Quantitative Biomarkers, Genomic Assays, and Demographics Associated with Breast-Conserving Surgery Following Neoadjuvant Therapy in Early-Stage, Hormone Receptor-Positive, HER-Negative Breast Cancer.

BACKGROUND: Given increased neoadjuvant therapy use in early-stage, hormone receptor (HR)-positive/HER2-negative breast cancer, we sought to quantify likelihood of breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NACT) or endocrine therapy (NET) as a function of ER%/PR%/Ki-67%, 21-gene recurrence scores (RS), or 70-gene risk groups. METHODS: We analyzed the 2010-2020 National Cancer Database. Surgery was categorized as "mastectomy/BCS." Logistic regression was performed. Adjusted odds ratios (AOR) were per 10-unit increase in ER%/PR%/Ki-67%. RESULTS: Overall, 42.3% underwent BCS after NACT, whereas 64.0% did after NET. Increasing ER% (AOR = 0.96, 95% confidence interval [CI] 0.94-0.97) or PR% (AOR=0.98, 95% CI 0.96-0.99) was associated with lower odds of BCS after NACT. Increasing Ki-67% was associated with greater odds of BCS (AOR = 1.07, 95% CI 1.04-1.10). Breast-conserving surgery rates increased by ~20 percentage points, with Ki-67% ≥15 or RS >20. Patients with a low (43.0%, AOR = 0.50, 95% CI 0.29-0.88) or intermediate (46.4%, AOR = 0.58, 95% CI 0.41-0.81) RS were less likely than patients with a high RS (65.0%) to undergo BCS after NACT. Increasing ER% was associated with higher odds of BCS after NET (AOR = 1.09, 95% CI 1.01-1.17). Breast-conserving surgery rates increased by ~20 percentage points between ER <50% and >80%. In both cohorts, the odds of BCS were similar between 70-gene low-risk and high-risk groups. Asian or uninsured patients had lower odds of BCS. CONCLUSIONS: Neoadjuvant chemotherapy is unlikely to downstage tumors with a low-intermediate RS, higher ER%/PR%, or lower Ki-67%. Breast-conserving surgery after NET was most dependent on ER%. Findings could facilitate treatment decision-making based on tumor biology and racial/socioeconomic disparities and improve patient counseling on the likelihood of successful BCS.

Navigating the complexity of PI3K/AKT pathway in HER-2 negative breast cancer: biomarkers and beyond.

The results of the SOLAR-1 and CAPItello-291, highlight the benefit of the ɑ-selective phosphoinositide 3-Kinase Pathway inhibitor (PI3Ki) alpelisib and the AKT inhibitor (AKTi) capivasertib in patients with hormone receptor-positive (HR+)/Human Epidermal Growth Factor Receptor 2 (HER2)- negative metastatic breast cancer (mBC) that have PIK3CA/AKT1/PTEN tumour alterations. Although effective, these drugs are associated with significant toxicities, which often limit their use, particularly in frail patients. Following the recent incorporation of these agents into clinical practice, and with many others currently in development, significant challenges have emerged, particularly those regarding biomarkers for patient selection. This review will discuss biomarkers of response and their resistance to PI3K/AKT inhibitors (PI3K/AKTis) in HR+/HER- BC in early and advanced settings to ascertain which populations will most benefit from these drugs. Of the biomarkers that were analysed, such as PIK3CA, AKT, PTEN mutations, insulin levels, 18 F-FDG-PET/TC, only the PIK3CA-mutations (PIK3CA-mut) and the AKT pathway alterations seem to have a predictive value for treatments with alpelisib and capivasertib. However, due to the retrospective and exploratory nature of the study, the data did not provide conclusive results. In addition, the different methods used to detect PIK3CA/AKT1/PTEN alterations underline the fact that the optimal diagnostic companion has yet to be established. We have summarised the clinical data on the approved and discontinued agents targeting this pathway and have assessed the drugs development, successes, and failures. Finally, because of tumour heterogeneity, we emphasise the importance of reassessing the mutational status of PI3KCA in both metastatic tissue and blood at the time of disease progression to better tailor treatment for patients.

Predictive and prognostic biomarkers in urological tumours.

Advancements in cutting-edge molecular profiling techniques, such as next-generation sequencing and bioinformatic analytic tools, have allowed researchers to examine tumour biology in detail and stratify patients based on factors linked with clinical outcome and response to therapy. This manuscript highlights the most relevant prognostic and predictive biomarkers in kidney, bladder, prostate and testicular cancers with recognised impact in clinical practice. In bladder and prostate cancer, new genetic acquisitions concerning the biology of tumours have modified the therapeutic scenario and led to the approval of target directed therapies, increasing the quality of patient care. Thus, it has become of paramount importance to choose adequate molecular tests, i.e., FGFR screening for urothelial cancer and BRCA1-2 alterations for prostate cancer, to guide the treatment plan for patients. While no tissue or blood-based biomarkers are currently used in routine clinical practice for renal cell carcinoma and testicular cancers, the field is quickly expanding. In kidney tumours, gene expression signatures might be the key to identify patients who will respond better to immunotherapy or anti-angiogenic drugs. In testicular germ cell tumours, the use of microRNA has outperformed conventional serum biomarkers in the diagnosis of primary tumours, prediction of chemoresistance, follow-up monitoring, and relapse prediction.

Advanced Technologies for Potency Assay Measurement.

Crucial for their application, cell products need to be well-characterized in the cell manufacturing facilities and conform to regulatory approval criteria before infusion into the patients. Mesenchymal Stromal Cells (MSCs) are the leading cell therapy candidate in clinical trials worldwide. Early phase clinical trials have demonstrated that MSCs display an excellent safety profile and are well tolerated. However, MSCs have also exhibited contradictory efficacy in later-phase clinical trials with reasons for this discrepancy including poorly understood mechanism of MSC therapeutic action. With likelihood that a number of attributes are involved in MSC derived clinical benefit, an assay that measures a single quality of may not adequately reflect potency, thus a combination of bioassays and analytical methods, collectively called "assay matrix" are favoured for defining the potency of MSC more adequately. This chapter highlights advanced technologies and targets that can achieve quantitative measurement for a range of MSC attributes, including immunological, genomic, secretome, phosphorylation, morphological, biomaterial, angiogenic and metabolic assays.

Molecular Profiling in Early ER + Breast Cancer to Aid Systemic Therapy Decisions.

PURPOSE OF REVIEW: Clinical decisions for (neo)adjuvant treatment in early breast cancer (eBC) have been based mostly on clinical factors over the last decades. We have reviewed development and validation of such assays in the HR + /HER2 eBC and discuss possible future directions in this field. RECENT FINDINGS: Increasing knowledge about the biology of hormone-sensitive eBC, based on the precise and reproducible multigene expression analysis, has led to a significant change in the treatment pathways and reduction of overtreatment in particular by chemotherapy in HR + /HER2 eBC with up to 3 positive lymph nodes based on results from several retrospective-prospective trials used several genomic assays and in particular prospective trials (TAILORx, RxPonder, MINDACT, and ADAPT used OncotypeDX® and Mammaprint®). Precise evaluation of tumor biology together with endocrine responsiveness assessment appears as promising tools for individualized treatment decisions together with clinical factors and menopausal status in early hormone-sensitive/HER2-negative breast cancer.

Extended Adjuvant Endocrine Treatment in Luminal Breast Cancers in the Era of Genomic Tests.

In patients with early-stage endocrine receptor-positive (ER+) breast cancer (BC), adjuvant endocrine therapy (ET) for 5 years is the standard of care. However, for some patients, the risk of recurrence remain high for up to 15 years after diagnosis and extended ET beyond 5 years may be a reasonable option. Nevertheless, this strategy significantly increases the occurrence of side effects. Here we summarize the available evidence from randomized clinical trials on the efficacy and safety profile of extended ET and discuss available clinical and genomic tools helpful to select eligible patients in daily clinical practice.

Precision Medicine in Breast Cancer: Do MRI Biomarkers Identify Patients Who Truly Benefit from the Oncotype DX Recurrence Score® Test?

The aim of this study was to combine breast MRI-derived biomarkers with clinical-pathological parameters to identify patients who truly need an Oncotype DX Breast Recurrence Score® (ODXRS) genomic assay, currently used to predict the benefit of adjuvant chemotherapy in ER-positive/HER2-negative early breast cancer, with the ultimate goal of customizing therapeutic decisions while reducing healthcare costs. Patients who underwent a preoperative multiparametric MRI of the breast and ODXRS tumor profiling were retrospectively included in this study. Imaging sets were evaluated independently by two breast radiologists and classified according to the 2013 American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) lexicon. In a second step of the study, a combined oncologic and radiologic assessment based on clinical-pathological and radiological data was performed, in order to identify patients who may need adjuvant chemotherapy. Results were correlated with risk levels expressed by ODXRS, using the decision made on the basis of the ODXRS test as a gold standard. The χ2 test was used to evaluate associations between categorical variables, and significant ones were further investigated using logistic regression analyses. A total of 58 luminal-like, early-stage breast cancers were included. A positive correlation was found between ODXRS and tumor size (p = 0.003), staging (p = 0.001) and grading (p = 0.005), and between BI-RADS categories and ODXRS (p < 0.05 for both readers), the latter being confirmed at multivariate regression analysis. Moreover, BI-RADS categories proved to be positive predictors of the therapeutic decision taken after performing an ODXRS assay. A statistically significant association was also found between the therapeutic decision based on the ODXRS and the results of combined onco-radiologic assessment (p < 0.001). Our study suggests that there is a correlation between BI-RADS categories at MRI and ODXRS and that a combined onco-radiological assessment may predict the decision made on the basis of the results of ODXRS genomic test.

The Prognostic and Predictive Value of Genomic Assays in Guiding Adjuvant Breast Radiation Therapy.

Many patients with non-metastatic breast cancer benefit from adjuvant radiation therapy after lumpectomy or mastectomy on the basis of many randomized trials. However, there are many patients that have such low risks of recurrence after surgery that de-intensification of therapy by either reducing the treatment volume or omitting radiation altogether may be appropriate options. On the other hand, dose intensification may be necessary for more aggressive breast cancers. Until recently, these treatment decisions were based solely on clinicopathologic factors. Here, we review the current literature on the role of genomic assays as prognostic and/or predictive biomarkers to help guide adjuvant radiation therapy decision-making.

The use of genomic assays reduces rates of chemotherapy: a single-institution experience.

INTRODUCTION: The National Institute for Clinical Excellence recommends the use of tumour profiling tests to guide adjuvant chemotherapy in breast cancer. The Oncotype DX™ score (Genomic Health) has superseded more traditional tools such as PREDICT in appropriate patients (ER + ve, HER2-ve, lymph node negative and with a Nottingham Prognostic Index [NPI] ≥ 3.4). The aim of this study was to see whether the introduction of Oncotype DX within our institution resulted in an overall reduction in rates of chemotherapy. METHOD: Data was collected retrospectively using the Somerset Cancer Register, Pathology department databases and the institution's own online medical records system. Two groups were compared: (1) pre-oncotype (Jan 2012-Dec 2014) and (2) post-oncotype (Jan 2016-July 2018). RESULTS: During the pre-oncotype period, 28/82 (34%) patients who would have been eligible for testing (patients who were ER + ve, HER2-ve, and a NPI ≥ 3.4) received chemotherapy compared to 34/135 (25%) who were sent for oncotype during the second study period (p = 0.157). For grade 3 cancers, and those aged under 50, the results were more marked: grade 3 pre-oncotype 23/43 (53%), post-oncotype 29/76 (38%) (p = 0.101), aged under 50 pre-oncotype 8/15 (53%), post-oncotype 10/31 (32%) (p = 0.197). CONCLUSION: Within our institution, overall rates of chemotherapy have reduced since the introduction of Oncotype DX with the results more marked in subgroups of traditional indicators of tumour aggression. As genomic assays provide a more accurate prediction of the benefit of chemotherapy, its overall reduction has potential cost saving implications as well as reducing risk in patients who will derive little benefit.

Expediting rare disease diagnosis: a call to bridge the gap between clinical and functional genomics.

Approximately 400 million people throughout the world suffer from a rare disease. Although advances in whole exome and whole genome sequencing have greatly facilitated rare disease diagnosis, overall diagnostic rates remain below 50%. Furthermore, in cases where accurate diagnosis is achieved the process requires an average of 4.8 years. Reducing the time required for disease diagnosis is among the most critical needs of patients impacted by a rare disease. In this perspective we describe current challenges associated with rare disease diagnosis and discuss several cutting-edge functional genomic screening technologies that have the potential to rapidly accelerate the process of distinguishing pathogenic variants that lead to disease.

The concordance of treatment decision guided by OncotypeDX and the PREDICT tool in real-world early-stage breast cancer.

BACKGROUND: Decision-making regarding adjuvant chemotherapy for early-stage breast cancer can be guided by genomic assays such as OncotypeDX. The concordance of expected clinical decisions guided by OncotypeDX and prognostication online tools such as PREDICT is unknown. METHODS: We performed a retrospective single-center cohort study comprising all women with estrogen receptor (ER) positive, human epidermal growth factor receptor 2 (HER2) negative, node negative disease, whose tumors were sent for OncotypeDX analysis. Expected decision on adjuvant chemotherapy was evaluated using OncotypeDX and using PREDICT. The concordance between these two tools was calculated. The impact on concordance of prespecified features was assessed, including age, tumor size, intensity of ER and progesterone receptor (PR), grade, Ki67 and perineural and lymphovascular invasion. RESULTS: A total of 445 women were included. Overall concordance was 75% (K = 0.284). The concordance was significantly higher for grade 1 disease compared to grade 2-3 (93% vs 72%, P < .001), tumor ≤ 1 cm compared to >1 cm (85% vs 72%, P = .009), PR positive compared to PR negative (78% vs 58%, P < .001) and ki67 < 10% compared to ≥10% (92% vs 63%, P < .001). The intensity of ER and the presence of perineural or lymphovascular invasion had no significant impact on concordance. CONCLUSIONS: Compared to PREDICT, using OncotypeDx in node negative, ER positive disease is expected to change the clinical decision in a quarter of patients. The concordance between OncotypeDx and PREDICT is influenced by pathological features. In patients with very low risk, treatment decisions may be made based solely on clinical risk assessment.

Breast Cancer Prognostic Tests: Helping Patients Understand Testing Results and Their Implications.

Breast cancer prognostic tests have become an essential component of breast cancer care. Oncology nurses play an important role in assisting patients in their understanding of and decision making regarding the use of prognostic tests in treatment planning. This article outlines the most commonly used breast cancer prognostic tests, including the individual assay's purpose, its genomic makeup, the targeted patient population, and its prognostic and predictive abilities. Key nursing implications are discussed, highlighting how nurses can best apply knowledge of breast cancer prognostic tests to nursing practice.

Impact of Genomic Assay Testing and Clinical Factors on Chemotherapy Use After Implementation of Standardized Testing Criteria.

BACKGROUND: For clinically appropriate early-stage breast cancer patients, reflex criteria for Oncotype DX ordering ("the intervention") were implemented at our comprehensive cancer center, which reduced time-to-adjuvant chemotherapy initiation. Our objective was to evaluate Oncotype DX ordering practices and chemotherapy use before and after implementation of the intervention. MATERIALS AND METHODS: We examined medical records for 498 patients who had definitive breast cancer surgery at our center. The post-intervention cohort consisted of 232 consecutive patients who had Oncotype DX testing after reflex criteria implementation. This group was compared to a retrospective cohort of 266 patients who were diagnosed and treated prior to reflex criteria implementation, including patients who did and did not have Oncotype DX ordered. Factors associated with Oncotype DX ordering pre- and post-intervention were examined. We used multivariate logistic regression to evaluate factors associated with chemotherapy receipt among patients with Oncotype DX testing. RESULTS: The distribution of Oncotype DX scores, the proportion of those having Oncotype DX testing (28.9% vs. 34.1%) and those receiving chemotherapy (14.3% vs. 19.4%), did not significantly change between pre- and post-intervention groups. Age ≤65 years, stage II, grade 2, 1-3+ nodes, and tumor size >2 cm were associated with higher odds of Oncotype DX testing. Among patients having Oncotype DX testing, node status and Oncotype DX scores were significantly associated with chemotherapy receipt. CONCLUSION: Our criteria for reflex Oncotype DX ordering appropriately targeted patients for whom Oncotype DX would typically be ordered by providers. No significant change in the rate of Oncotype DX ordering or chemotherapy use was observed after reflex testing implementation. IMPLICATIONS FOR PRACTICE: This study demonstrates that implementing multidisciplinary consensus reflex criteria for Oncotype DX ordering maintains a stable Oncotype DX ordering rate and chemotherapy rate, mirroring what was observed in a specific clinical practice, while decreasing treatment delays due to additional testing. These reflex criteria appropriately capture patients who would likely have had Oncotype DX ordered by their providers and for whom the test results are predicted to influence management. This intervention serves as a potential model for other large integrated, multidisciplinary oncology centers to institute processes targeting patient populations most likely to benefit from genomic assay testing, while mitigating treatment delays.

The Impact of EndoPredict Clinical Score on Chemotherapy Recommendations in Women with Invasive ER+/HER2- Breast Cancer Stratified as Having Moderate or Poor Prognosis by Nottingham Prognostic Index.

BACKGROUND: The Nottingham Prognostic Index (NPI) was developed using tumour pathological features to guide decisions regarding adjuvant therapy in breast cancer. Recent breakthroughs in molecular biology aided development of genomic assays such as EndoPredict, which have been shown to provide excellent prognostic information. The current study investigated the impact of EndoPredict Clinical (EPClin), a composite of clinicopathological data and EndoPredict score, on chemotherapy recommendations based on NPI. PATIENTS AND METHODS: A total of 120 patients with oestrogen receptor-positive (ER+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer who were candidates for post-operative adjuvant chemotherapy at a single tertiary centre were included. Both NPI and EPClin were applied to all patients. NPI differentiated patients into groups with excellent/good prognosis (N=41; NPI≤3.4) or moderate/poor prognosis (N=79; NPI >3.4). The latter were considered for adjuvant chemotherapy. RESULTS: There was discordance in results of 31% of cases; 35% of the patients/candidates for adjuvant chemotherapy according to NPI were reclassified as being at low risk of recurrence by EPClin. CONCLUSION: Genomic profiling using EPClin reduces the potential need for adjuvant chemotherapy in women with ER+/HER2- breast cancer who are candidates for chemotherapy according to the NPI.

Clinical application and utility of genomic assays in early-stage breast cancer: key lessons learned to date.

Early-stage hormone receptor-positive breast cancer is the most common subtype and stage presenting in countries with organized screening programs. Standard clinical and pathologic factors are routinely used to support prognosis and decisions about adjuvant therapies. Hormone receptor and her2 status are essential for decision-making about the use of adjuvant hormonal and anti-her2 therapies respectively. Genomic assays are now commercially available to aid in either further prognostication or in refining the potential benefit of adjuvant chemotherapy. The current genomic assays all generally quantify estrogen receptor and proliferation gene sets (among others) by rna expression, although the specific genes assayed are quite discordant. The present review focuses on the pivotal studies in which each assay attempted to demonstrate clinical utility, with an emphasis on prospective trial data for each assay, if available. Using genomic assays, health care providers will increasingly be able to individualize therapy or de-escalate therapy, optimizing clinic benefit while minimizing toxicities from systemic therapies.

Biomarkers of aggressiveness in genitourinary tumors with emphasis on kidney, bladder, and prostate cancer.

INTRODUCTION: Over the last decade, the improvement in molecular techniques and the acquisition of genomic information has transformed and increased the quality of patient care and our knowledge of diseases. Areas covered: Protein expression levels in immunohistochemistry and molecular biomarkers are reported for their ability to predict recurrence, progression, development of metastases, or patient survival. In particular, for renal cell carcinoma, we take into consideration the biomarkers applicable to immunohistochemistry and with molecular and genetic analyses. In urothelial carcinoma, there is great interest in the possibility of distinguishing the basal vs. luminal subtypes and to acquire deeper insight into the tumor biology through examining exosomes in urine and biomarkers in the serum. In prostate cancer, single gene expression and multiple gene expression classifiers are reviewed as a tool to distinguish indolent vs. aggressive disease. Expert commentary: The genomic information along with the application of ancillary techniques allow the definition of a neoplasia not only by its morphology but also by its biological signature. This continuous increase in knowledge will result in a better comprehension of oncogenesis, development of targeted therapies and optimizing decision-making processes related to patient care.

A Comparison of the Performance of EndoPredict Clinical and NHS PREDICT in 120 Patients Treated for ER-positive Breast Cancer.

BACKGROUND: Computational algorithms, such as NHS PREDICT, have been developed using cancer registry data to guide decisions regarding adjuvant chemotherapy. They are limited by biases of the underlying data. Recent breakthroughs in molecular biology have aided the development of genomic assays which provide superior clinical information. In this study, we compared the performance in risk stratification of EndoPredict Clinical (EPClin, a composite of clinical data and EndoPredict) and PREDICT in a cohort of patients with breast cancer considered potential candidates for chemotherapy by the clinicians. MATERIALS AND METHODS: One hundred and twenty patients with biopsy-proven oestrogen receptor positive (ER+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer who underwent surgery were included. EPClin and PREDICT were determined for every tumour, and the results were compared. RESULTS: Using EPClin scores performed on 120 tumours, the cohort was stratified into low- (n=60) and high-risk (n=60) groups leading to 50% reduction in total chemotherapy prescriptions. PREDICT differentiated the patients into low- (n=45), intermediate- (n=33), and high-risk groups (n=42). Discordance between scores was demonstrated for 50 (41.66%) tumours. Nine (20%) out of 45 patients with low PREDICT scores had high EPClin scores and would otherwise not have received chemotherapy if the NHS PREDICT tool had been used alone. Eight (19%) out of 42 patients at high risk by PREDICT were reclassified as being at low risk by EPClin and avoided adjuvant chemotherapy. The sensitivity, specificity, positive predictive value and negative predictive value for NHS PREDICT to predict the potential need for chemotherapy as determined by EPClin were 85%, 51%, 68% and 80%, respectively. CONCLUSION: To our knowledge, this is the first clinical study to compare EPClin and PREDICT. The data indicate that computational algorithms such as NHS PREDICT may not accurately predict the need for chemotherapy leading to overtreatment, undertreatment or uncertainty and anxiety in a significant proportion of patients. This underscores the importance of more personalized prognostic tools.