Updates in endocrine therapy for metastatic breast cancer

Calcification-associated molecular traits and therapeutic strategies in hormone receptor-positive HER2-negative breast cancer

OBJECTIVE

Mammographic calcifications are a common feature of breast cancer, but their molecular characteristics and treatment implications in hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer remain unclear.

METHODS

We retrospectively collected mammography records of an HR+/HER2- breast cancer cohort (n = 316) with matched clinicopathological, genomic, transcriptomic, and metabolomic data. On the basis of mammographic images, we grouped tumors by calcification status into calcification-negative tumors, tumors with probably benign calcifications, tumors with calcification of low-moderate suspicion for maligancy and tumors with calcification of high suspicion for maligancy. We then explored the molecular characteristics associated with each calcification status across multiple dimensions.

RESULTS

Among the different statuses, tumors with probably benign calcifications exhibited elevated hormone receptor immunohistochemical staining scores, estrogen receptor (ER) pathway activation, lipid metabolism, and sensitivity to endocrine therapy. Tumors with calcifications of high suspicion for malignancy had relatively larger tumor sizes, elevated lymph node metastasis incidence, Ki-67 staining scores, genomic instability, cell cycle pathway activation, and may benefit from cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors.

CONCLUSIONS

Our research established links between tumor calcifications and molecular features, thus proposing potential precision treatment strategies for HR+/HER2- breast cancer.

Development of an obesity-related multi-gene prognostic model incorporating clinical characteristics in luminal breast cancer

Despite adjuvant chemotherapy and endocrine therapy in luminal breast cancer (LBC), relapses are common. Addressing this, we aim to develop a prognostic model to refine adjuvant therapy strategies, particularly for patients at high recurrence risk. Notably, obesity profoundly affects the tumor microenvironment (TME) of LBC. However, it is unclear whether obesity-related biological features can effectively screen high-risk patients. Utilizing weighted gene coexpression network analysis (WGCNA) on RNA sequencing (RNAseq) data, we identified seven obese LBC genes (OLGs) closely associated with patient prognosis. Subsequently, we developed a luminal obesity-gene clinical prognostic index (LOG-CPI), combining a 7-gene signature, TNM staging, and age. Its predictive efficacy was confirmed across validation datasets and a clinical cohort (5-year accuracy = 0.828, 0.760, 0.751, and 0.792, respectively). LOG-CPI emerges as a promising predictor for clinical prognosis and treatment response, helping distinguish molecular and immunological features in LBC patients and guiding clinical practice by identifying varying prognoses.

Bibliometric analysis and visualization of endocrine therapy for breast cancer research in the last two decade

Background

Breast cancer endocrine therapy research has become a crucial domain in oncology since hormone receptor-positive breast cancers have been increasingly recognized, and targeted therapeutic interventions have been advancing over the past few years. This bibliometric analysis attempts to shed light on the trends, dynamics, and knowledge hotspots that have shaped the landscape of breast cancer endocrine therapy research between 2003 and 2022.

Methods

In this study, we comprehensively reviewed the scientific literature spanning the above-mentioned period, which included publications accessible through the database of the Web of Science (WOS) and the National Center for Biotechnology Information (NCBI). Next, a systematic and data-driven analysis supported by sophisticated software tools was conducted, such that the core themes, prolific authors, influential journals, prominent countries, and critical citation patterns in the relevant research field can be clarified.

Results

A continuous and substantial expansion of breast cancer endocrine therapy research was revealed over the evaluated period. A total of 1,317 scholarly articles were examined. The results of the analysis suggested that research on endocrine therapy for breast cancer has laid a solid basis for the treatment of hormone receptor-positive breast cancer. From a geographical perspective, the US, the UK, and China emerged as the most active contributors, illustrating the global impact of this study. Furthermore, our analysis delineated prominent research topics that have dominated the discourse in the past two decades, including drug therapy, therapeutic efficacy, molecular biomarkers, and hormonal receptor interactions.

Conclusion

This comprehensive bibliometric analysis provides a panoramic view of the ever-evolving landscape of breast cancer endocrine therapy research. The findings highlight the trajectory of past developments while signifying an avenue of vast opportunities for future investigations and therapeutic advancements. As the field continues to burgeon, this analysis will provide valuable guidance for to researchers toward pertinent knowledge hotspots and emerging trends, which can expedite the discoveries in the realm of breast cancer endocrine therapy.

Making inroads to precision medicine for the treatment of autoimmune diseases: Harnessing genomic studies to better diagnose and treat complex disorders

Precision Medicine is an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle. Autoimmune diseases are those in which the body's natural defense system loses discriminating power between its own cells and foreign cells, causing the body to mistakenly attack healthy tissues. These conditions are very heterogeneous in their presentation and therefore difficult to diagnose and treat. Achieving precision medicine in autoimmune diseases has been challenging due to the complex etiologies of these conditions, involving an interplay between genetic, epigenetic, and environmental factors. However, recent technological and computational advances in molecular profiling have helped identify patient subtypes and molecular pathways which can be used to improve diagnostics and therapeutics. This review discusses the current understanding of the disease mechanisms, heterogeneity, and pathogenic autoantigens in autoimmune diseases gained from genomic and transcriptomic studies and highlights how these findings can be applied to better understand disease heterogeneity in the context of disease diagnostics and therapeutics.

Combining Immune-Related Genes For Delineating the Extracellular Matrix and Predicting Hormone Therapy and Neoadjuvant Chemotherapy Benefits In Breast Cancer

Breast cancer (BC) is the most prevalent cancer in women worldwide. A systematic approach to BC treatment, comprising adjuvant and neoadjuvant chemotherapy (NAC), as well as hormone therapy, forms the foundation of the disease’s therapeutic strategy. The extracellular matrix (ECM) is a dynamic network that exerts a robust biological effect on the tumor microenvironment (TME), and it is highly regulated by several immunological components, such as chemokines and cytokines. It has been established that the ECM promotes the development of an immunosuppressive TME. Therefore, while analyzing the ECM of BC, immune-related genes must be considered. In this study, we used bioinformatic approaches to identify the most valuable ECM-related immune genes. We used weighted gene co-expression network analysis to identify the immune-related genes that potentially regulate the ECM and then combined them with the original ECM-related gene set for further analysis. Least absolute shrinkage and selection operator (LASSO) regression and SurvivalRandomForest were used to narrow our ECM-related gene list and establish an ECM index (ECMI) to better delineate the ECM signature. We stratified BC patients into ECMI high and low groups and evaluated their clinical, biological, and genomic characteristics. We found that the ECMI is highly correlated with long-term BC survival. In terms of the biological process, this index is positively associated with the cell cycle, DNA damage repair, and homologous recombination but negatively with processes involved in angiogenesis and epithelial–mesenchymal transition. Furthermore, the tumor mutational burden, copy number variation, and DNA methylation levels were found to be related to the ECMI. In the Metabric cohort, we demonstrated that hormone therapy is more effective in patients with a low ECMI. Additionally, differentially expressed genes from the ECM-related gene list were extracted from patients with a pathologic complete response (pCR) to NAC and with residual disease (RD) to construct a neural network model for predicting the chance of achieving pCR individually. Finally, we performed qRT-PCR to validate our findings and demonstrate the important role of the gene OGN in predicting the pCR rate. In conclusion, delineation of the ECM signature with immune-related genes is anticipated to aid in the prediction of the prognosis of patients with BC and the benefits of hormone therapy and NAC in BC patients.

Soluble POSTN is a novel biomarker complementing CA153 and CEA for breast cancer diagnosis and metastasis prediction

BACKGROUND

Breast cancer (BCa) is the leading cause of cancer deaths among women. Reliable biomarkers for early diagnosis and metastasis prediction are essential to improve the prognosis of BCa. This study aimed to evaluate serum periostin (POSTN) as a novel biomarker complementing CA153 (carbohydrate antigen 153) and CEA (carcinoembryonic antigen) for BCa diagnosis and metastasis prediction.

METHODS

To assess the potential of soluble POSTN as a circulating biomarker, 242 participants, including 173 patients with different stages of BCa and 69 healthy individuals, were enrolled in this study. Soluble POSTN, together with CA153 and CEA, were determined in serum by enzyme linked immunosorbent assay (ELISA) or electrochemiluminescence immunoassays.

RESULTS

Serum POSTN levels in locoregional BCa patients were significantly higher than that in healthy controls. Receiver operating curve (ROC) analysis revealed that, to distinguish health controls from locoregional BCa, POSTN was observed with the highest AUC (area under curve) (AUC_POSTN = 0.72 [0.65 - 0.79], AUC_CA153 = 0.57 [0.49 - 0.64], AUC_CEA = 0.62 [0.55 - 0.69]), and both CA153 and CEA were observed with significantly improved AUCs by combination with POSTN (AUC_{POSTN + CA153} = 0.74 [0.67 - 0.80], P < 0.001; AUC_{POSTN + CEA} = 0.77 [0.70 - 0.82], P < 0.001). Moreover, the performances of the POSTN were comparable with that of CA153 in predicting distant metastasis of BCa (AUC_POSTN = 0.78 [0.71 - 0.84], AUC_CA153 = 0.82 [0.76 - 0.88]). Kaplan-Meier analysis indicated that elevated serum POSTN was associated with poor overall survival and progression-free survival.

CONCLUSIONS

This study suggested that soluble POSTN is a promising potential biomarker for diagnosis and metastasis prediction of BCa.

Circulating tumor DNA profile and its clinical significance in patients with hormone receptor-positive and HER2-negative mBC

BACKGROUND

After early-line (first- and second-line) endocrine therapy, hormone-receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancers (mBCs) become resistant to endocrine therapy. Genetic alterations may underlie resistance to endocrine therapies. This study aims to investigate the circulating tumor DNA (ctDNA) alterations and the clinical implication in hormone-receptor-positive, HER2-negative metastatic breast cancer patients with multiline endocrine therapy failure.

METHODS

This registered study (NCT05079074, ClinicalTrials.gov) enrolled 104 patients with hormone-receptor-positive, HER2-negative metastatic breast cancer who progressed after the early-line endocrine therapy. ctDNA alterations were analyzed by next generation sequencing (NGS). ctDNA alterations were ranked and clustered by using R 'ComplexHeatmap' and 'hclust' function. ctDNA-guided therapy was administrated. Progression-free survival (PFS) was assessed COX regression analysis, and Kaplan-Meier curves were plotted.

FINDINGS

The top ctDNA altered genes were TP53 (39%), PIK3CA (38%), BRCA1/2 (13%), ESR1 (12%), FGFR (11%), ERBB2 (11%), and GATA3 (9%). Among these genes, TP53, PIK3CA helix domain mutation (PIK3CA-HD), FGFR, ESR1 and GATA3 were related to endocrine therapy resistance. The genetic landscapes changed and tumor mutation burden increased in both TP53-altered and PIK3CA-altered patients. Both BRCA1/2 and ERBB2 alterations correlated with TP53 alterations (P=0.02 and P=0.04, respectively). However, while 93% BRCA1/2 alterations concentrated in PIK3CA-wildtype patients, 82% ERBB2 alterations concentrated in PIK3CA-altered patients. Kaplan-Meier curves showed that patients who received druggable ctDNA alteration-guided treatment (DDAT) had significantly longer PFS than those who received physician-chosen therapy, with median PFS of 6.1 months versus 4.6 months (hazard ratio = 0.53, 95% CI: 0.34-0.85, Logrank P = 0.006).

CONCLUSION

Multiple genetic alterations were important reasons for the failure of endocrine therapy for HR-positive and HER2-negative mBC. Targeting these genes might restore the treatment sensitivity and benefit survival.