Luminal Breast Cancer

As a new-generation CDK inhibitor, a CDK4/6 inhibitor combined with endocrine therapy has been successful in the treatment of advanced estrogen receptor–positive (ER+) breast cancer. Although there has been overall progress in the treatment of cancer, drug resistance is an emerging cause for breast cancer–related death. Overcoming CDK4/6 resistance is an urgent problem. Overactivation of the cyclin-CDK-Rb axis related to uncontrolled cell proliferation is the main cause of CDK4/6 inhibitor resistance; however, the underlying mechanisms need to be clarified further. We review various resistance mechanisms of CDK4/6 inhibitors in luminal breast cancer. The cell signaling pathways involved in therapy resistance are divided into two groups: upstream response mechanisms and downstream bypass mechanisms. Finally, we discuss possible strategies to overcome CDK4/6 inhibitor resistance and identify novel resistance targets for future clinical application.

Meta-analysis of gene expression profiling reveals novel basal gene signatures in MCF-10A cells transformed with cadmium

Cadmium (Cd²⁺) is an environmental toxicant and a human carcinogen. Several studies show an association of Cd²⁺ exposure to the development of breast cancer. Previously, we have transformed the immortalized non-tumorigenic cell line MCF-10A with Cd²⁺ and have demonstrated that the transformed cells have anchorage independent growth. In a separate study, we showed that transformation of the immortalized urothelial cells with the environmental carcinogen arsenite (As³⁺) results in an increase in expression of genes associated with the basal subtype of bladder cancer. In this study, we determined if transformation of the MCF-10A cells with Cd²⁺ would have a similar effect on the expression of basal genes. The results of our study indicate that there is a decrease in expression of genes associated with keratinization and cornification and this gene signature includes the genes associated with the basal subtype of breast cancer. An analysis of human breast cancer databases indicates an increased expression of this gene signature is associated with a positive correlation to patient survival whereas a reduced expression/absence of this gene signature is associated with poor patient survival. Thus, our study suggests that transformation of the MCF-10A cells with Cd²⁺ produces a decreased basal gene expression profile that correlates to patient outcome.

Schlafen 12 Is Prognostically Favorable and Reduces C-Myc and Proliferation in Lung Adenocarcinoma but Not in Lung Squamous Cell Carcinoma

Schlafen 12 (SLFN12) is an intermediate human Schlafen that induces differentiation in enterocytes, prostate, and breast cancer. We hypothesized that SLFN12 influences lung cancer biology. We investigated survival differences in high versus low SLFN12-expressing tumors in two databases. We then adenovirally overexpressed SLFN12 (AdSLFN12) in HCC827, H23, and H1975 cells to model lung adenocarcinoma (LUAD), and in H2170 and HTB-182 cells representing lung squamous cell carcinoma (LUSC). We analyzed proliferation using a colorimetric assay, mRNA expression by RT-qPCR, and protein by Western blot. To further explore the functional relevance of SLFN12, we correlated SLFN12 with seventeen functional oncogenic gene signatures in human tumors. Low tumoral SLFN12 expression predicted worse survival in LUAD patients, but not in LUSC. AdSLFN12 modulated expression of SCGB1A1, SFTPC, HOPX, CK-5, CDH1, and P63 in a complex fashion in these cells. AdSLFN12 reduced proliferation in all LUAD cell lines, but not in LUSC cells. SLFN12 expression inversely correlated with expression of a myc-associated gene signature in LUAD, but not LUSC tumors. SLFN12 overexpression reduced c-myc protein in LUAD cell lines but not in LUSC, by inhibiting c-myc translation. Our results suggest SLFN12 improves prognosis in LUAD in part via a c-myc-dependent slowing of proliferation.

Gene Expression Assay in the Management of Early Breast Cancer

The addition of adjuvant chemotherapy to hormonal therapy is often considered questionable in patients with estrogen receptor-positive early breast cancer. Low risk of disease relapse after endocrine treatment alone and/or a low sensitivity to chemotherapy are reasons behind not all patients benefit from chemotherapy. Most of the patients could be exposed to unnecessary treatment- related adverse events and health care costs when treatment decision-making is based only on classical clinical histological features. Gene expression profile has been developed to refine physician's decision-making process and to tailor personalized treatment to patients. In particular, these tests are designed to spare patients the side effects of unnecessary treatment, and ensure that adjuvant chemotherapy is correctly recommended to patients with early breast cancer. In this review, we will discuss the main diagnostic tests and their potential clinical applications (Oncotype DX, MammaPrint, PAM50/Prosigna, EndoPredict, MapQuant Dx, IHC4, and Theros-Breast Cancer Gene Expression Ratio Assay).

Therapeutic Strategies for Human Epidermal Receptor-2 Positive Metastatic Breast Cancer: A Literature Review

Breast cancer is a frequently occurring malignancy in women. Immunologically, breast cancers can be classified into four subtypes depending on the types of receptors present and their expression profiles. These are estrogen positive, progesterone positive, human epidermal growth factor receptor type 2 (HER2) positive, and triple-negative as identified by immunohistochemistry. This classification is the basis of response to treatment, prognosis, and survival. With the identification of HER2 receptor overexpression, targeted therapies with anti-HER2 agents have been developed. The first-line therapy approved for HER2 positive tumors is trastuzumab and pertuzumab linked to taxane and further treatment with an antibody-drug conjugate to achieve satisfactory outcomes. Tyrosine kinase overexpression can be treated with lapatinib, which has also been approved for improving survival and is used in combination with capecitabine. Acquired resistance in HER2 positive tumors is shown in many cases due to genetic or epigenetic modifications. Therefore, it is very important to plan therapeutic strategies and design effective treatment approaches. For a long time, only two agents, trastuzumab and lapatinib, have been approved by the Food and Drug Administration (FDA) for the treatment of HER2 positive breast cancers. There has been no appropriate treatment for trastuzumab resistance and its failure to reduce tumor growth. Lapatinib was approved by the FDA in 2007 for HER2 positive breast cancer. Three existing therapy options after trastuzumab resistance was proposed by clinicians: continuation of trastuzumab, starting therapy with lapatinib, and the synergistic use of trastuzumab and lapatinib.

There have been several effective therapies proposed for HER2 positive breast cancers in correlation with clinical trials. Discovering the mechanisms of trastuzumab resistance would increase its response to therapy and better clinical outcome. Clinicians are being continuously challenged by the resistance mechanisms and bioavailability of the drugs in the treatment of metastatic breast cancers. The addition of new drugs to the chemotherapeutic regimen increases the complexity, burden of side effects, and chances of relapse. Novel anti-HER2 agents have been directed towards therapy making a major paradigm shift.

Gene signature-based prediction of triple-negative breast cancer patient response to Neoadjuvant chemotherapy

Neoadjuvant chemotherapy is the current standard of care for large, advanced, and/or inoperable tumors, including triple‐negative breast cancer. Although the clinical benefits of neoadjuvant chemotherapy have been illustrated through numerous clinical trials, more than half of the patients do not experience therapeutic benefit and needlessly suffer from side effects. Currently, no clinically applicable biomarkers are available for predicting neoadjuvant chemotherapy response in triple‐negative breast cancer; the discovery of such a predictive biomarker or marker profile is an unmet need. In this study, we introduce a generic computational framework to calculate a response‐probability score (RPS), based on patient transcriptomic profiles, to predict their response to neoadjuvant chemotherapy. We first validated this framework in ER‐positive breast cancer patients and showed that it predicted neoadjuvant chemotherapy response with equal performance to several clinically used gene signatures, including Oncotype DX and MammaPrint. Then, we applied this framework to triple‐negative breast cancer data and, for each patient, we calculated a response probability score (TNBC‐RPS). Our results indicate that the TNBC‐RPS achieved the highest accuracy for predicting neoadjuvant chemotherapy response compared to previously proposed 143 gene signatures. When combined with additional clinical factors, the TNBC‐RPS achieved a high prediction accuracy for triple‐negative breast cancer patients, which was comparable to the prediction accuracy of Oncotype DX and MammaPrint in ER‐positive patients. In conclusion, the TNBC‐RPS accurately predicts neoadjuvant chemotherapy response in triple‐negative breast cancer patients and has the potential to be clinically used to aid physicians in stratifying patients for more effective neoadjuvant chemotherapy.

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.

Accounting for grouped predictor variables or pathways in high-dimensional penalized Cox regression models

BACKGROUND

The standard lasso penalty and its extensions are commonly used to develop a regularized regression model while selecting candidate predictor variables on a time-to-event outcome in high-dimensional data. However, these selection methods focus on a homogeneous set of variables and do not take into account the case of predictors belonging to functional groups; typically, genomic data can be grouped according to biological pathways or to different types of collected data. Another challenge is that the standard lasso penalisation is known to have a high false discovery rate.

RESULTS

We evaluated different penalizations in a Cox model to select grouped variables in order to further penalize variables that, in addition to having a low effect, belong to a group with a low overall effect; and to favor the selection of variables that, in addition to having a large effect, belong to a group with a large overall effect. We considered the case of prespecified and disjoint groups and proposed diverse weights for the adaptive lasso method. In particular we proposed the product Max Single Wald by Single Wald weighting (MSW*SW) which takes into account the information of the group to which it belongs and of this biomarker. Through simulations, we compared the selection and prediction ability of our approach with the standard lasso, the composite Minimax Concave Penalty (cMCP), the group exponential lasso (gel), the Integrative L1-Penalized Regression with Penalty Factors (IPF-Lasso), and the Sparse Group Lasso (SGL) methods. In addition, we illustrated the methods using gene expression data of 614 breast cancer patients.

CONCLUSIONS

The adaptive lasso with the MSW*SW weighting method incorporates both the information in the grouping structure and the individual variable. It outperformed the competitors by reducing the false discovery rate without severely increasing the false negative rate.

Identification of a prognostic LncRNA signature for ER-positive, ER-negative and triple-negative breast cancers

PURPOSE

The development of multi-gene signatures has led to improvements in identification of breast cancer patients at high risk of recurrence. The prognostic power of commercially available gene signatures is mostly restricted to estrogen receptor (ER)-positive breast cancer. On the contrary, immune-related gene signatures predict prognosis only in ER-negative breast cancer. This study aimed to develop a better prognostic signature for breast cancer.

METHODS

The expressions of long non-coding RNA (lncRNA) genes from 30 independent microarray datasets with a total of 4813 samples were analyzed. A prognostic lncRNA signature was developed based on likelihood-ratio Cox regression analysis. Survival analysis was used to compare the prognostic efficiencies of our signature and 10 previously reported prognostic gene signatures.

RESULTS

Cox regression analysis on 30 independent datasets showed that the 6-lncRNA signature identified in this study performed as well as five commercially available signatures in recurrence prediction for ER-positive breast cancer. In ER-negative breast cancer, this lncRNA signature was as prognostic as three immune-related gene signatures. Moreover, our lncRNA signature also demonstrated a good capacity to predict recurrence risk for triple-negative breast cancer. Function analysis showed that several lncRNAs in this signature were probably involved in cell proliferation and immune processes.

CONCLUSIONS

A six-LncRNA signature was identified that is prognostic for ER-positive, ER-negative, and triple-negative breast cancers and thus deserves further validation in prospective studies.

Tumor-Infiltrating Lymphocytes in Patients Receiving Trastuzumab/Pertuzumab-Based Chemotherapy: A TRYPHAENA Substudy

Background

There is an urgent requirement to identify biomarkers to tailor treatment in human epidermal growth factor receptor 2 (HER2)-amplified early breast cancer treated with trastuzumab/pertuzumab-based chemotherapy.

Methods

Among the 225 patients randomly assigned to trastuzumab/pertuzumab concurrently or sequentially with an anthracycline-containing regimen or concurrently with an anthracycline-free regimen in the Tryphaena trial, we determined the percentage of tumor-infiltrating lymphocytes (TILs) at baseline in 213 patients, of which 126 demonstrated a pathological complete response (pCR; ypT0/is ypN0), with 28 demonstrating event-free survival (EFS) events. We investigated associations between baseline TIL percentage and either pCR or EFS after adjusting for clinicopathological characteristics using logistic and Cox regression models, respectively. To understand TIL biology, we evaluated associations between baseline TILs and baseline tumor gene expression data (800 gene set by NanoString) in a subset of 173 patients. All statistical tests were two-sided.

Results

Among the patients with measurable TILs at baseline, the median level was 14.1% (interquartile range = 7.1%-32.4%). After adjusting for clinicopathological characteristics, baseline percentage TIL was not associated with pCR (adjusted odds ratio [aOR] for every 10-percentage unit increase in TILs = 1.12, 95% confidence interval [CI] = 0.95 to 1.31, P = .17). At a median follow-up of 4.7 years, for every increase in baseline TILs of 10%, there was a 25% reduction in the hazard for an EFS event (aOR = 0.75, 95% CI = 0.56 to 1.00, P = .05) after adjusting for baseline clinicopathological characteristics and pCR. Additionally, genes associated with epithelial-mesenchymal transition, angiogenesis, and T-cell inhibition such as SNAIL1, ZEB1, NOTCH3, and B7-H3 were statistically significantly inversely correlated with percentage TIL.

Conclusions

Baseline TIL percentage provides independent prognostic information in patients treated with trastuzumab/pertuzumab-based neoadjuvant chemotherapy. However, further validation is required.

Prognostic and Predictive Impact of Beta-2 Adrenergic Receptor Expression in HER2-Positive Breast Cancer

BACKGROUND

Beta-2 adrenergic receptor (ADRB2) mediates proliferation and treatment resistance in preclinical models of human epidermal growth factor receptor 2 positive (HER2+) breast cancer. We evaluated ADRB2 gene expression as a prognostic and predictive biomarker in patients with HER2+ early breast cancer.

METHODS

ADRB2 expression was retrieved from HER2+ patients enrolled in the FinHer study (N = 202), and 2 public datasets containing data from patients with HER2+ early breast cancer: one including patients who did not receive systemic treatment (disease-free survival [DFS] dataset; n = 175) and another including patients who received neoadjuvant treatment (pathologic complete response [pCR] dataset; n = 207). Survival was estimated with Kaplan-Meier method and Cox regression was used for uni-multivariate analyses. ADRB2 expression was correlated with several gene signatures.

RESULTS

ADRB2 high expression was associated with improved DFS rates in HER2+ patients (hazard ratio [HR] 0.52; 95% confidence interval [CI] 0.32-0.84; P = .0068). No association between ADRB2 expression and pCR was observed (odds ratio 1.14; 95% CI, 0.63-2.10; P = .67). No association between ADRB2 and relapse-free survival (RFS) was observed in HER2+ patients enrolled in the FinHer study (HR 0.93; 95% CI, 0.69-1.25; P = .61). ADRB2 was associated with a low expression of angiogenesis-related (vascular endothelial growth factor -0.38, P < .001) and proliferation-related (aurora kinase A -0.36, P < .001; genomic grade index -0.028, P < .001; signal transducers and activators of transcription -0.17, P < .001) genes; and a high expression of immune-related genes (Perez +0.45, P < .001; STAT1 +0.28, P < .001; immune response gene expression module +0.29, P < .001).

CONCLUSIONS

Opposing our initial hypothesis, a high ADRB2 expression may be a favorable prognostic factor in patients with HER2+ early breast cancer. This association appears to be mediated by antiproliferative, antiangiogenic, and immunogenic effects of ADRB2.

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.

Reactive stroma and trastuzumab resistance in HER2-positive early breast cancer

We investigated the value of reactive stroma as a predictor for trastuzumab resistance in patients with early HER2-positive breast cancer receiving adjuvant therapy. The pathological reactive stroma and the mRNA gene signatures that reflect reactive stroma in 209 HER2-positive breast cancer samples from the FinHer adjuvant trial were evaluated. Levels of stromal gene signatures were determined as a continuous parameter, and pathological reactive stromal findings were defined as stromal predominant breast cancer (SPBC; ≥50% stromal) and correlated with distant disease-free survival. Gene signatures associated with reactive stroma in HER2-positive early breast cancer (N = 209) were significantly associated with trastuzumab resistance in estrogen receptor (ER)-negative tumors (hazard ratio [HR] = 1.27 p interaction = 0.014 [DCN], HR = 1.58, p interaction = 0.027 [PLAU], HR = 1.71, p interaction = 0.019 [HER2STROMA, novel HER2 stromal signature]), but not in ER-positive tumors (HR = 0.73 p interaction = 0.47 [DCN], HR = 0.71, p interaction = 0.73 [PLAU], HR = 0.84; p interaction = 0.36 [HER2STROMA]). Pathological evaluation of HER2-positive/ER-negative tumors suggested an association between SPBC and trastuzumab resistance. Reactive stroma did not correlate with tumor-infiltrating lymphocytes (TILs), and the expected benefit from trastuzumab in patients with high levels of TILs was pronounced only in tumors with low stromal reactivity (SPBC <50%). In conclusion, reactive stroma in HER2-positive/ER-negative early breast cancer tumors may predict resistance to adjuvant trastuzumab therapy.

MAGI1, a New Potential Tumor Suppressor Gene in Estrogen Receptor Positive Breast Cancer

Membrane-associated guanylate kinase (MAGUK) with inverted domain structure-1 (MAGI1) is an intracellular adaptor protein that stabilizes epithelial junctions consistent with a tumor suppressive function in several cancers of epithelial origin. Here we report, based on experimental results and human breast cancer (BC) patients’ gene expression data, that MAGI1 is highly expressed and acts as tumor suppressor in estrogen receptor (ER)⁺/HER2⁻ but not in HER2⁺ or triple negative breast cancer (TNBC). Within the ER⁺/HER2⁻ subset, high MAGI1 expression associates with ESR1 and luminal genes GATA3 and FOXA1 expression and better prognosis, while low MAGI1 levels correlates with higher histological grade, more aggressive phenotype and worse prognosis. Experimentally, MAGI1 downregulation in the ER⁺ human BC cells MCF7 impairs ER expression and signaling, promotes cell proliferation, and reduces apoptosis and epithelial differentiation. MAGI1 downregulation in the ER⁺ murine BC cell line 67NR accelerates primary tumor growth and enhances experimental lung metastasis formation. MAGI1 expression is upregulated by estrogen/ER, downregulated by prostaglandin E2/COX-2axis, and negatively correlates with inflammation in ER⁺/HER2⁻ BC patients. Taken together, we show that MAGI1 is a new potential tumor suppressor in ER⁺/HER2⁻ breast cancer with possible prognostic value for the identification of patients at high-risk of relapse within this subset.

Comprehensive evaluation of methods to assess overall and cell-specific immune infiltrates in breast cancer

Background

Breast cancer (BC) immune infiltrates play a critical role in tumor progression and response to treatment. Besides stromal tumor infiltrating lymphocytes (sTILs) which have recently reached level 1B evidence as a prognostic marker in triple negative BC, a plethora of methods to assess immune infiltration exists, and it is unclear how these compare to each other and if they can be used interchangeably.

Methods

Two experienced pathologists scored sTIL, intra-tumoral TIL (itTIL), and 6 immune cell types (CD3⁺, CD4⁺, CD8⁺, CD20⁺, CD68⁺, FOXP3⁺) in the International Cancer Genomics Consortium breast cancer cohort using hematoxylin and eosin-stained (n = 243) and immunohistochemistry-stained tissue microarrays (n = 254) and whole slides (n = 82). The same traits were evaluated using transcriptomic- and methylomic-based deconvolution methods or signatures.

Results

The concordance correlation coefficient (CCC) between pathologists for sTIL was very good (0.84) and for cell-specific immune infiltrates slightly lower (0.63–0.66). Comparison between tissue microarray and whole slide pathology scores revealed systematically higher values in whole slides (ratio 2.60–5.98). The Spearman correlations between microscopic sTIL and transcriptomic- or methylomic-based assessment of immune infiltrates were highly variable (r = 0.01–0.56). Similar observations were made for cell type-specific quantifications (r = 0.001–0.54). We observed a strong inter-method variability between the omics-derived estimations, which is further cell type dependent. Finally, we demonstrated that most methods more accurately identify highly infiltrated (sTIL ≥ 60%; area under the curve, AUC, 0.64–0.99) as compared to lowly infiltrated tumors (sTIL ≤ 10%; AUC 0.52–0.82).

Conclusions

There is a lower inter-pathologist concordance for cell-specific quantification as compared to overall infiltration quantification. Microscopic assessments are underestimated when considering small cores (tissue microarray) instead of whole slides. Results further highlight considerable differences between the microscopic-, transcriptomic-, and methylomic-based methods in the assessment of overall and cell-specific immune infiltration in BC. We therefore call for extreme caution when assessing immune infiltrates using current methods and emphasize the need for standardized immune characterization beyond TIL.

PAK4 suppresses RELB to prevent senescence-like growth arrest in breast cancer

Overcoming cellular growth restriction, including the evasion of cellular senescence, is a hallmark of cancer. We report that PAK4 is overexpressed in all human breast cancer subtypes and associated with poor patient outcome. In mice, MMTV-PAK4 overexpression promotes spontaneous mammary cancer, while PAK4 gene depletion delays MMTV-PyMT driven tumors. Importantly, PAK4 prevents senescence-like growth arrest in breast cancer cells in vitro, in vivo and ex vivo, but is not needed in non-immortalized cells, while PAK4 overexpression in untransformed human mammary epithelial cells abrogates H-RAS-V12-induced senescence. Mechanistically, a PAK4 – RELB - C/EBPβ axis controls the senescence-like growth arrest and a PAK4 phosphorylation residue (RELB-Ser151) is critical for RELB-DNA interaction, transcriptional activity and expression of the senescence regulator C/EBPβ. These findings establish PAK4 as a promoter of breast cancer that can overcome oncogene-induced senescence and reveal a selective vulnerability of cancer to PAK4 inhibition.

Oncogene induced senescence protects cells from unrestricted growth and cancer. Here, the authors show that PAK4 overrides this senescence in breast cancer cells through phosphorylation of RELB, thereby inhibiting transcription of the senescence regulator C/EBPβ.

Schlafen-11 expression is associated with immune signatures and basal-like phenotype in breast cancer

PURPOSE

Breast cancer (BC) is a heterogeneous disorder, with variable response to systemic chemotherapy. Likewise, BC shows highly complex immune activation patterns, only in part reflecting classical histopathological subtyping. Schlafen-11 (SLFN11) is a nuclear protein we independently described as causal factor of sensitivity to DNA damaging agents (DDA) in cancer cell line models. SLFN11 has been reported as a predictive biomarker for DDA and PARP inhibitors in human neoplasms. SLFN11 has been implicated in several immune processes such as thymocyte maturation and antiviral response through the activation of interferon signaling pathway, suggesting its potential relevance as a link between immunity and cancer. In the present work, we investigated the transcriptional landscape of SLFN11, its potential prognostic value, and the clinico-pathological associations with its variability in BC.

METHODS

We assessed SLFN11 determinants in a gene expression meta-set of 5061 breast cancer patients annotated with clinical data and multigene signatures.

RESULTS

We found that 537 transcripts are highly correlated with SLFN11, identifying "immune response", "lymphocyte activation", and "T cell activation" as top Gene Ontology processes. We established a strong association of SLFN11 with stromal signatures of basal-like phenotype and response to chemotherapy in estrogen receptor negative (ER-) BC. We identified a distinct subgroup of patients, characterized by high SLFN11 levels, ER- status, basal-like phenotype, immune activation, and younger age. Finally, we observed an independent positive predictive role for SLFN11 in BC.

CONCLUSIONS

Our findings are suggestive of a relevant role for SLFN11 in BC and its immune and molecular variability.

Immunotherapy in breast cancer

The idea of using the immune system to fight cancer is over 100 years old. A new molecular approach led to a better understanding of the immune system. Checkpoint regulation, understanding the roles of Tregs, Th1, and Th2, development of Chimeric antigen receptor (CAR)-T cells, as well as regulation of dendritic cells and macrophages, are just a few examples of our understating that has also led to the discovery of immune checkpoint inhibitors (ICIs) and modulators. This led the Nobel Prize committee in 2018, to award Dr. James P. Allison the Nobel Prize in medicine for the discovery of Cytotoxic T-lymphocyte-associated antigen-4, and Dr. Tasuku Honjo for the discovery of programmed cell death-1 (PD-1)/PD-1-ligand (PDL-1). Several ICIs are already approved by the regulatory authorities, and many more are currently used in studies of several solid tumors and hematologic malignancies. Positive studies have led to the US Food and Drug Administration (FDA) and European Medicines Agency approval of a number of these compounds, but none to date are approved in breast cancer (BC). Moreover, PD-1/PDL-1, MSI high (and dMMR), and tumor mutational burden are the currently “best” predictive markers for benefit from immunotherapy. BCs have some of these markers positive only in subsets but less frequently expressed than most other solid tumors, for example, malignant melanoma or non-small cell lung cancer. To improve the potential efficacy of ICI in BC, the addition of chemotherapy was one of the strategies. Many early and large clinical trials in all phases are underway in BC. We will discuss the role of immune system in BC editing, and the potential impact of immunotherapy in BC outcomes.

Plasma miRNA Levels for Predicting Therapeutic Response to Neoadjuvant Treatment in HER2-positive Breast Cancer: Results from the NeoALTTO Trial

PURPOSE

To investigate the potential of circulating-miRNAs (ct-miRNA) as noninvasive biomarkers to predict the efficacy of single/dual HER2-targeted therapy in the NeoALTTO study.

EXPERIMENTAL DESIGN

Patients with plasma samples at baseline (T0) and/or after 2 weeks (T1) of treatment were randomized into training (n = 183) and testing (n = 246) sets. RT-PCR-based high-throughput miRNA profiling was employed in the training set. After normalization, ct-miRNAs associated with pathologic complete response (pCR) were identified by univariate analysis. Multivariate logistic regression models were implemented to generate treatment-specific signatures at T0 and T1, which were evaluated by RT-PCR in the testing set. Event-free survival (EFS) according to ct-miRNA signatures was estimated by Kaplan-Meier method and Cox regression model.

RESULTS

In the training set, starting from 51 ct-miRNAs associated with pCR, six signatures with statistically significant predictive capability in terms of area under the ROC curve (AUC) were identified. Four signatures were confirmed in the testing set: lapatinib at T0 and T1 [AUC 0.86; 95% confidence interval (CI), 0.73-0.98 and 0.71 (0.55-0.86)], respectively; trastuzumab at T1 (0.81; 0.70-0.92); lapatinib + trastuzumab at T1 (0.67; 0.51-0.83). These signatures were confirmed predictive after adjusting for known variables, including estrogen receptor status. ct-miRNA signatures failed to correlate with EFS. However, the levels of ct-miR-140-5p, included in the trastuzumab signature, were associated with EFS (HR 0.43; 95% CI, 0.22-0.84).

CONCLUSIONS

ct-miRNAs discriminate patients with and without pCR after neoadjuvant lapatinib- and/or trastuzumab-based therapy. ct-miRNAs at week two could be valuable to identify patients responsive to trastuzumab, to avoid unnecessary combination with other anti-HER2 agents, and finally to assist deescalating treatment strategies.

Type I interferon/IRF7 axis instigates chemotherapy-induced immunological dormancy in breast cancer

Neoadjuvant and adjuvant chemotherapies provide survival benefits to breast cancer patients, in particular in estrogen receptor negative (ER^-) cancers, by reducing rates of recurrences. It is assumed that the benefits of (neo)adjuvant chemotherapy are due to the killing of disseminated, residual cancer cells, however, there is no formal evidence for it. Here, we provide experimental evidence that ER^- breast cancer cells that survived high-dose Doxorubicin and Methotrexate based chemotherapies elicit a state of immunological dormancy. Hallmark of this dormant phenotype is the sustained activation of the IRF7/IFN-β/IFNAR axis subsisting beyond chemotherapy treatment. Upregulation of IRF7 in treated cancer cells promoted resistance to chemotherapy, reduced cell growth and induced switching of the response from a myeloid derived suppressor cell-dominated immune response to a CD4⁺/CD8⁺ T cell-dependent anti-tumor response. IRF7 silencing in tumor cells or systemic blocking of IFNAR reversed the state of dormancy, while spontaneous escape from dormancy was associated with loss of IFN-β production. Presence of IFN-β in the circulation of ER^- breast cancer patients treated with neoadjuvant Epirubicin chemotherapy correlated with a significantly longer distant metastasis-free survival. These findings establish chemotherapy-induced immunological dormancy in ER^- breast cancer as a novel concept for (neo)adjuvant chemotherapy activity, and implicate sustained activation of the IRF7/IFN-β/IFNAR pathway in this effect. Further, IFN-β emerges as a potential predictive biomarker and therapeutic molecule to improve outcome of ER^- breast cancer patients treated with (neo)adjuvant chemotherapy.

Expression of NK Cell Surface Receptors in Breast Cancer Tissue as Predictors of Resistance to Antineoplastic Treatment

Background:

Currently, one of the most used strategies for the treatment of newly diagnosed patients with breast cancer is neoadjuvant chemotherapy based on the application of taxanes and anthracyclines. However, despite the high number of patients who develop a complete pathological clinical response, resistance and relapse following this therapy continue to be a clinical challenge. As a component of the innate immune system, the cytotoxic function of Natural Killer (NK) cells plays an important role in the elimination of tumor cells. However, the role of NK cells in resistance to systemic therapy in breast cancer remains unclear. The present project aims to evaluate the gene expression profile of human NK cells in breast cancer tissue resistant to treatment with taxanes–anthracyclines.

Methods:

Biopsies from tumor tissues were obtained from patients with breast cancer without prior treatment. Histopathological analysis and ex vivo exposure to antineoplastic chemotherapeutics were carried out. Alamar blue and lactate dehydrogenase release assays were performed for quantitative analysis of tumor viability. Gene expression profiles from tumor tissues without prior exposure to therapeutic drugs were analyzed by gene expression microarrays and verified by polymerase chain reaction.

Results:

A significant decrease in gene expression of cell-surface receptors related to NK cells was observed in tumor samples resistant to antineoplastic treatment compared with those that were sensitive to treatment.

Conclusion:

A decrease in NK cell infiltration into tumor tissue might be a predictive marker for failure of chemotherapeutic treatment in breast cancer.

Noninvasive profiling of serum cytokines in breast cancer patients and clinicopathological characteristics

Cancers elicit an immune response by modifying the microenvironment. The immune system plays a pivotal role in cancer recognition and eradication. While the potential clinical value of infiltrating lymphocytes at the tumor site has been assessed in breast cancer, circulating cytokines – the molecules coordinating and fine-tuning immune response – are still poorly characterized.

Using two breast cancer cohorts (MicMa, n = 131, DCTB, n = 28) and the multiplex Luminex platform, we measured the levels of 27 cytokines in the serum of breast cancer patients prior to treatment. We investigated the cytokine levels in relation to clinicopathological characteristics and in perspective of the tumor infiltrating immune cells predicted from the bulk mRNA expression data.

Unsupervised clustering analysis of the serum cytokine levels in the MicMa cohort identified a cluster of pro-inflammatory, pro-angiogenic, and Th2-related cytokines which was associated with poor prognosis. Notably high levels of platelet derived growth factor BB (PDGF) reflected a more aggressive tumor phenotype and larger tumor size. A significant positive correlation between serum levels of interferon gamma-induced protein 10 (IP10) and its mRNA expression at the tumor site suggested that tumor-IP10-production may outflow to the bloodstream. High IP10 serum levels were associated with a worse prognosis. Finally, we found serum levels of both PDGF and IP10 associated with enrichment scores of specific tumor infiltrating immune cells.

Our study suggests that monitoring cytokine circulating levels in breast cancer could be used to characterize breast cancers and the immune composition of their microenvironment through readily available biological material.

Impact of Topoisomerase IIα, PTEN, ABCC1/MRP1, and KI67 on triple-negative breast cancer patients treated with neoadjuvant chemotherapy

PURPOSE

Triple-negative breast cancer (TNBC) patients with residual disease following neoadjuvant chemotherapy (NAC) harbor higher risk of relapse, and eventual demise compared to those who achieve pathologic complete response. Therefore, in this study, we assessed a panel of molecules involved in key pathways of drug resistance and tumor progression before and after NAC in TNBC patients, in order to clarify the underlying mechanisms.

METHODS

We studied 148 TNBC Japanese patients treated with anthracycline/taxane-based NAC. KI67, Topoisomerase IIα (TopoIIα), PTEN, p53, Bcl2, vimentin, ABCG2/BCRP1, ABCB1/MDR1, and ABCC1/MRP1 were immunolocalized in surgical pathology materials before and after NAC.

RESULTS

The status of vimentin and increasing labeling index (LI) of TopoIIα and KI67 in biopsy specimens were significantly associated with those who responded to NAC treatment. The abundance of p53 (p = 0.003), ABCC1/MRP1 (p = 0.033), ABCB1/MDR1 (p = 0.022), and a loss of PTEN (p < 0.0001) in surgery specimens following treatment were associated with pathologic parameters. TopoIIα, PTEN, and ABCC1/MRP1 status predicted pathologic response. In addition, the status of PTEN, ABCC1/MRP1, ABCB1/MDR1, Bcl2, and vimentin in surgical specimens was also significantly associated with adverse clinicopathological factors in surgery specimens, suggesting that these alterations could be responsible for tumor relapse in TNBC patients.

CONCLUSION

KI67, TopoIIα, PTEN, and ABCC1/MRP1 status could predict treatment response and/or eventual clinical outcomes. These results could also provide an insight into the mechanisms of drug resistance and relapse of TNBC patients receiving NAC.

Hot Spot and Whole-Tumor Enumeration of CD8+ Tumor-Infiltrating Lymphocytes Utilizing Digital Image Analysis Is Prognostic in Triple-Negative Breast Cancer

BACKGROUND

CD8⁺ tumor-infiltrating lymphocytes (TILs) have emerged as a prognostic indicator in triple-negative breast cancer (TNBC). There is debate surrounding the prognostic value of hot spots for CD8⁺ TIL enumeration.

METHODS

We compared hot spot versus whole-tumor CD8⁺ TIL enumeration in prognosticating TNBC using immunohistochemistry on whole tissue sections and quantification by digital image analysis (Halo imaging analysis software; Indica Labs, Corrales, NM). A wide range of clinically relevant hot spot sizes was evaluated.

RESULTS

CD8⁺ TIL enumeration was independently statistically significant for all hot spot sizes and whole-tumor annotations for disease-free survival by multivariate analysis. A 10× objective (2.2 mm diameter) hot spot was found to correlate significantly with overall survival (P = .04), while the remaining hot spots and whole-tumor CD8⁺ TIL enumeration did not (P > .05). Statistical significance was not demonstrated when comparing between hot spots and whole-tumor annotations, as the groups had overlapping confidence intervals.

CONCLUSION

CD8⁺ TIL hot spot enumeration is equivalent to whole-tumor enumeration for prognostication in TNBC and may serve as a good alternative methodology in future studies and clinical practice.

Total choline quantification measured by 1H MR spectroscopy as early predictor of response after neoadjuvant treatment for locally advanced breast cancer: The impact of immunohistochemical status

BACKGROUND

Validation of new biomarkers is essential for the early evaluation of neoadjuvant treatments.

PURPOSE

To determine whether measurements of total choline (tCho) by 1H spectroscopy could predict morphological or pathological complete response (pCR) of neoadjuvant treatment and whether breast cancer subgroups are related to prediction accuracy.

STUDY TYPE

Prospective, nonrandomized, monocentric, diagnostic study.

POPULATION

Sixty patients were initially included with 39 women participating in the final cohort.

FIELD STRENGTH/SEQUENCE

A 1.5T scanner was used for acquisition and MRS was performed using the syngo GRACE sequence.

ASSESSMENT

MRS and MRI examinations were performed at baseline (TP1), 24-72 hours after first chemotherapy (TP2), after the end of anthracycline treatment (TP3), and MRI only after the end of taxane treatment (TP4). Early (EMR) and late (LMR) morphological response were defined as %ΔDmax13 or %ΔDmax14, respectively. Responders were patients with %ΔDmax >30. Pathological complete response (pCR) patients achieved a residual cancer burden score of 0.

STATISTICAL TESTS

T-test, receiver operating characteristic (ROC) curves, multiple regression, logistic regression, one-way analysis of variance (ANOVA) analysis were used for the analysis.

RESULTS

At TP1 there was a significant difference between response groups for tCho1 concerning EMR prediction (P = 0.05) and pCR (P < 0.05) and for K_ep 1 (P = 0.03) concerning LMR prediction. At TP2, no modification of tCho and other parameters could predict response. At TP3, ΔtCho, ΔDmax, and ΔVol could predict LMR (P < 0.05 for all parameters), pCR (P < 0.05 for all parameters), and ΔK^trans could predict only pCR (P = 0.04). Logistic regression at baseline showed the highest area under the curve (AUC) of 0.9 for prediction of pCR. The triple negative (TN) subgroup showed significantly higher tCho at baseline (P = 0.02) and higher ΔtCho levels at TP3 (P < 0.05).

DATA CONCLUSION

Baseline measurements of tCho in combination with clinicopathological criteria could predict non-pCR with a high AUC. Furthermore, tCho quantification for prediction of pCR was more sensitive for TN tumors.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2018;48:982-993.

Tumor-infiltrating lymphocytes predict prognosis of breast cancer patients treated with anti-Her-2 therapy

PURPOSE

Infiltration of tumor associated lymphocytes and count of its different phenotypes are potentially new independent predictor of prognosis in breast cancer. However, research related to it is less reported in breast cancer patients treated with anti-Her-2 therapy. Thus, we evaluated the relationship between survival and tumor infiltrating lymphocytes including its different phenotypes in tumors of such patients.

METHODS

Between 1999 and 2010, 98 patients diagnosed with primary breast cancer and treated with anti-Her-2 therapy at Sun-Yat-Sen University Cancer Center were included in the study. Biopsy specimens were collected post-operation but before chemotherapy. Tumor infiltrating lymphocytes as well as its FOXP3+, CD68+, IL-17+ phenotypes in both intratumoral and stromal sites and expression of FOXP3 in cancer cells were assessed.

RESULTS

Median follow-up time of 98 patients was 83.3 months (range 7.4-201 months). It suggested that patients with high stromal infiltration of TILs, lower count of FOXP3+ Tregs and CD68+ Mφ in stromal site, and high expression of FOXP3 in cancer cells had longer survival of OS. In multivariate Cox regression analysis, high count of intratumoral CD68+ Mφ [HR: 2.70 (1.00-7.31); p=0.050] and high expression of FOXP3 in cancer cells [HR: 0.29 (0.09-0.91); p=0.034] were independent prognostic factors for overall survival.

CONCLUSIONS

Tumor infiltrating lymphocytes as well as its FOXP3+, CD68+ phenotypes in stromal site, and expression of FOXP3 in cancer cells were significantly associated with OS, suggesting that they can be used as important pathological factor predicting prognosis of breast cancer patients treated with anti-Her-2 therapy.

Immune gene expression and response to chemotherapy in advanced breast cancer

Background:

Transcriptomic profiles have shown promise as predictors of response to neoadjuvant chemotherapy in breast cancer (BC). This study aimed to explore their predictive value in the advanced BC (ABC) setting.

Methods:

In a Phase 3 trial of first-line chemotherapy in ABC, a fine needle aspiration biopsy (FNAB) was obtained at baseline. Intrinsic molecular subtypes and gene modules related to immune response, proliferation, oestrogen receptor (ER) signalling and recurring genetic alterations were analysed for association with objective response to chemotherapy. Gene-set enrichment analysis (GSEA) of responders vs non-responders was performed independently. Lymphocytes were enumerated in FNAB smears and the absolute abundance of immune cell types was calculated using the Microenvironment Cell Populations counter method.

Results:

Gene expression data were available for 109 patients. Objective response to chemotherapy was statistically significantly associated with an immune module score (odds ratio (OR)=1.62; 95% confidence interval (CI), 1.03–2.64; P=0.04). Subgroup analysis showed that this association was restricted to patients with ER-positive or luminal tumours (OR=3.54; 95%, 1.43–10.86; P=0.012 and P for interaction=0.04). Gene-set enrichment analysis confirmed that in these subgroups, immune-related gene sets were enriched in responders.

Conclusions:

Immune-related transcriptional signatures may predict response to chemotherapy in ER-positive and luminal ABC.

Biology and Management of Undifferentiated Pleomorphic Sarcoma, Myxofibrosarcoma, and Malignant Peripheral Nerve Sheath Tumors: State of the Art and Perspectives

Undifferentiated pleomorphic sarcomas, myxofibrosarcomas, and malignant peripheral nerve sheath tumors are characterized by complex genomic characteristics and aggressive clinical behavior. Recent advances in the understanding of the pathogenesis of these tumors may allow for the development of more-effective innovative therapeutic strategies, including immunotherapies. This review describes the current knowledge of the epidemiology, clinical presentation, treatment, and pathogenesis of these tumors and highlights ongoing and future research.

Gene modules associated with breast cancer distant metastasis-free survival in the PAM50 molecular subtypes

To identify PAM50 subtype–specific associations between distant metastasis-free survival (DMFS) in breast cancer (BC) patients and gene modules describing potentially targetable oncogenic pathways, a comprehensive analysis evaluating the prognostic efficacy of published gene signatures in 2027 BC patients from 13 studies was conducted. We calculated 21 gene modules and computed hazard ratios (HRs) for DMFS for one-unit increases in module score, with and without adjustment for clinical characteristics. By comparing gene expression to survival outcomes, we derived four subtype-specific prognostic signatures for BC. Univariate and multivariate analyses showed that in the luminal A subgroup, E2F3, PTEN and GGI gene module scores were associated with clinical outcome. In the luminal B tumors, RAS was associated with DMFS and in the basal-like tumors, ER was associated with DMFS. Our defined gene modules predicted high-risk patients in multivariate analyses for the basal-like (HR: 2.19, p=2.5×10⁻⁴), luminal A (HR: 3.03, p=7.2×10⁻⁵), luminal B (HR: 3.00, p=2.4×10⁻¹⁰) and HER2+ (HR: 5.49, p=9.7×10⁻¹⁰) subgroups. We found that different modules are associated with DMFS in different BC subtypes. The results of this study could help to identify new therapeutic strategies for specific molecular subgroups of BC, and could enhance efforts to improve patient-specific therapy options.

A Long Noncoding RNA Signature That Predicts Pathological Complete Remission Rate Sensitively in Neoadjuvant Treatment of Breast Cancer

BACKGROUND

Mounting evidence suggests that long noncoding RNAs (lncRNAs) are closely related to pathological complete response (pCR) in neoadjuvant treatment of breast cancer. Here, we construct lncRNA associated models to predict pCR rate.

METHODS

LncRNA expression profiles of breast cancer patients treated with neoadjuvant chemotherapy (NAC) were obtained from Gene Expression Omnibus by repurposing existing microarray data. The prediction model was firstly built by analyzing the correlation between pCR and lncRNA expression in the discovery dataset GSE 25066 (n=488). Another three independent datasets, GSE20194 (n=278), GSE20271 (n=178), and GSE22093 (n=97), were integrated as the validation cohort to assess the prediction efficiency.

RESULTS

A novel lncRNA signature (LRS) consisting of 36 lncRNAs was identified. Based on this LRS, patients with NAC treatment were divided into two groups: LRS-high group and LRS-low group, with positive correlation of pCR rate in the discovery dataset. In the validation cohort, univariate and multivariate analyses both demonstrated that high LRS was associated with higher pCR rate. Subgroup analysis confirmed that this model performed well in luminal B [odds ratio (OR)=5.4; 95% confidence interval (CI)=2.7-10.8; P=1.47e-06], HER2-enriched (OR=2.5; 95% CI=1.1-5.7; P=.029), and basal-like (OR=5.5; 95% CI=2.3-16.2; P=5.32e-04) subtypes. Compared with other preexisting prediction models, LRS demonstrated better performance with higher area under the curve. Functional annotation analysis suggested that lncRNAs in this signature were mainly involved in cancer proliferation process.

CONCLUSION

Our findings indicated that our lncRNA signature was sensitive to predict pCR rate in the neoadjuvant treatment of breast cancer, which deserves further evaluation.