PAM50 Intrinsic Subtype Profiles in Primary and Metastatic Breast Cancer Show a Significant Shift toward More Aggressive Subtypes with Prognostic Implications

Prognostic relevance of CD163+ immune cells in patients with metastatic breast cancer

Metastatic breast cancer (MBC) is generally considered an incurable disease and even though new treatments are available, the median survival is approximately three years. The introduction of immune therapies for MBC highlights the importance of the immune system in cancer progression and treatment. CD163+ anti-inflammatory myeloid cells, including tumor associated macrophages (TAMs), are known to be of relevance in early breast cancer but their role in MBC is not yet established. Here we determine the levels of CD163+ immune cells in 139 patients with newly diagnosed MBC by using Immunohistochemistry (IHC) and gene expression analyses (GEX). We aim to determine changes and distribution of CD163+ immune cells during tumor progression from primary tumors (PT) to lymph node metastases (LNM) and distant metastases (DM). In addition, we evaluate associations between CD163+ immune cells, clinicopathological factors and disease outcome (progression-free and overall survival; PFS and OS, respectively). Despite similar distribution, high levels of CD163+ immune cells in the tumor nest of PT, but not in LNM or DM, associated with adverse prognostic features including higher grade and molecular subtype, as well as with shorter PFS and OS, however this observation was not significant after adjusted multivariate analyses. Finally, high levels of CD163+ immune cells in PT, as well as GEX in PT and synchronous LNM associated with shorter OS from the initial diagnosis. These results indicate that evaluating the levels of CD163+ immune cells may identify MBC patients with a worse prognosis. Unraveling the role of CD163+ immune cells in the complex immune responses in MBC is highly relevant for improving future immune therapies.

Integrative Analysis of ATAC-Seq and RNA-Seq through Machine Learning Identifies 10 Signature Genes for Breast Cancer Intrinsic Subtypes

Breast cancer is a heterogeneous disease composed of various biologically distinct subtypes, each characterized by unique molecular features. Its formation and progression involve a complex, multistep process that includes the accumulation of numerous genetic and epigenetic alterations. Although integrating RNA-seq transcriptome data with ATAC-seq epigenetic information provides a more comprehensive understanding of gene regulation and its impact across different conditions, no classification model has yet been developed for breast cancer intrinsic subtypes based on such integrative analyses. In this study, we employed machine learning algorithms to predict intrinsic subtypes through the integrative analysis of ATAC-seq and RNA-seq data. We identified 10 signature genes (CDH3, ERBB2, TYMS, GREB1, OSR1, MYBL2, FAM83D, ESR1, FOXC1, and NAT1) using recursive feature elimination with cross-validation (RFECV) and a support vector machine (SVM) based on SHAP (SHapley Additive exPlanations) feature importance. Furthermore, we found that these genes were primarily associated with immune responses, hormone signaling, cancer progression, and cellular proliferation.

Clinical applications of next-generation sequencing-based ctDNA analyses in breast cancer: defining treatment targets and dynamic changes during disease progression

The advancements in the detection and characterization of circulating tumor DNA (ctDNA) have revolutionized precision medicine and are likely to transform standard clinical practice. The non-invasive nature of this approach allows for molecular profiling of the entire tumor entity, while also enabling real-time monitoring of the effectiveness of cancer therapies as well as the identification of resistance mechanisms to guide targeted therapy. Although the field of ctDNA studies offers a wide range of applications, including in early disease, in this review we mainly focus on the role of ctDNA in the dynamic molecular characterization of unresectable locally advanced and metastatic BC (mBC). Here, we provide clinical practice guidance for the rapidly evolving field of molecular profiling of mBC, outlining the current landscape of liquid biopsy applications and how to choose the right ctDNA assay. Additionally, we underline the importance of exploring the clinical relevance of novel molecular alterations that potentially represent therapeutic targets in mBC, along with mutations where targeted therapy is already approved. Finally, we present a potential roadmap for integrating ctDNA analysis into clinical practice.

Hormone receptor mRNA and protein levels as predictors of premenopausal tamoxifen benefit

BACKGROUND AND PURPOSE

Tamoxifen remains an important adjuvant treatment in premenopausal patients with hormone receptor-positive breast cancer. Thus, determination of hormone receptors is important. Here, we compare cytosol-based methods, immunohistochemistry (IHC), and gene expression (GEX) analysis for determining hormone receptor status in premenopausal breast cancer patients from a randomised tamoxifen trial, to evaluate their performance in identifying patients that benefit from tamoxifen.

PATIENTS AND METHODS

Premenopausal patients (n=564) were randomised to 2 years of tamoxifen or no systemic treatment. Estrogen receptor (ER) and progesterone receptor (PR) status by protein expression measured by cytosol-based methods and IHC, and mRNA by GEX analysis were compared in 313 patients with available data from all methods. Kaplan Meier estimates and Cox regression were used to evaluate the treatment-predictive value for recurrence-free interval (RFi) and overall survival (OS). Median follow-up for event-free patients was 26 (RFi) and 33 (OS) years.

RESULTS

The mRNA data of ESR1 and PGR distributed bimodally, patterns confirmed in an independent cohort. Kappa-values between all methods were 0.76 and 0.79 for ER and PR, respectively. Tamoxifen improved RFi in patients with ER-positive (ER+) or PR-positive (PR+) tumours (Hazard Ratio [HR] and 95% confidence interval [CI]), cytosol-ER+ 0.53 [0.36-0.79]; IHC-ER+ 0.55 [0.38-0.79]; GEX-ER+ 0.54 [0.37-0.77]; cytosol-PR+ 0.49 [0.34-0.72]; IHC-PR+ 0.58 [0.40-0.85]; GEX-PR+ 0.55 [0.38-0.80]). Results were similar for OS.

INTERPRETATION

These methods can all identify patients that benefit from 2 years of tamoxifen with equal performance, indicating that GEX data might be used to guide adjuvant tamoxifen therapy.

Gene expression in metastatic breast cancer-patterns in primary tumors and metastatic tissue with prognostic potential

Background: Metastatic breast cancer (MBC) is the main cause of breast cancer-related death. The outcome of MBC varies, and there is a lack of biomarkers to aid in prognostication. The primary aim of this study was to evaluate the prognostic value of gene expression (GEX) signatures in the primary tumor (PT) and distant metastasis (DM) for progression-free survival (PFS) and overall survival (OS). The secondary aim was to describe GEX changes through MBC evolution and to identify MBC subtypes. Methods: RNA was extracted from the PT, lymph node metastasis (LNM), and DM from MBC patients in a prospective observational study (n = 142; CTC-MBC NCT01322893) and was subjected to GEX analysis retrospectively using the NanoString Breast Cancer 360™ panel. 31 continuous GEX variables in DMs and PTs were analyzed for PFS and OS by Cox regression analysis and Kaplan-Meier estimates. Multivariable Cox regressions were adjusted for number of DM sites and CTCs, visceral metastasis, ECOG status, age at MBC diagnosis and, in additional analyses, PAM50 subtype. Differential GEX analyses and Euclidean distances were used to describe subgroup differences and visualize within-patient heterogeneity. Results: Compared to DM GEX, GEX of the PT was at least equally useful for predicting MBC outcome. The strongest marker for a favorable PFS, both when expressed in the PT and the DM was AR, even after adjustment for prognostic markers including PAM50. GEX signatures related to hormone responsiveness, including ESR1, FOXA1, PGR, and AR were favorable prognostic markers, and the p53 signature was unfavorable for PFS when expressed in PT or DM. The previously published PAM50MET signature was prognostic for both PFS and OS. We established five distinct DM GEX profiles where two associated with liver and bone metastases, respectively. Finally, we identified four DM GEX profiles able to identify MBCs with poor OS in this cohort. Conclusion: GEX of both DM and PT are useful in MBC prognostication. GEX of AR adds prognostic information for MBC. Our descriptive analyses illuminate the biological differences between MBCs in relation to outcome and metastatic site.

Intrinsic Subtype and Overall Survival of Patients with Advanced HR+/HER2- Breast Cancer Treated with Ribociclib and ET: Correlative Analysis of MONALEESA-2, -3, -7

PURPOSE

The MONALEESA-2, -3, -7 trials demonstrated statistically significant and clinically meaningful progression-free survival and overall survival (OS) benefits with ribociclib plus endocrine therapy (ET) versus ET alone in hormone receptor-positive, HER2-negative (HR+/HER2-) advanced breast cancer (ABC). Understanding the association of intrinsic subtypes with survival outcomes could potentially guide treatment decisions. Here, we evaluated the association of intrinsic subtypes with OS in MONALEESA-2, -3, -7.

EXPERIMENTAL DESIGN

Tumor samples from MONALEESA-2, -3, -7 underwent PAM50-based subtyping. The relationship between subtypes and OS was assessed using univariable and multivariable Cox proportional hazards models. Multivariable models were adjusted for clinical prognostic factors.

RESULTS

Overall, 990 tumors (among 2,066 patients) from ribociclib (n = 580) and placebo (n = 410) arms were profiled. Subtype distribution was luminal A, 54.5%; luminal B, 28.0%; HER2-enriched (HER2E) 14.6%; and basal-like, 2.8%; and was consistent across treatment arms. The luminal A subtype had the best OS outcomes in both arms, while basal-like had the worst. Patients with HER2E (HR, 0.60; P = 0.018), luminal B (HR, 0.69; P = 0.023), and luminal A (HR, 0.75; P = 0.021) subtypes derived OS benefit with ribociclib. Patients with basal-like subtype did not derive benefit from ribociclib (HR, 1.92; P = 0.137); however, patient numbers were small (n = 28).

CONCLUSIONS

The prognostic value of intrinsic subtypes for OS was confirmed in this pooled analysis of the MONALEESA trials (largest dataset in HR+/HER2- ABC). While basal-like subtype did not benefit, a consistent OS benefit was observed with ribociclib added to ET across luminal and HER2E subtypes.

Prognostic value of intrinsic subtypes in hormone-receptor-positive metastatic breast cancer: systematic review and meta-analysis

BACKGROUND

In hormone receptor-positive (HoR+) breast cancer (BC), gene expression analysis identifies luminal A (LumA), luminal B (LumB), human epidermal growth factor receptor 2 (HER2)-enriched (HER2-E), basal-like (BL) intrinsic subtypes and a normal-like group. This classification has an established prognostic value in early-stage HoR+ BC. Here, we carried out a trial-level meta-analysis to determine the prognostic ability of subtypes in metastatic BC (MBC).

MATERIALS AND METHODS

We systematically reviewed all the available prospective phase II/III trials in HoR+ MBC where subtype was assessed. The primary endpoint was progression-free survival (PFS)/time to progression (TTP) of the LumA subtype compared to non-LumA. Secondary endpoints were PFS/TTP of each individual subtype, according to treatment, menopausal and HER2 status and overall survival (OS). The random-effect model was applied, and heterogeneity assessed through Cochran's Q and I². Threshold for significance was set at P < 0.05. The study was registered in PROSPERO (ID: CRD42021255769).

RESULTS

Seven studies were included (2536 patients). Non-LumA represented 55.2% and was associated with worse PFS/TTP than LumA [hazard ratio (HR) 1.77, P < 0.001, I² = 61%], independently of clinical HER2 status [P_{subgroup difference} (P_sub) = 0.16], systemic treatment (P_sub = 0.96) and menopausal status (P_sub = 0.12). Non-LumA tumors also showed worse OS (HR 2.00, P < 0.001, I² = 65%), with significantly different outcomes for LumB (PFS/TTP HR 1.46; OS HR 1.41), HER2-E (PFS/TTP HR 2.39; OS HR 2.08) and BL (PFS/TTP HR 2.67; OS HR 3.26), separately (PFS/TTP P_sub = 0.01; OS P_sub = 0.005). Sensitivity analyses supported the main result. No publication bias was observed.

CONCLUSIONS

In HoR+ MBC, non-LumA disease is associated with poorer PFS/TTP and OS than LumA, independently of HER2, treatment and menopausal status. Future trials in HoR+ MBC should consider this clinically relevant biological classification.

PD-L1 blockade in combination with carboplatin as immune induction in metastatic lobular breast cancer: the GELATO trial

Invasive lobular breast cancer (ILC) is the second most common histological breast cancer subtype, but ILC-specific trials are lacking. Translational research revealed an immune-related ILC subset, and in mouse ILC models, synergy between immune checkpoint blockade and platinum was observed. In the phase II GELATO trial ( NCT03147040 ), patients with metastatic ILC were treated with weekly carboplatin (area under the curve 1.5 mg ml-1 min-1) as immune induction for 12 weeks and atezolizumab (PD-L1 blockade; triweekly) from the third week until progression. Four of 23 evaluable patients had a partial response (17%), and 2 had stable disease, resulting in a clinical benefit rate of 26%. From these six patients, four had triple-negative ILC (TN-ILC). We observed higher CD8+ T cell infiltration, immune checkpoint expression and exhausted T cells after treatment. With this GELATO trial, we show that ILC-specific clinical trials are feasible and demonstrate promising antitumor activity of atezolizumab with carboplatin, particularly for TN-ILC, and provide insights for the design of highly needed ILC-specific trials.

Serum immuno-oncology markers carry independent prognostic information in patients with newly diagnosed metastatic breast cancer, from a prospective observational study

BACKGROUND

Metastatic breast cancer (MBC) is a challenging disease, and despite new therapies, prognosis is still poor for a majority of patients. There is a clinical need for improved prognostication where immuno-oncology markers can provide important information. The aim of this study was to evaluate serum immuno-oncology markers in MBC patients and their respective relevance for prediction of survival.

PATIENTS AND METHODS

We investigated a broad panel of 92 immuno-oncology proteins in serum from 136 MBC patients included in a prospective observational study (NCT01322893) with long-term follow-up. Serum samples were collected before start of systemic therapy and analyzed using multiplex proximity extension assay (Olink Target 96 Immuno-Oncology panel). Multiple machine learning techniques were used to identify serum markers with highest importance for prediction of overall and progression-free survival (OS and PFS), and associations to survival were further evaluated using Cox regression analyses. False discovery rate was then used to adjust for multiple comparisons.

RESULTS

Using random forest and random survival forest analyses, we identified the top nine and ten variables of highest predictive importance for OS and PFS, respectively. Cox regression analyses revealed significant associations (P < 0.005) of higher serum levels of IL-8, IL-10 and CAIX with worse OS in multivariable analyses, adjusted for established clinical prognostic factors including circulating tumor cells (CTCs). Similarly, high serum levels of IL-8, IL-10, ADA and CASP8 significantly associated with worse PFS. Interestingly, high serum levels of FasL significantly associated with improved OS and PFS. In addition, CSF-1, IL-6, MUC16, TFNSFR4 and CD244 showed suggestive evidence (P < 0.05) for an association to survival in multivariable analyses. After correction for multiple comparisons, IL-8 still showed strong evidence for correlation to survival.

CONCLUSION

To conclude, we found six serum immuno-oncology markers that were significantly associated with OS and/or PFS in MBC patients, independently of other established prognostic factors including CTCs. Furthermore, an additional five serum immuno-oncology markers provided suggestive evidence for an independent association to survival. These findings highlight the relevance of immuno-oncology serum markers in MBC patients and support their usefulness for improved prognostication. Trial registration Clinical Trials (NCT01322893), registered March 25, 2011.

Circulating tumor DNA reveals complex biological features with clinical relevance in metastatic breast cancer

Liquid biopsy has proven valuable in identifying individual genetic alterations; however, the ability of plasma ctDNA to capture complex tumor phenotypes with clinical value is unknown. To address this question, we have performed 0.5X shallow whole-genome sequencing in plasma from 459 patients with metastatic breast cancer, including 245 patients treated with endocrine therapy and a CDK4/6 inhibitor (ET + CDK4/6i) from 2 independent cohorts. We demonstrate that machine learning multi-gene signatures, obtained from ctDNA, identify complex biological features, including measures of tumor proliferation and estrogen receptor signaling, similar to what is accomplished using direct tumor tissue DNA or RNA profiling. More importantly, 4 DNA-based subtypes, and a ctDNA-based genomic signature tracking retinoblastoma loss-of-heterozygosity, are significantly associated with poor response and survival outcome following ET + CDK4/6i, independently of plasma tumor fraction. Our approach opens opportunities for the discovery of additional multi-feature genomic predictors coming from ctDNA in breast cancer and other cancer-types.

Multiomics in primary and metastatic breast tumors from the AURORA US network finds microenvironment and epigenetic drivers of metastasis

The AURORA US Metastasis Project was established with the goal to identify molecular features associated with metastasis. We assayed 55 females with metastatic breast cancer (51 primary cancers and 102 metastases) by RNA sequencing, tumor/germline DNA exome and low-pass whole-genome sequencing and global DNA methylation microarrays. Expression subtype changes were observed in ~30% of samples and were coincident with DNA clonality shifts, especially involving HER2. Downregulation of estrogen receptor (ER)-mediated cell-cell adhesion genes through DNA methylation mechanisms was observed in metastases. Microenvironment differences varied according to tumor subtype; the ER+/luminal subtype had lower fibroblast and endothelial content, while triple-negative breast cancer/basal metastases showed a decrease in B and T cells. In 17% of metastases, DNA hypermethylation and/or focal deletions were identified near HLA-A and were associated with reduced expression and lower immune cell infiltrates, especially in brain and liver metastases. These findings could have implications for treating individuals with metastatic breast cancer with immune- and HER2-targeting therapies.

High PANX1 Expression Leads to Neutrophil Recruitment and the Formation of a High Adenosine Immunosuppressive Tumor Microenvironment in Basal-like Breast Cancer

Background: A high adenosine level is an important characteristic of the tumor microenvironment (TME) in breast cancer. Pannexin 1 (PANX1) can release intracellular ATP to the extracellular space and elevate extracellular ATP (exATP) levels under physiological conditions. Methods: We performed public database bioinformatics analysis, surgical specimen histological validation, RNA sequencing, and exATP/extracellular adenosine (exADO) assays to reveal the role of PANX1 in regulating the immune microenvironment of basal-like breast cancer. Results: Our results revealed that PANX1 acted as a poor prognostic factor for breast cancer and had high expression in basal-like breast cancer. PANX1 expression was positively correlated with exATP and exADO levels in basal-like breast cancer TME. PANX1 expression was also positively correlated with tumor-associated neutrophil (TAN) infiltration in breast cancer TME and TANs highly expressed ENTPD1 (CD39)/NT5E (CD73). Conclusions: This study suggests that high PANX1 expression is associated with high TAN infiltration and adenosine production to induce local immunosuppression in basal-like breast cancer TME.

Breast Cancer Heterogeneity

Breast tumor heterogeneity is a major challenge in the clinical management of breast cancer patients. Both inter-tumor and intra-tumor heterogeneity imply that each breast cancer (BC) could have different prognosis and would benefit from specific therapy. Breast cancer is a dynamic entity, changing during tumor progression and metastatization and this poses fundamental issues to the feasibility of a personalized medicine approach. The most effective therapeutic strategy for patients with recurrent disease should be assessed evaluating biopsies obtained from metastatic sites. Furthermore, the tumor progression and the treatment response should be strictly followed and radiogenomics and liquid biopsy might be valuable tools to assess BC heterogeneity in a non-invasive way.