SETER/PR: a robust 18-gene predictor for sensitivity to endocrine therapy for metastatic breast cancer

Txnrd1 as a prognosticator for recurrence, metastasis and response to neoadjuvant chemotherapy and radiotherapy in breast cancer patients

Thioredoxin reductase 1 (Txnrd1) is known to have prognostic significance in a subset of breast cancer patients. Despite the pivotal role of Txnrd1 in regulating several cellular and physiological processes in cancer progression and metastasis, its clinical significance is largely unrecognized. Here, we undertook a retrospective comprehensive meta-analysis of 13,322 breast cancer patients from 43 independent cohorts to assess prognostic and predictive roles of Txnrd1. We observed that Txnrd1 has a positive correlation with tumor grade and size and it is over-expressed in higher-grade and larger tumors. Further, hormone receptor-negative and HER2-positive tumors exhibit elevated Txnrd1 gene expression. Patients with elevated Txnrd1 expression exhibit significant hazards for shorter disease-specific and overall survival. While Txnrd1 has a positive correlation with tumor recurrence and metastasis, it has a negative correlation with time to recurrence and metastasis. Txnrd1High patients exhibit 2.5 years early recurrence and 1.3 years early metastasis as compared to Txnrd1Low cohort. Interestingly, patients with high Txnrd1 gene expression exhibit a pathologic complete response (pCR) to neoadjuvant chemotherapy, but they experience early recurrence after radiotherapy. Txnrd1High MDA-MB-231 cells exhibit significant ROS generation and reduced viability after doxorubicin treatment compared to Txnrd1Low MCF7 cells. Corroborating with findings from meta-analysis, Txnrd1 depletion leads to decreased survival, enhanced sensitivity to radiation induced killing, poor scratch-wound healing, and reduced invasion potential in MDA-MB-231 cells. Thus, Txnrd1 appears to be a potential predictor of recurrence, metastasis and therapy response in breast cancer patients.

Experimental and clinical evidence in favour of an effective immune stimulation in ER-positive, endocrine-dependent metastatic breast cancer

In ER+ breast cancer, usually seen as the low immunogenic type, the main mechanisms favouring the immune response or tumour growth and immune evasion in the tumour microenvironment (TME) have been examined. The principal implications of targeting the oestrogen-mediated pathways were also considered. Recent experimental findings point out that anti-oestrogens contribute to the reversion of the immunosuppressive TME. Moreover, some preliminary clinical data with the hormone-immunotherapy association in a metastatic setting support the notion that the reversion of immune suppression in TME is likely favoured by the G0-G1 state induced by anti-oestrogens. Following immune stimulation, the reverted immune suppression allows the boosting of the effector cells of the innate and adaptive immune response. This suggests that ER+ breast cancer is a molecular subtype where a successful active immune manipulation can be attained. If this is confirmed by a prospective multicentre trial, which is expected in light of the provided evidence, the proposed hormone immunotherapy can also be tested in the adjuvant setting. Furthermore, the different rationale suggests a synergistic activity of our proposed immunotherapy with the currently recommended regimen consisting of antioestrogens combined with cyclin kinase inhibitors. Overall, this lays the foundation for a shift in clinical practice within this most prevalent molecular subtype of breast cancer.

Molecular features of luminal breast cancer defined through spatial and single-cell transcriptomics

BACKGROUND

Intratumour heterogeneity is a hallmark of most solid tumours, including breast cancers. We applied spatial transcriptomics and single-cell RNA-sequencing on patient-derived xenografts (PDXs) to profile spatially resolved cell populations within oestrogen receptor-positive (ER+ ) breast cancer and to elucidate their importance in oestrogen-dependent tumour growth.

METHODS

Two PDXs of 'ER-high' breast cancers with opposite oestrogen-mediated growth responses were investigated: oestrogen-suppressed GS3 (80-100% ER) and oestrogen-dependent SC31 (40-90% ER) models. The observation was validated via single-cell analyses on an 'ER-low' PDX, GS1 (5% ER). The results from our spatial and single-cell analyses were further supported by a public ER+ breast cancer single-cell dataset and protein-based dual immunohistochemistry (IHC) of SC31 examining important luminal cancer markers (i.e., ER, progesterone receptor and Ki67). The translational implication of our findings was assessed by clinical outcome analyses on publicly available cohorts.

RESULTS

Our space-gene-function study revealed four spatially distinct compartments within ER+ breast cancers. These compartments showed functional diversity (oestrogen-responsive, proliferative, hypoxia-induced and inflammation-related). The 'proliferative' population, rather than the 'oestrogen-responsive' compartment, was crucial for oestrogen-dependent tumour growth, leading to the acquisition of luminal B-like features. The cells expressing typical oestrogen-responsive genes like PGR were not directly linked to oestrogen-dependent proliferation. Dual IHC analyses demonstrated the distinct contribution of the Ki67+ proliferative cells toward oestrogen-mediated growth and their response to a CDK4/6 inhibitor. The gene signatures derived from the proliferative, hypoxia-induced and inflammation-related compartments were significantly correlated with worse clinical outcomes, while patients with the oestrogen-responsive signature showed better prognoses, suggesting that this compartment would not be directly associated with oestrogen-dependent tumour progression.

CONCLUSIONS

Our study identified the gene signature in our 'proliferative' compartment as an important determinant of luminal cancer subtypes. This 'proliferative' cell population is a causative feature of luminal B breast cancer, contributing toward its aggressive behaviours.

A Novel Mathematical Approach for Analysis of Integrated Cell-Patient Data Uncovers a 6-Gene Signature Linked to Endocrine Therapy Resistance

A significant number of breast cancers develop resistance to hormone therapy. This progression, while posing a major clinical challenge, is difficult to predict. Despite important contributions made by cell models and clinical studies to tackle this problem, both present limitations when taken individually. Experiments with cell models are highly reproducible but do not reflect the indubitable heterogenous landscape of breast cancer. On the other hand, clinical studies account for this complexity but introduce uncontrolled noise due to external factors. Here, we propose a new approach for biomarker discovery that is based on a combined analysis of sequencing data from controlled MCF7 cell experiments and heterogenous clinical samples that include clinical and sequencing information from The Cancer Genome Atlas. Using data from differential gene expression analysis and a Bayesian logistic regression model coupled with an original simulated annealing-type algorithm, we discovered a novel 6-gene signature for stratifying patient response to hormone therapy. The experimental observations and computational analysis built on independent cohorts indicated the superior predictive performance of this gene set over previously known signatures of similar scope. Together, these findings revealed a new gene signature to identify patients with breast cancer with an increased risk of developing resistance to endocrine therapy.

Toxic PARP trapping upon cAMP-induced DNA damage reinstates the efficacy of endocrine therapy and CDK4/6 inhibitors in treatment-refractory ER+ breast cancer

Resistance to endocrine therapy and CDK4/6 inhibitors, the standard of care (SOC) in estrogen receptor-positive (ER+) breast cancer, greatly reduces patient survival. Therefore, elucidating the mechanisms of sensitivity and resistance to SOC therapy and identifying actionable targets are urgently needed. Here, we show that SOC therapy causes DNA damage and toxic PARP1 trapping upon generation of a functional BRCAness (i.e., BRCA1/2 deficiency) phenotype, leading to increased histone parylation and reduced H3K9 acetylation, resulting in transcriptional blockage and cell death. Mechanistically, SOC therapy downregulates phosphodiesterase 4D (PDE4D), a novel ER target gene in a feedforward loop with ER, resulting in increased cAMP, PKA-dependent phosphorylation of mitochondrial COXIV-I, ROS generation and DNA damage. However, during SOC resistance, an ER-to-EGFR switch induces PDE4D overexpression via c-Jun. Notably, combining SOC with inhibitors of PDE4D, EGFR or PARP1 overcomes SOC resistance irrespective of the BRCA1/2 status, providing actionable targets for restoring SOC efficacy.

Pre-analytical effects on whole transcriptome and targeted RNA sequencing analysis in cytology: The effects of prolonged time in storage of effusion specimens prior to preservation

OBJECTIVES

To investigate the pre-analytics of the molecular testing of cytology specimens, we studied the effects of time in refrigerator storage (4°C) of malignant effusions on RNA sequencing (RNAseq) results.

METHODS

Ten effusion specimens were stored in a refrigerator (4°C) for different durations (day 0, 1, 4, and 7). All specimens were prepared as cytospins fixed in either Carnoy's solution or 95% ethanol (EtOH) and in an RNA preservative for a fresh frozen (FF) high-quality reference. Whole transcriptome (wt) and targeted (t)RNAseq of two multigene expression signatures were performed. We then compared transcript expression levels (including mutant allele fraction) according to pre-analytical variables using a concordance correlation coefficient (CCC) and a mixed effect model.

RESULTS

Sequencing results were mostly stable over increasing time in storage. Cytospins fixed in Carnoy's solution were more concordant with FF samples than cytospins fixed in 95% EtOH at all timepoints. This finding was consistent for both wtRNAseq (averages: day 0 CCC = 0.98 vs 0.91; day 7 CCC = 0.88 vs 0.78) and tRNAseq methods (averages: day 0 CCC = 0.98 vs 0.81; day 7 CCC = 0.98 vs 0.90). Cytospins fixed in Carnoy's solution did not show significant changes in expression over timepoints or between expression signatures, whereas 95% EtOH did.

CONCLUSION

RNAseq can be accurately performed on effusion specimens after prolonged refrigerator storage. RNA extracted from scraped cytospin slides fixed in Carnoy's solution was marginally superior to 95% EtOH fixation, but either method had comparable analytic performance to high-quality FF RNA samples.

Molecular Characterization of HER2-Low Invasive Breast Carcinoma by Quantitative RT-PCR Using Oncotype DX Assay

BACKGROUND

HER2 immunohistochemistry (IHC) reproducibility is suboptimal for HER-low cases (IHC 1+ or 2+).

METHODS

The Yale cohort included 214 stages I-II estrogen receptor positive breast cancers with IHC scores 0, 1+, and 2+ and routine Oncotype DX Recurrence Score (RS) results. The Exact Sciences (ES) cohort included 9 57 624 patients who had an Oncotype DX RS assay that assigns HER2-negative, equivocal, or positive status based on HER2 mRNA levels.

RESULTS

HER2 mRNA levels varied across IHC categories but with increasing medians of 9.10 (n = 89), 9.20 (n = 71), and 9.45 (n = 54) in IHC 0, 1+, and 2+, respectively. 22.4% of HER2-low (1+/2+) cancer had RS > 25. Over 98% of HER-low cancers were HER2-negative by Oncotype DX assignment.

CONCLUSIONS

Cancers with higher mRNA levels exist within IHC 0 and low categories, most of the HER2-low patients by IHC have low RS indicating no benefit from current adjuvant chemotherapies.

Molecular features and clinical implications of the heterogeneity in Chinese patients with HER2-low breast cancer

The molecular heterogeneity and distinct features of HER2-low breast cancers, particularly in the Chinese population, are not well understood, limiting its precise management in the era of antibody‒drug conjugates. To address this issue, we established a cohort of 434 Chinese patients with HER2-low breast cancer (433 female and one male) and integrated genomic, transcriptomic, proteomic, and metabolomic profiling data. In this cohort, HER2-low tumors are more distinguished from HER2-0 tumors in the hormone receptor-negative subgroup. Within HER2-low tumors, significant interpatient heterogeneity also exists in the hormone receptor-negative subgroup: basal-like tumors resemble HER2-0 disease, and non-basal-like HER2-low tumors mimic HER2-positive disease. These non-basal-like HER2-low tumors are enriched in the HER2-enriched subtype and the luminal androgen receptor subtype and feature PIK3CA mutation, FGFR4/PTK6/ERBB4 overexpression and lipid metabolism activation. Among hormone receptor-positive tumors, HER2-low tumors show less loss/deletion in 17q peaks than HER2-0 tumors. In this work, we reveal the heterogeneity of HER2-low breast cancers and emphasize the need for more precise stratification regarding hormone receptor status and molecular subtype.

Accelerated glycolysis in tumor microenvironment is associated with worse survival in triple-negative but not consistently with ER+/HER2- breast cancer

Metabolic reprogramming to sustain immortality is a hallmark of cancer and glycolysis is an important way to attain this. Thus, we investigate the association of glycolysis and associated pathways in the survival of breast cancer. A total of 5,176 breast cancer patients from multiple independent cohorts were analyzed. We determined the glycolytic signaling score by the degree of enrichment by Gene Set Variant Analysis and the median was used to divide each cohort into high vs low score groups. Glycolysis high breast cancer significantly enriched the hallmark cell proliferation-related gene sets (E2F targets, G2M checkpoint, and MYC targets v1 and v2) and was associated with high MKI67 expression. In all cohorts, triple-negative breast cancer (TNBC) was associated with the highest glycolysis score. It was found that in TNBC, glycolysis high breast cancer was associated with worse survival but in ER-positive/HER2-negative breast cancer this was not observed consistently. The glycolysis high TNBC enriched multiple pro-cancerous gene sets and was infiltrated with a low level of B-cells and anti-cancerous immune cells, and significantly associated with a decreased level of cytolytic activity. It was also observed that the glycolysis was higher in the metastatic sites than in the primary breast cancer and the survival was not affected by the metastatic sites. In conclusion, accelerated glycolysis is associated with cancer cell proliferation and worse survival in TNBC.

Taxifolin Inhibits Breast Cancer Growth by Facilitating CD8+ T Cell Infiltration and Inducing a Novel Set of Genes including Potential Tumor Suppressor Genes in 1q21.3

Taxifolin inhibits breast cancer (BC) via novel mechanisms. In a syngeneic mouse BC model, taxifolin suppressed 4T-1 cell-derived allografts. RNA-seq of 4T-1 tumors identified 36 differentially expressed genes (DEGs) upregulated by taxifolin. Among their human homologues, 19, 7, and 2 genes were downregulated in BCs, high-proliferative BCs, and BCs with high-fatality risks, respectively. Three genes were established as tumor suppressors and eight were novel to BC, including HNRN, KPRP, CRCT1, and FLG2. These four genes exhibit tumor suppressive actions and reside in 1q21.3, a locus amplified in 70% recurrent BCs, revealing a unique vulnerability of primary and recurrent BCs with 1q21.3 amplification with respect to taxifolin. Furthermore, the 36 DEGs formed a multiple gene panel (DEG36) that effectively stratified the fatality risk in luminal, HER2+, and triple-negative (TN) equivalent BCs in two large cohorts: the METABRIC and TCGA datasets. 4T-1 cells model human TNBC cells. The DEG36 most robustly predicted the poor prognosis of TNBCs and associated it with the infiltration of CD8+ T, NK, macrophages, and Th2 cells. Of note, taxifolin increased the CD8+ T cell content in 4T-1 tumors. The DEG36 is a novel and effective prognostic biomarker of BCs, particularly TNBCs, and can be used to assess the BC-associated immunosuppressive microenvironment.

Evaluation of the Sensitivity to Endocrine Therapy Index and 21-Gene Breast Recurrence Score in the SWOG S8814 Trial

PURPOSE

Chemotherapy has not demonstrated benefit over adjuvant endocrine therapy alone for postmenopausal patients with node-positive breast cancer with a 21-gene breast recurrence score (RS) of 25 or below (RS ≤ 25). We tested whether combined results from RS and the sensitivity to endocrine therapy (SET2,3) index of endocrine-related transcription (SETER/PR) adjusted for baseline prognostic index (BPI) improve prognostic assessment, and whether SET2,3 predicted benefit from anthracycline-based chemotherapy.

METHODS

A blinded retrospective clinical validation of SET2,3 in two randomized treatment arms from the SWOG S8814 trial comparing adjuvant anthracycline-based chemotherapy followed by tamoxifen endocrine therapy for 5 years, versus tamoxifen alone. SET2,3 assay was calibrated and measured using whole-transcriptome RNA sequence of tumor samples already tested for RS. The primary end point was disease-free survival (DFS).

RESULTS

There were 106 events in 283 patients over a median follow-up of 8.99 years. Proportional hazards assumptions were met during the first 5 years only. SET2,3 index and RS were not correlated (r = -0.04) and were independently prognostic (SET2,3: hazard ratio [HR], 0.48 per unit; 95% CI, 0.34 to 0.68; P < .001; RS: HR, 1.28 per 10 units; 95% CI, 1.14 to 1.44; P < .001). SET2,3 index did not predict chemotherapy benefit (interaction P = .77). SET2,3 was high in 93/175 (53%) patients with RS ≤ 25 (concordant low-risk), with 5-year DFS 97%. SET2,3 was low in 55/108 (51%) patients with RS > 25 (concordant high-risk), with 5-year DFS 53%. Both components of SET2,3 index were prognostic after adjustment for RS: SETER/PR (HR, 0.65; 95% CI, 0.46 to 0.92) and BPI (HR, 0.45; 95% CI, 0.31 to 0.64).

CONCLUSION

SET2,3 index was not correlated with RS, demonstrated additive prognostic performance, and was not chemopredictive in this subset of patients from S8814. The SETER/PR and BPI components of SET2,3 each added prognostic information to RS.

Pharmacological Targeting of Androgen Receptor Elicits Context-Specific Effects in Estrogen Receptor-Positive Breast Cancer

Androgen receptor (AR) is expressed in 80% to 90% of estrogen receptor α-positive (ER+) breast cancers. Accumulated evidence has shown that AR is a tumor suppressor and that its expression is associated with improved prognosis in ER+ breast cancer. However, both a selective AR agonist (RAD140) and an AR inhibitor (enzalutamide, ENZ) have shown a therapeutic effect on ER+ breast cancer, so the potential for clinical application of AR-targeting therapy for ER+ breast cancer is still in dispute. In this study, we evaluated the efficacy of ENZ and RAD140 in vivo and in vitro in AR+/ER+ breast cancer models, characterizing the relationship of AR and ER levels to response to AR-targeting drugs and investigating the alterations of global gene expression and chromatin binding of AR and ERα after ENZ treatment. In the AR-low setting, ENZ directly functioned as an ERα antagonist. Cell growth inhibition by ENZ in breast cancer with low AR expression was independent of AR and instead dependent on ER. In AR-high breast cancer models, AR repressed ERα signaling and ENZ promoted ERα signaling by antagonizing AR. In contrast, RAD140 activated AR signaling and suppressed AR-high tumor growth by deregulating ERα expression and blocking ERα function. Overall, analysis of the dynamic efficacies and outcomes of AR agonist, and antagonist in the presence of different AR and ERα levels reveals regulators of response and supports the clinical investigation of ENZ in selected ER+ tumors with a low AR/ER ratio and AR agonists in tumors with a high AR/ER ratio.

SIGNIFICANCE

The ratio of androgen receptor to estrogen receptor in breast cancer dictates the response to AR-targeted therapies, providing guidelines for developing AR-directed treatment strategies for patients with breast cancer.

Molecular testing opportunities on cytology effusion specimens: the pre-analytic effects of various body fluid cytology preparation methods on RNA extraction quality and targeted sequencing

INTRODUCTION

RNA sequencing (RNAseq) analysis is emerging as a clinical research or diagnostic approach for cytologic samples, but there is need for formal comparison of different sample preparation methods in the cytology laboratory to identify which pre-analytic methods could provide alternatives to formalin-fixed paraffin-embedded (FFPE) sections.

MATERIALS AND METHODS

We prepared 13 malignant effusions (metastatic estrogen receptor-positive breast cancer) in the cytology laboratory using 6 routine cytologic methods: FFPE cell block, Carnoy's solution, 95% ethanol (EtOH), air-dried and Diff-Quik, ThinPrep, and SurePath preparations. Measurements of RNA quality, expression of 2 multigene expression signatures, molecular subtype, and 4 common activating mutation sites in each preparation were compared with fresh frozen (FF) cell pellet in RNA preservative using distribution of fragment length and concordance correlation coefficient (CCC).

RESULTS

The fraction of RNA fragments measuring 200 bases or more (DV200) were 24% higher from cytospins fixed in Carnoy's solution or 95% EtOH than DV200 from FFPE cell blocks. SurePath samples failed RNAseq quality control. There was high concordance of gene expression measurements with FF samples using cytospins fixed in Carnoy's solution, 95% EtOH, Diff-Quik (CCC = 0.829, 0.812, 0.760, respectively), or ThinPrep (CCC = 0.736), but lower using FFPE cell block (CCC = 0.564). The proportion of mutant transcripts was concordant between FF and any cytologic preparation methods.

CONCLUSIONS

Cytospin preparations fixed with Carnoy's or 95% ETOH then Papanicolaou stained produced RNAseq results that were equivalent to FF samples and superior to FFPE cell block sections.

Neoadjuvant endocrine therapy in postmenopausal women with HR+/HER2- breast cancer

INTRODUCTION

While endocrine therapy is the standard-of-care adjuvant treatment for hormone receptor-positive (HR+) breast cancers, there is also extensive evidence for the role of pre-operative (or neoadjuvant) endocrine therapy (NET) in HR+ postmenopausal women.

AREAS COVERED

We conducted a thorough review of the published literature, to summarize the evidence to date, including studies of how NET compares to neoadjuvant chemotherapy, which NET agents are preferable, and the optimal duration of NET. We describe the importance of on-treatment assessment of response, the different predictors available (including Ki67, PEPI score, and molecular signatures) and the research opportunities the pre-operative setting offers. We also summarize recent combination trials and discuss how the COVID-19 pandemic led to increases in NET use for safe management of cases with deferred surgery and adjuvant treatments.

EXPERT OPINION

NET represents a safe and effective tool for the management of postmenopausal women with HR+/HER2- breast cancer, enabling disease downstaging and a wider range of surgical options. Aromatase inhibitors are the preferred NET, with evidence suggesting that longer regimens might yield optimal results. However, NET remains currently underutilised in many territories and institutions. Further validation of predictors for treatment response and benefit is needed to help standardise and fully exploit the potential of NET in the clinic.

Identifying liver metastasis-related hub genes in breast cancer and characterizing SPARCL1 as a potential prognostic biomarker

Background

The liver is the third most common metastatic site for advanced breast cancer (BC), and liver metastases predict poor prognoses. However, the characteristic biomarkers of BC liver metastases and the biological role of secreted protein acidic and rich in cysteine-like 1 (SPARCL1) in BC remain unclear. The present study aimed to identify potential biomarkers for liver metastasis of BC and to investigate the effect of SPARCL1 on BC.

Methods

The publicly available GSE124648 dataset was used to identify differentially expressed genes (DEGs) between BC and liver metastases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to annotate these DEGs and understand the biological functions in which they are involved. A protein-protein interaction (PPI) network was constructed to identify metastasis-related hub genes and further validated in a second independent dataset (GSE58708). Clinicopathological correlation of hub gene expression in patients with BC was determined. Gene set enrichment analysis (GSEA) was performed to explore DEG-related signaling pathways. SPARCL1 expression in BC tissues and cell lines was verified by RT-qPCR. Further in vitro experiments were performed to investigate the biological functions of SPARCL1 in BC cells.

Results

We identified 332 liver metastasis-related DEGs from GSE124648 and 30 hub genes, including SPARCL1, from the PPI network. GO and KEGG enrichment analyses of liver-metastasis-related DEGs revealed several enriched terms associated with the extracellular matrix and pathways in cancer. Clinicopathological correlation analysis of SPARCL1 revealed that its expression in BC was associated with age, TNM stage, estrogen receptor status, progesterone receptor status, histological type, molecular type, and living status of patients. GSEA results suggested that low SPARCL1 expression in BC was related to the cell cycle, DNA replication, oxidative phosphorylation, and homologous recombination. Lower expression levels of SPARCL1 were detected in BC tissues compared to adjacent tissues. The in vitro experiments showed that SPARCL1 knockdown significantly increased the proliferation and migration of BC cells, whereas the proliferation and migration were suppressed after elevating the expression of SPARCL1.

Conclusion

We identified SPARCL1 as a tumor suppressor in BC, which shows potential as a target for BC and liver metastasis therapy and diagnosis.

Borderline indications for ovarian suppression: addressing uncertainties with patients

Ovarian function suppression (OFS) is a potentially life-saving treatment for young women diagnosed with high-risk hormonal-receptor (HR)+ early breast cancer (EBC), albeit one associated with significant side effects that may adversely affect quality of life. Of particular concern, this article raises a few borderline indications that were largely unaddressed in pivotal clinical trials but are still commonly encountered in daily practice. These, referred to here as 'borderline indications of OFS' remain a source of uncertainty for patients and physicians and are concisely addressed in this article.

Bioinformatics and network-based screening and discovery of potential molecular targets and small molecular drugs for breast cancer

Accurate identification of molecular targets of disease plays an important role in diagnosis, prognosis, and therapies. Breast cancer (BC) is one of the most common malignant cancers in women worldwide. Thus, the objective of this study was to accurately identify a set of molecular targets and small molecular drugs that might be effective for BC diagnosis, prognosis, and therapies, by using existing bioinformatics and network-based approaches. Nine gene expression profiles (GSE54002, GSE29431, GSE124646, GSE42568, GSE45827, GSE10810, GSE65216, GSE36295, and GSE109169) collected from the Gene Expression Omnibus (GEO) database were used for bioinformatics analysis in this study. Two packages, LIMMA and clusterProfiler, in R were used to identify overlapping differential expressed genes (oDEGs) and significant GO and KEGG enrichment terms. We constructed a PPI (protein–protein interaction) network through the STRING database and identified eight key genes (KGs) EGFR, FN1, EZH2, MET, CDK1, AURKA, TOP2A, and BIRC5 by using six topological measures, betweenness, closeness, eccentricity, degree, MCC, and MNC, in the Analyze Network tool in Cytoscape. Three online databases GSCALite, Network Analyst, and GEPIA were used to analyze drug enrichment, regulatory interaction networks, and gene expression levels of KGs. We checked the prognostic power of KGs through the prediction model using the popular machine learning algorithm support vector machine (SVM). We suggested four TFs (TP63, MYC, SOX2, and KDM5B) and four miRNAs (hsa-mir-16-5p, hsa-mir-34a-5p, hsa-mir-1-3p, and hsa-mir-23b-3p) as key transcriptional and posttranscriptional regulators of KGs. Finally, we proposed 16 candidate repurposing drugs YM201636, masitinib, SB590885, GSK1070916, GSK2126458, ZSTK474, dasatinib, fedratinib, dabrafenib, methotrexate, trametinib, tubastatin A, BIX02189, CP466722, afatinib, and belinostat for BC through molecular docking analysis. Using BC cell lines, we validated that masitinib inhibits the mTOR signaling pathway and induces apoptotic cell death. Therefore, the proposed results might play an effective role in the treatment of BC patients.

Evaluation of Sensitivity to Endocrine Therapy Index (SET2,3) for Response to Neoadjuvant Endocrine Therapy and Longer-Term Breast Cancer Patient Outcomes (Alliance Z1031)

PURPOSE

To evaluate prediction of response and event-free survival (EFS) following neoadjuvant endocrine therapy by SET2,3 index of nonproliferation gene expression related to estrogen and progesterone receptors adjusted for baseline prognosis.

EXPERIMENTAL DESIGN

A correlative study was conducted of SET2,3 measured from gene expression profiles of diagnostic tumor (Agilent microarrays) in 379 women with cStage II-III breast cancer from the American College of Surgeons Oncology Group Z1031 neoadjuvant aromatase inhibitor trial SET2,3 was dichotomized using the previously published cutoff. Fisher exact test was used to assess the association between SET2,3 and low proliferation at week 2-4 [Ki67 ≤ 10% or complete cell-cycle arrest (CCCA; Ki67 ≤ 2.7%)] and PEPI-0 rate in cohort B, and the association between SET2,3 and ypStage 0/I in all patients. Cox models were used to assess EFS with respect to SET2,3 excluding cohort B patients who switched to chemotherapy.

RESULTS

Patients with high SET2,3 had higher rate of pharmacodynamic response than patients with low SET2,3 (Ki67 ≤ 10% in 88.2% vs. 56.9%, P < 0.0001; CCCA in 50.0% vs. 26.2%, P = 0.0054), but rate of ypStage 0/I (24.0% vs. 20.4%, P = 0.4580) or PEPI = 0 (28.4% vs. 20.6%, P = 0.3419) was not different. Patients with high SET2,3 had longer EFS than patients with low SET2,3 (HR, 0.52, 95% confidence interval: 0.34-0.80; P = 0.0026).

CONCLUSIONS

This exploratory analysis of Z1031 data demonstrated a higher rate of pharmacodynamic suppression of proliferation and longer EFS in high SET2,3 disease relative to low SET2,3 disease. The ypStage 0/I rate and PEPI = 0 rate were similar with respect to SET2,3.

The crucial role of epigenetic regulation in breast cancer anti-estrogen resistance: Current findings and future perspectives

Breast cancer (BC) cell de-sensitization to Tamoxifen (TAM) or other selective estrogen receptor (ER) modulators (SERM) is a complex process associated with BC heterogeneity and the transformation of ER signalling. The most influential resistance-related mechanisms include modifications in ER expression and gene regulation patterns. During TAM/SERM treatment, epigenetic mechanisms can effectively silence ER expression and facilitate the development of endocrine resistance. ER status is efficiently regulated by specific epigenetic tools including hypermethylation of CpG islands within ER promoters, increased histone deacetylase activity in the ER promoter, and/or translational repression by miRNAs. Over-methylation of the ER α gene (ESR1) promoter by DNA methyltransferases was associated with poor prognosis and indicated the development of resistance. Moreover, BC progression and spreading were marked by transformed chromatin remodelling, post-translational histone modifications, and expression of specific miRNAs and/or long non-coding RNAs. Therefore, targeted inhibition of histone acetyltransferases (e.g. MYST3), deacetylases (e.g. HDAC1), and/or demethylases (e.g. lysine-specific demethylase LSD1) was shown to recover and increase BC sensitivity to anti-estrogens. Indicated as a powerful molecular instrument, the administration of epigenetic drugs can regain ER expression along with the activation of tumour suppressor genes, which can in turn prevent selection of resistant cells and cancer stem cell survival. This review examines recent advances in the epigenetic regulation of endocrine drug resistance and evaluates novel anti-resistance strategies. Underlying molecular mechanisms of epigenetic regulation will be discussed, emphasising the utilization of epigenetic enzymes and their inhibitors to re-program irresponsive BCs.

The clinical relevance of unfolded protein response signaling in breast cancer

Protein homeostasis regulated by the Endoplasmic Reticulum (ER) is a recognized process involved in cancer progression. ER stress activates the Unfolded Protein Response (UPR) and has been implicated in a variety of cancers. Given the role of the UPR activation in carcinogenesis, we hypothesized that UPR activation could be associated with pathological progression, higher clinical stage, and worse survival in breast cancer. A total of 4,416 breast cancer patients from multiple independent cohorts were analyzed. We defined the UPR pathway score by the degree of enrichment by Gene Set Variant Analysis and median was used to divide high vs. low score groups in each cohort. High UPR breast cancer significantly enriched not only cell proliferation-related but also other pro-cancerous gene sets consistently in both METABIC and GSE96058 cohort. Majority of UPR pathway score high cells in the bulk tumor were tumor cells compared to other cells, including stromal, T-, B-, and myeloid-cells (P<0.001). UPR score was significantly associated with advanced stage, high grade, and triple negative breast cancer (TNBC) (all P<0.001). High UPR breast cancer was associated with worse patient survival in both cohorts (all P<0.001). Among breast cancer subtype, ER-positive/HER2-negative breast cancer with high UPR was significantly associated with worse survival, but neither HER-positive nor TNBC. High UPR ER-positive/HER2-negative breast cancer was infiltrated with high level of Th1 and Th2 cells, M1 macrophage, and plasma cells. On the other hand, they were significantly infiltrated with high level of several types of stromal cells in tumor microenvironment (all P<0.001). Finally, high UPR metastatic breast cancer was also associated with worse patient survival (P=0.041). UPR signaling is associated with cancer aggressiveness, and worse survival, especially ER-positive/HER2-negative breast cancer subtype.

NR2F1, a Tumor Dormancy Marker, Is Expressed Predominantly in Cancer-Associated Fibroblasts and Is Associated with Suppressed Breast Cancer Cell Proliferation

BACKGROUND

Tumor dormancy is a crucial mechanism responsible for the late recurrence of breast cancer. Thus, we investigated the clinical relevance of the expression of NR2F1, a known dormancy biomarker.

METHODS

A total of 6758 transcriptomes of bulk tumors from multiple breast cancer patient cohorts and two single-cell sequence cohorts were analyzed.

RESULTS

Breast cancer (BC) with high NR2F1 expression enriched TGFβ signaling, multiple metastases, and stem cell-related pathways. Cell proliferation-related gene sets were suppressed, and MKi67 expression was lower in high NR2F1 BC. In tumors with high Nottingham grade, NR2F1 expression was found to be lower. There was no consistent relationship between NR2F1 expression and metastasis or survival. Cancer mutation rates, immune responses, and immune cell infiltrations were lower in high NR2F1 tumors, whereas the infiltration of stromal cells including cancer-associated fibroblasts (CAFs) was higher. NR2F1 was predominantly expressed in CAFs, particularly inflammatory CAFs, rather than in cancer cells, consistently in the two single-cell sequence cohorts.

CONCLUSIONS

NR2F1 expression in breast cancer is associated with tumor dormancy traits, and it is predominantly expressed in CAFs in the tumor microenvironment.

ENDORSE: a prognostic model for endocrine therapy in estrogen-receptor-positive breast cancers

Advanced and metastatic estrogen receptor-positive (ER+ ) breast cancers are often endocrine resistant. However, endocrine therapy remains the primary treatment for all advanced ER+ breast cancers. Treatment options that may benefit resistant cancers, such as add-on drugs that target resistance pathways or switching to chemotherapy, are only available after progression on endocrine therapy. Here we developed an endocrine therapy prognostic model for early and advanced ER+ breast cancers. The endocrine resistance (ENDORSE) model is composed of two components, each based on the empirical cumulative distribution function of ranked expression of gene signatures. These signatures include a feature set associated with long-term survival outcomes on endocrine therapy selected using lasso-regularized Cox regression and a pathway-based curated set of genes expressed in response to estrogen. We extensively validated ENDORSE in multiple ER+ clinical trial datasets and demonstrated superior and consistent performance of the model over clinical covariates, proliferation markers, and multiple published signatures. Finally, genomic and pathway analyses in patient data revealed possible mechanisms that may help develop rational stratification strategies for endocrine-resistant ER+ breast cancer patients.

Network Pharmacology-Based Strategy to Investigate the Anti-Breast Cancer Mechanisms of Spatholobus suberectus Dunn

Spatholobus suberectus Dunn (SSD) possesses potential antitumor activity; however, the mechanism underlying its anti-proliferative effect on breast cancer is unclear. In this study, we explored potential SSD targets for breast cancer treatment through a network pharmacology approach. First, by integrating multiple databases, a total of 16 potential bioactive compounds and 252 targets were screened. Differentially expressed genes (DEGs) were screened by analyzing breast cancer gene chip data from The Cancer Genome Atlas and Gene Expression Omnibus databases. By overlapping drug targets and DEGs, 33 common targets were found; their functions were further analyzed with Gene Ontology and KEGG analysis. A network of 16 compounds and 33 common targets was constructed, from which 10 hub targets were identified using CytoHubba. Based on the KEGG result and network analysis, the 33 common targets were mainly enriched in the peroxisome proliferator-activated receptor (PPAR) signaling pathway and PPARγ was identified as the potential target of SSD. Moreover, the 10 hub targets were correlated with prognosis and immune infiltration in breast cancer via bioinformatic analysis. Finally, molecular docking and experiments in vitro further verified the targeting ability and anti-breast cancer activity of SSD. SSD is promising in the treatment of breast cancer; PPARγ may be its potential therapeutic target.

Evolution of the Tumor Microenvironment toward Immune-Suppressive Seclusion during Brain Metastasis of Breast Cancer: Implications for Targeted Therapy

Simple Summary

Brain metastases (BM) of breast cancer (BC) are new targets of immunotherapy, but their characteristics are unclear. Therefore, we analyzed the differential expression profile of the tumor microenvironment (TME) in primary breast cancer brain metastasis (BCBM). In the TME of BCBM, immune-related pathways were downregulated and tumor intrinsic factors were upregulated. Moreover, CD8+ T cells and M1 macrophages with cytotoxic effects were decreased, but M2 cells were increased, in BM. Most tumor-suppressive immune functions ceased after BM with a molecular subtype shift. These results suggest the need for targeted therapy and immunotherapy strategies for BCBM.

Abstract

Breast cancer (BC) is the second most common solid malignant tumor that metastasizes to the brain. Despite emerging therapies such as immunotherapy, whether the tumor microenvironment (TME) in breast cancer brain metastasis (BCBM) has potential as a target of new treatments is unclear. Expression profiling of 770 genes in 12 pairs of primary BC and matched brain metastasis (BM) samples was performed using the NanoString nCounter PanCancer IO360^TM Panel. Immune cell profiles were validated by immunohistochemistry (IHC) in samples from 50 patients with BCBM. Pathway analysis revealed that immune-related pathways were downregulated. Immune cell profiling showed that CD8+ T cells and M1 macrophages were significantly decreased, and M2 macrophages were significantly increased, in BM compared to primary BC samples (p = 0.001, p = 0.021 and p = 0.007, respectively). CCL19 and CCL21, the top differentially expressed genes, were decreased significantly in BM compared to primary BC (p < 0.001, both). IHC showed that the CD8+ count was significantly lower (p = 0.027), and the CD163+ and CD206+ counts were higher, in BM than primary BC (p < 0.001, both). A low CD8+ T cell count, low CD86+ M1 macrophage count, and high M2/M1 macrophage ratio were related to unfavorable clinical outcomes. BC exhibits an immunosuppressive characteristic after metastasis to the brain. These findings will facilitate establishment of a treatment strategy for BCBM based on the TME of metastatic cancer.

Intra- and Interlaboratory Reproducibility of the Sensitivity to Endocrine Therapy Assay for Stage II/III Breast Cancer

BACKGROUND

The sensitivity to endocrine therapy assay (SET2,3) predicts treatment outcomes in Stage II-III breast cancer. SET2,3 measures transcription related to estrogen and progesterone receptors (SETER/PR index) and the molecular subtype (RNA4: ESR1, PGR, ERBB2, AURKA) from formalin-fixed paraffin-embedded (FFPE) tissue sections.

METHODS

We designed a nested study across 3 pathology laboratories, each testing 60 breast cancers twice in controlled batches. Laboratories macrodissected and directly homogenized the unstained FFPE tumor sections, then performed the QuantiGene Plex bead-based hybridization assay. SET2,3 was calculated centrally using predefined statistical R-scripts and applying pre-defined cutpoints. Concordance correlation coefficient (CCC) was calculated from continuous measurements and Kappa statistic from categorical results. A mixed-effects model estimated contributions to bias (fixed effects) and variance (random effects) from the replicated design.

RESULTS

Intralaboratory (CCC 0.96-0.99) and interlaboratory (CCC 0.98-0.99) SET2,3 results were concordant, with rates of agreement for high/low categorization within (Kappa 0.83-0.93) and between laboratories (Kappa 0.87-0.88). The relative contributions to overall variance of SET2,3 measurements were 96.90% from biological differences between cancers, 0.67% from interlaboratory variability, and 2.44% from residual causes including intralaboratory replicates. Similar results were obtained with SETER/PR, the baseline prognostic index calculated using pathological or clinical tumor and nodal staging information, and the 4 individual genes (ESR1, PGR, ERBB2, and AURKA).

CONCLUSION

Intra- and interpathology laboratory measurements of SET2,3 and its components were highly reproducible when tested from FFPE tumor sections.

Durvalumab with olaparib and paclitaxel for high-risk HER2-negative stage II/III breast cancer: Results from the adaptively randomized I-SPY2 trial

The combination of PD-L1 inhibitor durvalumab and PARP inhibitor olaparib added to standard paclitaxel neoadjuvant chemotherapy (durvalumab/olaparib/paclitaxel [DOP]) was investigated in the phase II I-SPY2 trial of stage II/III HER2-negative breast cancer. Seventy-three participants were randomized to DOP and 299 to standard of care (paclitaxel) control. DOP increased pathologic complete response (pCR) rates in all HER2-negative (20%-37%), hormone receptor (HR)-positive/HER2-negative (14%-28%), and triple-negative breast cancer (TNBC) (27%-47%). In HR-positive/HER2-negative cancers, MammaPrint ultra-high (MP2) cases benefited selectively from DOP (pCR 64% versus 22%), no benefit was seen in MP1 cancers (pCR 9% versus 10%). Overall, 12.3% of patients in the DOP arm experienced immune-related grade 3 adverse events versus 1.3% in control. Gene expression signatures associated with immune response were positively associated with pCR in both arms, while a mast cell signature was associated with non-pCR. DOP has superior efficacy over standard neoadjuvant chemotherapy in HER2-negative breast cancer, particularly in a highly sensitive subset of high-risk HR-positive/HER2-negative patients.

High-throughput CRISPR-mediated 3D enrichment platform for functional interrogation of chemotherapeutic resistance

Cancer is a disease of somatic mutations. These cellular mutations compete to dominate their microenvironment and dictate the disease outcome. While a therapeutic approach to target-specific oncogenic driver mutations helps to manage the disease, subsequent molecular evolution of tumor cells threatens to overtake therapeutic progress. There is a need for rapid, high-throughput, unbiased in vitro discovery screening platforms that capture the native complexities of the tumor and rapidly identify mutations that confer chemotherapeutic drug resistance. Taking the example of the CDK4/6 inhibitor (CDK4/6i) class of drugs, we show that the pooled in vitro CRISPR screening platform enables rapid discovery of drug resistance mutations in a three-dimensional (3D) setting. Gene-edited cancer cell clones assembled into an organotypic multicellular tumor spheroid (MCTS), exposed to CDK4/6i caused selection and enrichment of the most drug-resistant phenotypes, detectable by next-gen sequencing after a span of 28 days. The platform was sufficiently sensitive to enrich for even a single drug-resistant cell within a large, drug-responsive complex 3D tumor spheroid. The genome-wide 3D CRISPR-mediated knockout screen (>18,000 genes) identified several genes whose disruptions conferred resistance to CDK4/6i. Furthermore, multiple novel candidate genes were identified as top hits only in the microphysiological 3D enrichment assay platform and not the conventional 2D assays. Taken together, these findings suggest that including phenotypic 3D resistance profiling in decision trees could improve discovery and reconfirmation of drug resistance mechanisms and afford a platform for exploring noncell autonomous interactions, selection pressures, and clonal competition.

miRGTF-net: Integrative miRNA-gene-TF network analysis reveals key drivers of breast cancer recurrence

Analysis of regulatory networks is a powerful framework for identification and quantification of intracellular interactions. We introduce miRGTF-net, a novel tool for construction of miRNA-gene-TF networks. We consider multiple transcriptional and post-transcriptional interaction types, including regulation of gene and miRNA expression by transcription factors, gene silencing by miRNAs, and co-expression of host genes with their intronic miRNAs. The underlying algorithm uses information on experimentally validated interactions as well as integrative miRNA/mRNA expression profiles in a given set of samples. The latter ensures simultaneous tissue-specificity and biological validity of interactions. We applied miRGTF-net to paired miRNA/mRNA-sequencing data of breast cancer samples from The Cancer Genome Atlas (TCGA). Together with topological analysis of the constructed network we showed that considered players can form reliable prognostic gene signatures for ER-positive breast cancer. A number of signatures demonstrated remarkably high accuracy on transcriptomic data obtained by both microarrays and RNA sequencing from several independent patient cohorts. Furthermore, an essential part of prognostic genes were identified as direct targets of transcription factor E2F1. The putative interplay between estrogen receptor alpha and E2F1 was suggested as a potential recurrence factor in patients treated with tamoxifen. Source codes of miRGTF-net are available at GitHub (https://github.com/s-a-nersisyan/miRGTF-net).

Technical Validity of a Customized Assay of Sensitivity to Endocrine Therapy Using Sections from Fixed Breast Cancer Tissue

BACKGROUND

We translated a multigene expression index to predict sensitivity to endocrine therapy for Stage II-III breast cancer (SET2,3) to hybridization-based expression assays of formalin-fixed paraffin-embedded (FFPE) tissue sections. Here we report the technical validity with FFPE samples, including preanalytical and analytical performance.

METHODS

We calibrated SET2,3 from microarrays (Affymetrix U133A) of frozen samples to hybridization-based assays of FFPE tissue, using bead-based QuantiGene Plex (QGP) and slide-based NanoString (NS). The following preanalytical and analytical conditions were tested in controlled studies: replicates within and between frozen and fixed samples, age of paraffin blocks, homogenization of fixed sections versus extracted RNA, core biopsy versus surgically resected tumor, technical replicates, precision over 20 weeks, limiting dilution, linear range, and analytical sensitivity. Lin's concordance correlation coefficient (CCC) was used to measure concordance between measurements.

RESULTS

SET2,3 index was calibrated to use with QGP (CCC 0.94) and NS (CCC 0.93) technical platforms, and was validated in two cohorts of older fixed samples using QGP (CCC 0.72, 0.85) and NS (CCC 0.78, 0.78). QGP assay was concordant using direct homogenization of fixed sections versus purified RNA (CCC 0.97) and between core and surgical sample types (CCC 0.90), with 100% accuracy in technical replicates, 1-9% coefficient of variation over 20 weekly tests, linear range 3.0-11.5 (log2 counts), and analytical sensitivity ≥2.0 (log2 counts).

CONCLUSIONS

Measurement of the novel SET2,3 assay was technically valid from fixed tumor sections of biopsy or resection samples using simple, inexpensive, hybridization methods, without the need for RNA purification.

Diseasome and comorbidities complexities of SARS-CoV-2 infection with common malignant diseases

With the increasing number of immunoinflammatory complexities, cancer patients have a higher risk of serious disease outcomes and mortality with SARS-CoV-2 infection which is still not clear. In this study, we aimed to identify infectome, diseasome and comorbidities between COVID-19 and cancer via comprehensive bioinformatics analysis to identify the synergistic severity of the cancer patient for SARS-CoV-2 infection. We utilized transcriptomic datasets of SARS-CoV-2 and different cancers from Gene Expression Omnibus and Array Express Database to develop a bioinformatics pipeline and software tools to analyze a large set of transcriptomic data and identify the pathobiological relationships between the disease conditions. Our bioinformatics approach revealed commonly dysregulated genes (MARCO, VCAN, ACTB, LGALS1, HMOX1, TIMP1, OAS2, GAPDH, MSH3, FN1, NPC2, JUND, CHI3L1, GPNMB, SYTL2, CASP1, S100A8, MYO10, IGFBP3, APCDD1, COL6A3, FABP5, PRDX3, CLEC1B, DDIT4, CXCL10 and CXCL8), common gene ontology (GO), molecular pathways between SARS-CoV-2 infections and cancers. This work also shows the synergistic complexities of SARS-CoV-2 infections for cancer patients through the gene set enrichment and semantic similarity. These results highlighted the immune systems, cell activation and cytokine production GO pathways that were observed in SARS-CoV-2 infections as well as breast, lungs, colon, kidney and thyroid cancers. This work also revealed ribosome biogenesis, wnt signaling pathway, ribosome, chemokine and cytokine pathways that are commonly deregulated in cancers and COVID-19. Thus, our bioinformatics approach and tools revealed interconnections in terms of significant genes, GO, pathways between SARS-CoV-2 infections and malignant tumors.

Differences in Tumor Immune Microenvironment in Metastatic Sites of Breast Cancer

Introduction: Tumor immune microenvironment (TIME) promotes immune escape, allowing for tumor progression and metastasis. In spite of the current evidence of the complicated role of immune cells in promoting or suppressing cancer progression, the heterogeneity of TIME according to the tumor site has been scarcely investigated. Here, we analyzed transcriptomic profiles of metastatic breast cancer to understand how TIME varies according to tumor sites.

Methods: Two gene expression datasets from metastatic breast cancer of various sites and a single-cell RNA sequencing dataset of primary breast cancer and metastatic lymph nodes were analyzed. The immune cell-type enrichment of each tumor was estimated. Immune cell types were identified by clustering analysis, and the proportions of cell types in TIME were assessed according to the tumor site.

Results: Metastatic bone lesions showed more neutrophils than breast lesions. Tumors clustered according to immune cell type were significantly associated with tumor site. In single-cell analyses, the TIMEs of metastatic lymph nodes showed fewer macrophages than those of primary tumors. Differentially expressed gene signatures in the primary tumor and metastatic lymph nodes were associated with macrophage activation.

Conclusion: We conclude that metastatic sites show variable enrichment patterns of immune cells, and that the TIME of metastatic lesions should be considered in precise immuno-oncology treatments.

Predicted sensitivity to endocrine therapy for stage II-III hormone receptor-positive and HER2-negative (HR+/HER2-) breast cancer before chemo-endocrine therapy

BACKGROUND

We proposed that a test for sensitivity to the adjuvant endocrine therapy component of treatment for patients with stage II-III breast cancer (SET2,3) should measure transcription related to estrogen and progesterone receptors (SET_ER/PR index) adjusted for a baseline prognostic index (BPI) combining clinical tumor and nodal stage with molecular subtype by RNA4 (ESR1, PGR, ERBB2, and AURKA).

PATIENTS AND METHODS

Patients with clinically high-risk, hormone receptor-positive (HR+), human epidermal growth factor receptor 2 (HER2)-negative (HR+/HER2-) breast cancer received neoadjuvant taxane-anthracycline chemotherapy, surgery with measurement of residual cancer burden (RCB), and then adjuvant endocrine therapy. SET2,3 was measured from pre-treatment tumor biopsies, evaluated first in an MD Anderson Cancer Center (MDACC) cohort (n = 307, 11 years' follow-up, U133A microarrays), cut point was determined, and then independent, blinded evaluation was carried out in the I-SPY2 trial (n = 268, high-risk MammaPrint result, 3.8 years' follow-up, Agilent-44K microarrays, NCI Clinical Trials ID: NCT01042379). Primary outcome measure was distant relapse-free survival. Multivariate Cox regression models tested prognostic independence of SET2,3 relative to RCB and other molecular prognostic signatures, and whether other prognostic signatures could substitute for SET_ER/PR or RNA4 components of SET2,3.

RESULTS

SET2,3 added independent prognostic information to RCB in the MDACC cohort: SET2,3 [hazard ratio (HR) 0.23, P = 0.004] and RCB (HR 1.77, P < 0.001); and the I-SPY2 trial: SET2,3 (HR 0.27, P = 0.031) and RCB (HR 1.68, P = 0.008). SET2,3 provided similar prognostic information irrespective of whether RCB-II or RCB-III after chemotherapy, and in both luminal subtypes. Conversely, RCB was most strongly prognostic in cancers with low SET2,3 status (MDACC P < 0.001, I-SPY2 P < 0.001). Other molecular signatures were not independently prognostic; they could effectively substitute for RNA4 subtype within the BPI component of SET2,3, but they could not effectively substitute for SET_ER/PR index.

CONCLUSIONS

SET2,3 added independent prognostic information to chemotherapy response (RCB) and baseline prognostic score or subtype. Approximately 40% of patients with clinically high-risk HR+/HER2- disease had high SET2,3 and could be considered for clinical trials of neoadjuvant endocrine-based treatment.

Targeted RNAseq assay incorporating unique molecular identifiers for improved quantification of gene expression signatures and transcribed mutation fraction in fixed tumor samples

BACKGROUND

Our objective was to assess whether modifications to a customized targeted RNA sequencing (RNAseq) assay to include unique molecular identifiers (UMIs) that collapse read counts to their source mRNA counts would improve quantification of transcripts from formalin-fixed paraffin-embedded (FFPE) tumor tissue samples. The assay (SET4) includes signatures that measure hormone receptor and PI3-kinase related transcriptional activity (SETER/PR and PI3Kges), and measures expression of selected activating point mutations and key breast cancer genes.

METHODS

Modifications included steps to introduce eight nucleotides-long UMIs during reverse transcription (RT) in bulk solution, followed by polymerase chain reaction (PCR) of labeled cDNA in droplets, with optimization of the polymerase enzyme and reaction conditions. We used Lin's concordance correlation coefficient (CCC) to measure concordance, including precision (Rho) and accuracy (Bias), and nonparametric tests (Wilcoxon, Levene's) to compare the modified (NEW) SET4 assay to the original (OLD) SET4 assay and to whole transcriptome RNAseq using RNA from matched fresh frozen (FF) and FFPE samples from 12 primary breast cancers.

RESULTS

The modified (NEW) SET4 assay measured single transcripts (p< 0.001) and SETER/PR (p=0.002) more reproducibly in technical replicates from FFPE samples. The modified SET4 assay was more precise for measuring single transcripts (Rho 0.966 vs 0.888, p< 0.01) but not multigene expression signatures SETER/PR (Rho 0.985 vs 0.968) or PI3Kges (Rho 0.985 vs 0.946) in FFPE, compared to FF samples. It was also more precise than wtRNAseq of FFPE for measuring transcripts (Rho 0.986 vs 0.934, p< 0.001) and SETER/PR (Rho 0.993 vs 0.915, p=0.004), but not PI3Kges (Rho 0.988 vs 0.945, p=0.051). Accuracy (Bias) was comparable between protocols. Two samples carried a PIK3CA mutation, and measurements of transcribed mutant allele fraction was similar in FF and FFPE samples and appeared more precise with the modified SET4 assay. Amplification efficiency (reads per UMI) was consistent in FF and FFPE samples, and close to the theoretically expected value, when the library size exceeded 400,000 aligned reads.

CONCLUSIONS

Modifications to the targeted RNAseq protocol for SET4 assay significantly increased the precision of UMI-based and reads-based measurements of individual transcripts, multi-gene signatures, and mutant transcript fraction, particularly with FFPE samples.

Hormonal modulation of ESR1 mutant metastasis

Estrogen receptor alpha gene (ESR1) mutations occur frequently in ER-positive metastatic breast cancer, and confer clinical resistance to aromatase inhibitors. Expression of the ESR1 Y537S mutation induced an epithelial-mesenchymal transition (EMT) with cells exhibiting enhanced migration and invasion potential in vitro. When small subpopulations of Y537S ESR1 mutant cells were injected along with WT parental cells, tumor growth was enhanced with mutant cells becoming the predominant population in distant metastases. Y537S mutant primary xenograft tumors were resistant to the antiestrogen tamoxifen (Tam) as well as to estradiol (E2) withdrawal. Y537S ESR1 mutant primary tumors metastasized efficiently in the absence of E2; however, Tam treatment significantly inhibited metastasis to distant sites. We identified a nine-gene expression signature, which predicted clinical outcomes of ER-positive breast cancer patients, as well as breast cancer metastasis to the lung. Androgen receptor (AR) protein levels were increased in mutant models, and the AR agonist dihydrotestosterone significantly inhibited estrogen-regulated gene expression, EMT, and distant metastasis in vivo, suggesting that AR may play a role in distant metastatic progression of ESR1 mutant tumors.

Degree of Early Estrogen Response Predict Survival after Endocrine Therapy in Primary and Metastatic ER-Positive Breast Cancer

Simple Summary

Over 70% of breast cancer patients in the US have estrogen receptor (ER)-positive tumors. A better predictive biomarker of endocrine therapy would be useful to improve patient compliance. We found that estrogen response early score generated by a GSEA algorithm was significantly associated with immune cell infiltrations, patient survival, and endocrine therapy response in ER-positive breast cancer. Furthermore, the score may be a useful tool to predict response to endocrine therapy in both primary and metastatic breast cancer compared to ER gene expression. This study demonstrates that the estrogen response early score may be a useful prognostic and predicative biomarker in patients with either primary or metastatic breast cancer.

Abstract

Endocrine therapy is the gold-standard treatment for ER-positive/HER2-negative breast cancer. Although its clear benefit, patient compliance is poor (50–80%) due to its long administration period and adverse effects. Therefore, a predictive biomarker that can predict whether endocrine therapy is truly beneficial may improve patient compliance. In this study, we use estrogen response early gene sets of gene set enrichment assay algorithm as the score. We hypothesize that the score could predict the response to endocrine therapy and survival of breast cancer patients. A total of 6549 breast cancer from multiple patient cohorts were analyzed. The score was highest in ER-positive/HER2-negative compared to the other subtypes. Earlier AJCC stage, as well as lower Nottingham pathological grade, were associated with a high score. Low score tumors enriched only allograft rejection gene set, and was significantly infiltrated with immune cells, and high cytolytic activity score. A low score was significantly associated with a worse response to endocrine therapy and worse survival in both primary and metastatic breast cancer patients. The hazard ratio was double that of ESR1 expression. In conclusion, the estrogen response early score predicts response to endocrine therapy and is associated with survival in primary and metastatic breast cancer.

MYC Targets Scores Are Associated with Cancer Aggressiveness and Poor Survival in ER-Positive Primary and Metastatic Breast Cancer

MYC is one of the most studied oncogenes that is known to promote cell proliferation. We utilized MYC targets v1 and MYC targets v2 scores of gene set variation analysis and hypothesized that these scores correlate with tumor aggressiveness and survival outcomes. We examined a total of 3109 breast cancer patients from TCGA, METABRIC, and GSE124647 cohorts. In each cohort, the patients were divided into high- and low-score groups using the upper third value as the cut off. As expected, higher scores were related to increased cell proliferation and worse clinical and pathologic features. High MYC targets scores were associated with worse survival, specifically in primary ER-positive breast cancer, consistently in both TCGA and METABRIC cohorts. In ER-positive breast cancer, high MYC targets v1, but not v2 score, was associated with high mutation load, and high MYC targets v1 and v2 scores were both associated with increased infiltration of pro- and anti-cancerous immune cells. We found that high MYC scores were associated with worse survival in metastatic breast cancer. Our findings show that the MYC targets v1 and v2 scores are associated with tumor aggressiveness and poor prognosis in ER-positive primary tumors, as well as in metastatic breast cancer.

ColoType: a forty gene signature for consensus molecular subtyping of colorectal cancer tumors using whole-genome assay or targeted RNA-sequencing

Colorectal cancer (CRC) tumors can be partitioned into four biologically distinct consensus molecular subtypes (CMS1-4) using gene expression. Evidence is accumulating that tumors in different subtypes are likely to respond differently to treatments. However, to date, there is no clinical diagnostic test for CMS subtyping. In this study, we used novel methodology in a multi-cohort training domain (n = 1,214) to develop the ColoType scores and classifier to predict CMS1-4 based on expression of 40 genes. In three validation cohorts (n = 1,744, in total) representing three distinct gene-expression measurement technologies, ColoType predicted gold-standard CMS subtypes with accuracies 0.90, 0.91, 0.88, respectively. To accommodate for potential intratumoral heterogeneity and tumors of mixed subtypes, ColoType was designed to report continuous scores measuring the prevalence of each of CMS1-4 in a tumor, in addition to specifying the most prevalent subtype. For analysis of clinical specimens, ColoType was also implemented with targeted RNA-sequencing (Illumina AmpliSeq). In a series of formalin-fixed, paraffin-embedded CRC samples (n = 49), ColoType by targeted RNA-sequencing agreed with subtypes predicted by two independent methods with accuracies 0.92, 0.82, respectively. With further validation, ColoType by targeted RNA-sequencing, may enable clinical application of CMS subtyping with widely-available and cost-effective technology.

Progesterone receptor membrane component 1 regulates lipid homeostasis and drives oncogenic signaling resulting in breast cancer progression

Background

PGRMC1 (progesterone receptor membrane component 1) is a highly conserved heme binding protein, which is overexpressed especially in hormone receptor-positive breast cancer and plays an important role in breast carcinogenesis. Nevertheless, little is known about the mechanisms by which PGRMC1 drives tumor progression. The aim of our study was to investigate the involvement of PGRMC1 in cholesterol metabolism to detect new mechanisms by which PGRMC1 can increase lipid metabolism and alter cancer-related signaling pathways leading to breast cancer progression.

Methods

The effect of PGRMC1 overexpression and silencing on cellular proliferation was examined in vitro and in a xenograft mouse model.

Next, we investigated the interaction of PGRMC1 with enzymes involved in the cholesterol synthesis pathway such as CYP51, FDFT1, and SCD1. Further, the impact of PGRMC1 expression on lipid levels and expression of enzymes involved in lipid homeostasis was examined. Additionally, we assessed the role of PGRMC1 in key cancer-related signaling pathways including EGFR/HER2 and ERα signaling.

Results

Overexpression of PGRMC1 resulted in significantly enhanced proliferation. PGRMC1 interacted with key enzymes of the cholesterol synthesis pathway, alters the expression of proteins, and results in increased lipid levels. PGRMC1 also influenced lipid raft formation leading to altered expression of growth receptors in membranes of breast cancer cells. Analysis of activation of proteins revealed facilitated ERα and EGFR activation and downstream signaling dependent on PGRMC1 overexpression in hormone receptor-positive breast cancer cells. Depletion of cholesterol and fatty acids induced by statins reversed this growth benefit.

Conclusion

PGRMC1 may mediate proliferation and progression of breast cancer cells potentially by altering lipid metabolism and by activating key oncogenic signaling pathways, such as ERα expression and activation, as well as EGFR signaling. Our present study underlines the potential of PGRMC1 as a target for anti-cancer therapy.

The E2F Pathway Score as a Predictive Biomarker of Response to Neoadjuvant Therapy in ER+/HER2- Breast Cancer

E2F transcription factors play critical roles in the cell cycle. Therefore, their activity is expected to reflect tumor aggressiveness and responsiveness to therapy. We scored 3905 tumors of nine breast cancer cohorts for this activity based on their gene expression for the Hallmark E2F targets gene set. As expected, tumors with a high score had an increased expression of cell proliferation-related genes. A high score was significantly associated with shorter patient survival, greater MKI67 expression, histological grade, stage, and genomic aberrations. Furthermore, metastatic tumors had higher E2F scores than the primary tumors from which they arose. Although tumors with a high score had greater infiltration by both pro- and anti-cancerous immune cells, they had an increased expression of immune checkpoint genes. Estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative cancer with a high E2F score achieved a significantly higher pathological complete response (pCR) rate to neoadjuvant chemotherapy. The E2F score was significantly associated with the expression of cyclin-dependent kinase (CDK)-related genes and strongly correlated with sensitivity to CDK inhibition in cell lines. In conclusion, the E2F score is a marker of breast cancer aggressiveness and predicts the responsiveness of ER-positive/HER2-negative patients to neoadjuvant chemotherapy and possibly to CDK and immune checkpoint inhibitors.

Hormone Receptor-Status Prediction in Breast Cancer Using Gene Expression Profiles and Their Macroscopic Landscape

The cost of next-generation sequencing technologies is rapidly declining, making RNA-seq-based gene expression profiling (GEP) an affordable technique for predicting receptor expression status and intrinsic subtypes in breast cancer patients. Based on the expression levels of co-expressed genes, GEP-based receptor-status prediction can classify clinical subtypes more accurately than can immunohistochemistry (IHC). Using data from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA BRCA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets, we identified common predictor genes found in both datasets and performed receptor-status prediction based on these genes. By assessing the survival outcomes of patients classified using GEP- or IHC-based receptor status, we compared the prognostic value of the two methods. We found that GEP-based HR prediction provided higher concordance with the intrinsic subtypes and a stronger association with treatment outcomes than did IHC-based hormone receptor (HR) status. GEP-based prediction improved the identification of patients who could benefit from hormone therapy, even in patients with non-luminal breast cancer. We also confirmed that non-matching subgroup classification affected the survival of breast cancer patients and that this could be largely overcome by GEP-based receptor-status prediction. In conclusion, GEP-based prediction provides more reliable classification of HR status, improving therapeutic decision making for breast cancer patients.

G2M Cell Cycle Pathway Score as a Prognostic Biomarker of Metastasis in Estrogen Receptor (ER)-Positive Breast Cancer

The vast majority of breast cancer death is a result of metastasis. Thus, accurate identification of patients who are likely to have metastasis is expected to improve survival. The G2M checkpoint plays a critical role in cell cycle. We hypothesized that breast cancer tumors with high activity of G2M pathway genes are more aggressive and likely to metastasize. To test this, we used the single-sample gene set variation analysis method to calculate the score for the Hallmark G2M checkpoint pathway using gene expression data of a total of 4626 samples from 12 human breast cancer cohorts. As expected, a high G2M pathway score correlated with enriched tumor expression of other cell proliferation-related gene sets. The score was significantly associated with clinical aggressive features of tumors and patient survival in estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative breast cancer. Interestingly, a high G2M score of metastasis tumors was also significantly associated with worse survival. In primary as well as metastasis tumors with high scores, the infiltration of both pro- and anti-cancerous immune cells increased. Tumor G2M score was also associated with treatment response to systemic chemotherapy in ER-positive/HER2-negative cancer, and was predictive of response to cyclin-dependent kinase inhibition therapy.

The impact of RNA extraction method on accurate RNA sequencing from formalin-fixed paraffin-embedded tissues

Background

Utilization of RNA sequencing methods to measure gene expression from archival formalin-fixed paraffin-embedded (FFPE) tumor samples in translational research and clinical trials requires reliable interpretation of the impact of pre-analytical variables on the data obtained, particularly the methods used to preserve samples and to purify RNA.

Methods

Matched tissue samples from 12 breast cancers were fresh frozen (FF) and preserved in RNAlater or fixed in formalin and processed as FFPE tissue. Total RNA was extracted and purified from FF samples using the Qiagen RNeasy kit, and in duplicate from FFPE tissue sections using three different kits (Norgen, Qiagen and Roche). All RNA samples underwent whole transcriptome RNA sequencing (wtRNAseq) and targeted RNA sequencing for 31 transcripts included in a signature of sensitivity to endocrine therapy. We assessed the effect of RNA extraction kit on the reliability of gene expression levels using linear mixed-effects model analysis, concordance correlation coefficient (CCC) and differential analysis. All protein-coding genes in the wtRNAseq and three gene expression signatures for breast cancer were assessed for concordance.

Results

Despite variable quality of the RNA extracted from FFPE samples by different kits, all had similar concordance of overall gene expression from wtRNAseq between matched FF and FFPE samples (median CCC 0.63–0.66) and between technical replicates (median expression difference 0.13–0.22). More than half of genes were differentially expressed between FF and FFPE, but with low fold change (median |LFC| 0.31–0.34). Two out of three breast cancer signatures studied were highly robust in all samples using any kit, whereas the third signature was similarly discordant irrespective of the kit used. The targeted RNAseq assay was concordant between FFPE and FF samples using any of the kits (CCC 0.91–0.96).

Conclusions

The selection of kit to purify RNA from FFPE did not influence the overall quality of results from wtRNAseq, thus variable reproducibility of gene signatures probably relates to the reliability of individual gene selected and possibly to the algorithm. Targeted RNAseq showed promising performance for clinical deployment of quantitative assays in breast cancer from FFPE samples, although numerical scores were not identical to those from wtRNAseq and would require calibration.