Discordance in 21-gene recurrence scores between paired breast cancer samples is inversely associated with patient age

Extra-nuclear and cytoplasmic steroid receptor signalling in hormone dependent cancers

Steroid hormone receptors are key mediators in the execution of hormone action through a combination of genomic and non-genomic action. Since their isolation and characterisation in the early 20th Century much of our understanding of the biological actions of steroid hormones are underpinned by their activated receptor activity. Over the past two decades there has been an acceleration of more omics-based research which has resulted in a major uptick in our comprehension of genomic steroid action. However, it is well understood that steroid hormones can induce very rapid signalling events in tandem with their genomic actions wherein they exert their influence through alterations in gene expression. Thus the totality of genomic and non-genomic steroid action occurs in a simultaneous and reciprocal manner and a greater appreciation of whole cell action is required to fully evaluate steroid hormone activity in vivo. In this mini-review we outline the most recent developments in non-genomic steroid action and cytoplasmic steroid hormone receptor biology in endocrine-related cancers with a focus on the 3-keto steroid receptors, in particular the androgen receptor.

Mechanics of Small-Scale Spherical Inclusions Using Nonlocal Poroelasticity Integrated with Light Gradient Boosting Machine

Detecting inclusions in materials at small scales is of high importance to ensure the quality, structural integrity and performance efficiency of microelectromechanical machines and products. Ultrasound waves are commonly used as a non-destructive method to find inclusions or structural flaws in a material. Mathematical continuum models can be used to enable ultrasound techniques to provide quantitative information about the change in the mechanical properties due to the presence of inclusions. In this paper, a nonlocal size-dependent poroelasticity model integrated with machine learning is developed for the description of the mechanical behaviour of spherical inclusions under uniform radial compression. The scale effects on fluid pressure and radial displacement are captured using Eringen's theory of nonlocality. The conservation of mass law is utilised for both the solid matrix and fluid content of the poroelastic material to derive the storage equation. The governing differential equations are derived by decoupling the equilibrium equation and effective stress-strain relations in the spherical coordinate system. An accurate numerical solution is obtained using the Galerkin discretisation technique and a precise integration method. A Dormand-Prince solution is also developed for comparison purposes. A light gradient boosting machine learning model in conjunction with the nonlocal model is used to extract the pattern of changes in the mechanical response of the poroelastic inclusion. The optimised hyperparameters are calculated by a grid search cross validation. The modelling estimation power is enhanced by considering nonlocal effects and applying machine learning processes, facilitating the detection of ultrasmall inclusions within a poroelastic medium at micro/nanoscales.

Biomarkers in Cancer Detection, Diagnosis, and Prognosis

Biomarkers are vital in healthcare as they provide valuable insights into disease diagnosis, prognosis, treatment response, and personalized medicine. They serve as objective indicators, enabling early detection and intervention, leading to improved patient outcomes and reduced costs. Biomarkers also guide treatment decisions by predicting disease outcomes and facilitating individualized treatment plans. They play a role in monitoring disease progression, adjusting treatments, and detecting early signs of recurrence. Furthermore, biomarkers enhance drug development and clinical trials by identifying suitable patients and accelerating the approval process. In this review paper, we described a variety of biomarkers applicable for cancer detection and diagnosis, such as imaging-based diagnosis (CT, SPECT, MRI, and PET), blood-based biomarkers (proteins, genes, mRNA, and peptides), cell imaging-based diagnosis (needle biopsy and CTC), tissue imaging-based diagnosis (IHC), and genetic-based biomarkers (RNAseq, scRNAseq, and spatial transcriptomics).

Genomic Characterization of Aggressive Breast Cancer in Younger Women

PURPOSE

Although breast cancer (BC) risk increases with age, BC in younger women is more aggressive with higher mortality compared with older women. We characterize the genomic landscape of BCs in younger women.

METHODS

Clinicopathologic, molecular, and genomic differences across age groups (< 40 years, 40-60 years, > 60 years) in female BC patients were investigated in two large cohorts [AACR-GENIE8.1 (n = 11,594) and METABRIC (n = 2509)]. Cox-proportional regression analyzed the prognostic impact of age groups for disease-specific survival (DSS) and recurrence-free survival (RFS) in METABRIC and progression-free survival (PFS) in GENIE cohorts. Chi-squared test was used to assess statistical associations between genomic alterations and age groups.

RESULTS

Survival analysis showed that women < 40 years had shorter DSS [hazard ratio (HR): 1.52, p = 0.005], RFS (HR: 1.4, p = 0.006), and PFS (HR: 1.82, p = 0.0003) compared with women 40-60 years, and shorter RFS (HR: 1.5, p = 0.001) and PFS (HR: 2.95, p < 0.0001) compared with women > 60 years. Molecular subtypes in the METABRIC cohort showed women < 40 years were enriched with basal, and HER2+ subtypes, and less enriched with luminal A and B subtype (p < 0.0001). Characterization of genomic alterations in both cohorts demonstrated that BCs in women < 40 years were more enriched with TP53 mutations (FDR < 0.0001), BRCA1 mutations (FDR = 0.01), ERBB2 amplifications (FDR < 0.001), CDK12 amplifications (FDR < 0.001), and PPM1D amplifications (FDR < 0.001). In contrast, BCs in older women (> 60 years) were more enriched with PIK3CA, KMT2C, and CDH1 mutations (FDR < 0.0001).

CONCLUSIONS

BCs in young women are associated with shorter survival and more aggressive genomic features, including mutations in TP53 and BRCA1, and amplifications in ERBB2 and CDK12. These findings have the potential to impact clinical trial design and treatment.

Oncotype DX Recurrence Score in premenopausal women

In the past 20 years, clinicians have shifted away from relying solely on clinicopathologic indicators toward increasing use of multigene expression assays in guiding treatment decisions regarding adjuvant chemotherapy for early-stage hormone receptor (HR)-positive, HER2-negative breast cancer. Oncotype DX Recurrence Score (RS) is one of the most widely used multigene assays when considering indications for adjuvant chemotherapy, and guidelines have recently incorporated its use in women with early HR-positive HER2-negative breast cancer and up to three positive lymph nodes. While multiple retrospective and prospective clinical studies have demonstrated that most women with a low- to mid-range RS (0–25) can safely forgo chemotherapy, premenopausal women remain an important subgroup for which recommendations based on RS are ill-defined. The majority of patients included in clinical trials and retrospective analyses validating the use of RS have been postmenopausal women. In the subgroup of premenopausal women with HR-positive HER2-negative breast cancer, studies indicate that traditional clinicopathologic methods for assessing risk continue to be powerful tools when combined with RS to predict benefit from chemotherapy. This suggests that there is an element of uncaptured risk inherent to the premenopausal state that evades characterization by RS alone. This review describes the evidence that has supported the recommendation of RS in clinical guidelines, specifically focusing on data for its current use in premenopausal women. We review available data regarding the impact of the menstrual cycle on hormonally regulated gene expression, which may drive variations in the RS. Further research on the reliability and interpretation of the RS in the premenopausal subgroup is necessary and represents a gap in knowledge of how the RS should be applied in premenopausal women.

Impact of the menstrual cycle on commercial prognostic gene signatures in oestrogen receptor-positive primary breast cancer

PURPOSE

Changes occur in the expression of oestrogen-regulated and proliferation-associated genes in oestrogen receptor (ER)-positive breast tumours during the menstrual cycle. We investigated if Oncotype® DX recurrence score (RS), Prosigna® (ROR) and EndoPredict® (EP/EPclin) prognostic tests, which include some of these genes, vary according to the time in the menstrual cycle when they are measured.

METHODS

Pairs of test scores were derived from 30 ER-positive/human epidermal growth factor receptor-2-negative tumours sampled at two different points of the menstrual cycle. Menstrual cycle windows were prospectively defined as either W1 (days 1-6 and 27-35; low oestrogen and low progesterone) or W2 (days 7-26; high oestrogen and high or low progesterone).

RESULTS

The invasion module score of RS was lower (- 10.9%; p = 0.098), whereas the ER (+ 16.6%; p = 0.046) and proliferation (+ 7.3%; p = 0.13) module scores were higher in W2. PGR expression was significantly increased in W2 (+ 81.4%; p = 0.0029). Despite this, mean scores were not significantly different between W1 and W2 for any of the tests and the two measurements showed high correlation (r = 0.72-0.93). However, variability between the two measurements led to tumours being assigned to different risk categories in the following proportion of cases: RS 22.7%, ROR 27.3%, EP 13.6% and EPclin 13.6%.

CONCLUSION

There are significant changes during the menstrual cycle in the expression of some of the genes and gene module scores comprising the RS, ROR and EP/EPclin scores. These did not affect any of the prognostic scores in a systematic fashion, but there was substantial variability in paired measurements.

Steroid Ligands, the Forgotten Triggers of Nuclear Receptor Action; Implications for Acquired Resistance to Endocrine Therapy

PURPOSE

There is strong epidemiologic evidence indicating that estrogens may not be the sole steroid drivers of breast cancer. We hypothesize that abundant adrenal androgenic steroid precursors, acting via the androgen receptor (AR), promote an endocrine-resistant breast cancer phenotype.

EXPERIMENTAL DESIGN

AR was evaluated in a primary breast cancer tissue microarray (n = 844). Androstenedione (4AD) levels were evaluated in serum samples (n = 42) from hormone receptor-positive, postmenopausal breast cancer. Levels of androgens, progesterone, and estradiol were quantified using LC/MS-MS in serum from age- and grade-matched recurrent and nonrecurrent patients (n = 6) before and after aromatase inhibitor (AI) therapy (>12 months). AR and estrogen receptor (ER) signaling pathway activities were analyzed in two independent AI-treated cohorts.

RESULTS

AR protein expression was associated with favorable progression-free survival in the total population (Wilcoxon, P < 0.001). Pretherapy serum samples from breast cancer patients showed decreasing levels of 4AD with age only in the nonrecurrent group (P < 0.05). LC/MS-MS analysis of an AI-sensitive and AI-resistant cohort demonstrated the ability to detect altered levels of steroids in serum of patients before and after AI therapy. Transcriptional analysis showed an increased ratio of AR:ER signaling pathway activities in patients failing AI therapy (t test P < 0.05); furthermore, 4AD mediated gene changes associated with acquired AI resistance.

CONCLUSIONS

This study highlights the importance of examining the therapeutic consequences of the steroid microenvironment and demonstrable receptor activation using indicative gene expression signatures.

Ovarian cycle stage critically affects 21-gene recurrence scores in Mmtv-Pymt mouse mammary tumours

BACKGROUND

The Oncotype DX 21-gene Recurrence Score is predictive of adjuvant chemotherapy benefit for women with early-stage, estrogen receptor (ER)-positive, HER2-negative breast cancer. In premenopausal women, fluctuations in estrogen and progesterone during the menstrual cycle impact gene expression in hormone-responsive cancers. However, the extent to which menstrual cycling affects the Oncotype DX 21-gene signature remains unclear. Here, we investigate the impact of ovarian cycle stage on the 21-gene signature using a naturally cycling mouse model of breast cancer.

METHODS

ER-positive mammary tumours were dissected from naturally cycling Mmtv-Pymt mice at either the estrus or diestrus phase of the ovarian cycle. The Oncotype DX 21-gene signature was assessed through quantitative real time-PCR, and a 21-gene experimental recurrence score analogous to the Oncotype DX Recurrence Score was calculated.

RESULTS

Tumours collected at diestrus exhibited significant differences in expression of 6 Oncotype DX signature genes (Ki67, Ccnb1, Esr1, Erbb2, Grb7, Bag1; p ≤ 0.05) and a significant increase in 21-gene recurrence score (21.8 ± 2.4; mean ± SEM) compared to tumours dissected at estrus (15.5 ± 1.9; p = 0.03). Clustering analysis revealed a subgroup of tumours collected at diestrus characterised by increased expression of proliferation- (p < 0.001) and invasion-group (p = 0.01) genes, and increased 21-gene recurrence score (p = 0.01). No correlation between ER, PR, HER2, and KI67 protein abundance measured by Western blot and abundance of mRNA for the corresponding gene was observed, suggesting that gene expression is more susceptible to hormone-induced fluctuation compared to protein expression.

CONCLUSIONS

Ovarian cycle stage at the time of tissue collection critically affects the 21-gene signature in Mmtv-Pymt murine mammary tumours. Further studies are required to determine whether Oncotype DX Recurrence Scores in women are similarly affected by menstrual cycle stage.

Comparison of hormone-induced mRNA and protein biomarker expression changes in breast cancer cells

PURPOSE

Protein biomarkers estrogen receptor (ER), progesterone receptor (PR), and marker of proliferation (Ki67) are routinely assessed by immunohistochemistry to guide treatment decisions for breast cancer. Now, quantification of mRNA encoding these proteins is being adopted in the clinic. However, mRNA and protein biomarkers may be differentially regulated by fluctuations in estrogen and progesterone that occur across the menstrual cycle in premenopausal breast cancer patients. This study aimed to compare how estrogen and progesterone affect mRNA and protein biomarker expression in hormone-responsive breast cancer cells.

METHODS

Hormone-responsive ZR-75-1 and T-47D human breast cancer cell lines were xenografted into the mammary fat pad of BALB/c nude mice supplemented with estrogen. Progesterone or vehicle was administered prior to dissection of tumors. Protein expression of ER, PR and Ki67 was quantified by immunohistochemistry, and mRNA encoding these proteins, ESR1, PGR and KI67, respectively, was quantified by real-time PCR. mRNA expression was also quantified in breast cancer cell lines treated with estrogen and progesterone in vitro.

RESULTS

In T-47D-xenografted tumors, estrogen and progesterone treatment reduced PGR and KI67 mRNA expression, and reduced PR and Ki67 protein positivity, compared to estrogen treatment alone. In ZR-75-1 xenografted tumors, no significant differences in protein or mRNA biomarker expression were observed. In vitro, estrogen and progesterone co-treatment significantly reduced ESR1 and PGR mRNA expression in both T-47D and ZR-75-1 cell lines.

CONCLUSIONS

Estrogen and progesterone similarly affect mRNA and protein biomarker expression in hormone-responsive breast cancer xenografts. Further research is needed to investigate concordance between protein and mRNA biomarkers in premenopausal breast cancer.

Clinical utility of the 21-gene assay in predicting response to neoadjuvant endocrine therapy in breast cancer: A systematic review and meta-analysis

INTRODUCTION

OncotypeDX© Recurrence Score (RS) is a multigene panel used to aid therapeutic decision making in early-stage, estrogen receptor positive (ER+)/human epidermal growth factor receptor-2 negative (HER2-) breast cancer.

AIM

To compare responses to neoadjuvant endocrine therapy (NET) in patients with ER+/HER2-breast cancer following substratification by RS testing.

METHODS

This systematic review was performed in accordance to the PRISMA guidelines. Studies evaluating pathological complete response (pCR), partial response (PR), and successful conversion to breast conservation surgery (BCS) rates following NET guided by RS were retrieved. Dichotomous outcomes were reported as odds ratios (ORs) with 95% confidence intervals (CIs) following estimation by Mantel-Haenszel method.

RESULTS

Eight prospective studies involving 691 patients were included. The mean age was 62.6 years (range 25-85) and the mean RS was 14.5 (range 0-68). Patients with RS < 25 (OR: 4.60, 95% CI: 2.53-8.37, P < 0.001) and RS < 30 (OR: 3.40, 95% CI: 1.96-5.91, P < 0.001) were more likely to achieve PR than their counterparts. NET prescription failed to increase BCS conversion rates for patients with RS < 18 (OR: 0.23, 95% CI: 0.04-1.47, P = 0.120) and RS > 30 (OR: 1.27, 95% CI: 0.64-2.49, P = 0.490) respectively. Only 22 patients achieved pCR (2.8%) and RS group failed to predict pCR following NET (P = 0.850).

CONCLUSION

Estimations from this analysis indicate that those with low-intermediate RS on core biopsy are four times more likely to respond to NET than those with high-risk RS. Performing RS testing on diagnostic biopsy may be useful in guiding NET prescription.

Challenges in Adjuvant Therapy for Premenopausal Women Diagnosed With Luminal Breast Cancers

More than 90% of women with newly diagnosed breast cancer present with stage I to III disease and, with optimal multidisciplinary therapy, are likely to survive their disease. Of these patients, 70% are hormone receptor-positive and candidates for adjuvant endocrine therapy. The adoption of cumulatively better adjuvant treatments contributed to improved outcomes in patients with hormone receptor-positive, early-stage breast cancer. Premenopausal women with hormone receptor-positive breast cancer often present with complex disease and have inferior survival outcomes compared with their postmenopausal counterparts. Risk stratification strategies, including classic clinicopathologic features and newer gene expression assays, can assist in treatment decisions, including adjuvant chemotherapy use and type or duration of endocrine therapy. Gene expression assays may help identify patients who can safely forgo chemotherapy, although to a lesser extent among premenopausal patients, in whom they may play a role only in node-negative disease. Patients at lower risk of recurrence can be adequately treated with tamoxifen alone, whereas higher-risk patients benefit from ovarian function suppression with tamoxifen or an aromatase inhibitor. The role of adding newer therapies such as CDK4/6 inhibitors to adjuvant endocrine therapy is not yet clear. Breast cancer treatments are associated with several side effects, with major impact on patients' quality of life and treatment adherence, particularly in premenopausal women for whom these side effects may be more prominent as the result of the abrupt decrease in estrogen concentrations. Personalized management of treatment side effects, addressing patients' concerns, and health promotion should be an integral part of the care of premenopausal women diagnosed with luminal breast cancers.