The impact of the Oncotype Dx breast cancer assay in clinical practice: a systematic review and meta-analysis

Characteristics of premenopausal breast cancer patients with a midrange 21-gene recurrence score

Purpose

The results of the TAILORx trial have shown that premenopausal patients with intermediate Oncotype Dx (ODx) recurrence score of 16-25 may benefit from adjuvant chemotherapy. In addition, the clinicopathological features showed the information complementary to ODx results. However, the characteristics may vary depending on menopausal status even in the same score. This study aimed to analyze the differences in the clinical characteristics by menopausal status.

Methods

This study conducted a retrospective analysis of 756 patients with estrogen receptor-positive, human epidermal growth factor receptor 2-negative, and node-negative breast cancer who underwent the ODx test from July 2013 to December 2020 at the Severance Hospital.

Results

Of the 756 patients, 261 patients were postmenopausal, and 495 were premenopausal. The premenopausal patients with a midrange ODx had similar clinicopathological features as compared to those with a high ODx. Conversely, the postmenopausal patients with a midrange ODx did not show significantly different clinicopathological features from those with a low ODx, whereas a difference was seen as compared to those with a high ODx.

Conclusion

In this study, unlike the postmenopausal patients, some of the clinicopathological characteristics of the premenopausal patients with a midrange ODx were closer to those with a high ODx than those with a low ODx. In the premenopausal patients with a midrange ODx, considering the baseline characteristic itself, there was a significant difference between those with a low ODx when compared with postmenopausal patients. Therefore, more aggressive treatment decisions may be helpful in premenopausal patients with a midrange ODx.

Nomogram Development for Assessing Oncotype DX Recurrence Scores in Breast Cancer: A Chinese Population Study

BACKGROUND

Breast cancer (BC) is the most prevalent cancer among women worldwide, with increasing incidence rates, particularly in China. Given the high costs of Oncotype DX (ODX) testing, which predicts recurrence scores (RSs) on the basis of gene expression, developing a nomogram utilizing clinicopathological variables may provide an accessible alternative for risk stratification.

METHODS

We conducted a retrospective analysis of 703 estrogen receptor (ER)-positive, HER2-negative T1-3N0M0 BC patients who underwent ODX testing at Qilu Hospital. A nomogram was developed using multivariate logistic regression to predict low and high RSs in the group. Model performance was validated by receiver operating characteristic curve, calibration curve, and decision curve analysis.

RESULTS

Multivariate analysis revealed that older age, lower histologic grade, a higher ER expression level, a higher proportion of cells expressing progesterone receptor, and a lower proportion of cells expressing Ki-67 were significantly associated with a patient being in the low-risk subgroup. A nomogram was then developed using these variables to predict the RS, with an area under the curve (AUC) of 0.811 (95% confidence interval [CI] = 0.772-0.850) in the development group and 0.794 (95% CI = 0.737-0.851) in the validation group. Calibration and decision curve analyses further confirmed the nomogram's clinical utility. Moreover, a comparison between the TAILORx-nomogram and our nomogram was conducted, which proved that our nomogram has better predictive accuracy and reliability in Chinese BC patients.

CONCLUSION

We present the first nomogram for predicting the RS in Chinese patients with BC on the basis of clinicopathological factors. This model could aid in identifying patients who may not need ODX testing and serve as a cost-effective alternative for those unable to access ODX, thereby optimizing treatment decisions and enhancing patient management in resource-limited settings.

The EstroGene2.0 database for endocrine therapy response and resistance in breast cancer

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities ( https://estrogeneii.web.app/ ). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed transcriptomic landscape and substantial diversity in response to different classes of ER modulators. Endocrine-resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signalings, which is recapitulated clinically. Dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of cell model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancer's response to endocrine therapies and explore resistance mechanisms.

Bladder Cancer Treatments in the Age of Personalized Medicine: A Comprehensive Review of Potential Radiosensitivity Biomarkers

Bladder cancer is one of the most frequently diagnosed cancers in men. While cystectomy remains the primary treatment, advances in radiotherapy and chemotherapy have highlighted the value of bladder-preserving strategies, which can also enhance patients' quality of life. Despise these advances, around 20% of patients may still require salvage cystectomy due to tumor radioresistance. This underscores the need to develop radiosensitivity predictive assays. Radiotherapy acts by inducing DNA damage, primarily through DNA double-strand breaks, which can significantly affect treatment outcomes if left unrepaired. In addition to activating DNA repair pathways, the response to radiation also involves the tumor microenvironment, cell death pathways, immune responses and different types of cell death and proliferation receptors. In recent years, personalized medicine, which tailors treatments to individual patients, has gained increasing attention in cancer care. The development of chemo- and radiosensitivity predictive assays has become a key focus of cancer research. Despite the potential impact of such assays on bladder cancer treatment, there is still no reliable test that can help clinicians and informs patients in choosing the best treatment. This review aims to highlight studies that attempted to characterize bladder cancer radiosensitivity and to discuss the potential biomarkers that could be used to develop bladder cancer radiosensitivity predictive assays.

A multi-model approach integrating whole-slide imaging and clinicopathologic features to predict breast cancer recurrence risk

Breast cancer is the most common malignancy affecting women worldwide and is notable for its morphologic and biologic diversity, with varying risks of recurrence following treatment. The Oncotype DX Breast Recurrence Score test is an important predictive and prognostic genomic assay for estrogen receptor positive/HER2 negative breast cancer that guides therapeutic strategies; however, such tests can be expensive, delay care, and are not widely available. The aim of this study was to develop a multi-model approach integrating the analysis of whole-slide images and clinicopathologic data to predict their associated breast cancer recurrence risks and categorize these patients into two risk groups according to the predicted score: low-risk and high-risk. The proposed novel methodology uses convolutional neural networks for feature extraction and vision transformers for contextual aggregation, complemented by a logistic regression model that analyzes clinicopathologic data for classification into two risk categories. This method was trained and tested on 956 hematoxylin and eosin-stained whole-slide images of 950 ER+/HER2- breast cancer patients with corresponding clinicopathological features that had prior Oncotype DX testing. The model's performance was evaluated using an internal test set of 192 patients from Dartmouth Health and an external test set of 405 patients from the University of Chicago. The multi-model approach achieved an AUC of 0.91 (95% CI: 0.87-0.95) on the internal set and an AUC of 0.84 (95% CI: 0.78-0.89) on the external cohort for predicting low- and high-breast cancer recurrence risk categories based on the Oncotype DX recurrence score. With further validation, the proposed methodology could provide an alternative to assist clinicians in personalizing treatment for breast cancer patients and potentially improving their outcomes.

Disparities in OncotypeDx Testing and Subsequent Chemotherapy Receipt by Geography and Socioeconomic Status

BACKGROUND

OncotypeDx is a prognostic and predictive genomic assay used in early-stage hormone receptor-positive, HER2- (HR+/HER2-) breast cancer. It is used to inform adjuvant chemotherapy decisions, but not all eligible women receive testing. We aimed to assess variation in testing by demographics and geography, and to determine whether testing was associated with chemotherapy.

METHODS

For 1,615 women in the Carolina Breast Cancer Study with HR+/HER2-, Stage I-II tumors, we estimated prevalence differences (PD) and 95% confidence intervals (CI) for receipt of OncotypeDx genomic testing in association with and sociodemographic characteristics. We assessed associations between testing and chemotherapy receipt overall and by race. Finally, we calculated the proportion of eligible women receiving OncotypeDx by county-level rurality, census tract-level socioeconomic status, and Area Health Education Center regions.

RESULTS

38% (N = 609) of potentially eligible women were tested, with lower testing prevalences in Black (31%; PD, -11%; 95% CI, -16%-6%) and low-income women (24%; PD, -20%; 95% CI, -29% to -11%) relative to non-Black and higher income women. Urban participants were less likely to be tested than rural participants, though this association varied by region. Among women with low genomic risk tumors, tested participants were 29% less likely to receive chemotherapy than untested participants (95% CI, -40% to -17%). Racial differences in chemotherapy were restricted to untested women.

CONCLUSIONS

Both individual and area-level socioeconomics predict likelihood of OncotypeDx testing.

IMPACT

Variable adoption of OncotypeDx by socioeconomics and across geographic settings may contribute to excess chemotherapy among patients with HR+/HER2- cancers. See related In the Spotlight, p. 635.

Real-world use of multigene signatures in early breast cancer: differences to clinical trials

PURPOSE

In Italy, Lombardy was the first region to reimburse multigene assays (MGAs) for patients otherwise candidates for chemotherapy. This is a real-world experience of MGAs usage in six referral cancer centers in Lombardy.

METHODS

Among MGAs, Oncotype DX (RS) was used in 97% of cases. Consecutive patients tested with Oncotype DX from July 2020 to July 2022 were selected. The distribution of clinicopathologic features by RS groups (low RS: 0-25, high RS: 26-100) was assessed using chi-square and compared with those of the TAILORx and RxPONDER trials.

RESULTS

Out of 1,098 patients identified, 73% had low RS. Grade and Ki67 were associated with RS (p < 0.001). In patients with both G3 and Ki67 > 30%, 39% had low RS, while in patients with both G1 and Ki67 < 20%, 7% had high RS. The proportion of low RS in node-positive patients was similar to that in RxPONDER (82% vs 83%), while node-negative patients with low RS were significantly less than in TAILORx (66% vs 86%, p < 0.001). The distribution of Grade was different from registration trials, with more G3 and fewer G1 (38% and 3%) than in TAILORx (18% and 27%) and RxPONDER (10% and 24%) (p < 0.001). Patients ≤ 50 years were overrepresented in this series (41%) than in TAILORx and RxPONDER (31% and 24%, respectively) (p < 0.001) and, among them, 42% were node positive.

CONCLUSIONS

In this real-world series, Oncotype DX was the test almost exclusively used. Despite reimbursement being linked to pre-test chemotherapy recommendation, almost 3/4 patients resulted in the low-RS group. The significant proportion of node-positive patients ≤ 50 years tested indicates that oncologists considered Oncotype DX informative also in this population.

Nomogram prediction of the 70-gene signature (MammaPrint) binary and quartile categorized risk using medical history, imaging features and clinicopathological data among Chinese breast cancer patients

BACKGROUND

The 70-gene signature (70-GS, MammaPrint) test has been recommended by the main guidelines to evaluate prognosis and chemotherapy benefit of hormonal receptor positive human epidermal receptor 2 negative (HR + /Her2-) early breast cancer (BC). However, this expensive assay is not always accessible and affordable worldwide. Based on our previous study, we established nomogram models to predict the binary and quartile categorized risk of 70-GS.

METHODS

We retrospectively analyzed a consecutive cohort of 150 female patients with HR + /Her2- BC and eligible 70-GS test. Comparison of 40 parameters including the patients' medical history risk factors, imaging features and clinicopathological characteristics was performed between patients with high risk (N = 62) and low risk (N = 88) of 70-GS test, whereas risk calculations from established models including Clinical Treatment Score Post-5 years (CTS5), Immunohistochemistry 3 (IHC3) and Nottingham Prognostic Index (NPI) were also compared between high vs low binary risk of 70-GS and among ultra-high (N = 12), high (N = 50), low (N = 65) and ultra-low (N = 23) quartile categorized risk of 70-GS. The data of 150 patients were randomly split by 4:1 ratio with training set of 120 patients and testing set 30 patients. Univariate analyses and multivariate logistic regression were performed to establish the two nomogram models to predict the the binary and quartile categorized risk of 70-GS.

RESULTS

Compared to 70-GS low-risk patients, the high-risk patients had significantly less cardiovascular co-morbidity (p = 0.034), more grade 3 BC (p = 0.006), lower progesterone receptor (PR) positive percentage (p = 0.007), more Ki67 high BC (≥ 20%, p < 0.001) and no significant differences in all the imaging parameters of ultrasound and mammogram. The IHC3 risk and the NPI calculated score significantly correlated with both the binary and quartile categorized 70-GS risk classifications (both p < 0.001). The area under curve (AUC) of receiver-operating curve (ROC) of nomogram for binary risk prediction were 0.826 (C-index 0.903, 0.799-1.000) for training and 0.737 (C-index 0.785, 0.700-0.870) for validation dataset respectively. The AUC of ROC of nomogram for quartile risk prediction was 0.870 (C-index 0.854, 0.746-0.962) for training and 0.592 (C-index 0.769, 0.703-0.835) for testing set. The prediction accuracy of the nomogram for quartile categorized risk groups were 55.0% (likelihood ratio tests, p < 0.001) and 53.3% (p = 0.04) for training and validation, which more than double the baseline probability of 25%.

CONCLUSIONS

To our knowledge, we are the first to establish easy-to-use nomograms to predict the individualized binary (high vs low) and the quartile categorized (ultra-high, high, low and ultra-low) risk classification of 70-GS test with fair performance, which might provide information for treatment choice for those who have no access to the 70-GS testing.

Evolution of Breast Cancer Recurrence Risk Prediction: A Systematic Review of Statistical and Machine Learning-Based Models

PURPOSE

Selection of appropriate adjuvant therapy to ultimately reduce the risk of breast cancer (BC) recurrence is a challenge for medical oncologists. Several automated risk prediction models have been developed using retrospective clinical data and have evolved significantly over the years in terms of predictors of recurrence, data usage, and predictive techniques (statistical/machine learning [ML]).

METHODS

Following PRISMA guidelines, we performed a systematic literature review of the aforementioned statistical and ML models published between January 2008 and December 2022 through searching five digital databases-PubMed, ScienceDirect, Scopus, Cochrane, and Web of Science. The comprehensive search yielded a total of 163 papers and after a screening process focusing on papers that dealt exclusively with statistical/ML methods, only 23 papers were deemed appropriate for further analysis. We benchmarked the studies on the basis of development, evaluation metrics, and validation strategy with an added emphasis on racial diversity of patients included in the studies.

RESULTS

In total, 30.4% of the included studies use statistical techniques, while 69.6% are ML-based. Among these, traditional ML models (support vector machines, decision tree, logistic regression, and naïve Bayes) are the most frequently used (26.1%) along with deep learning (26.1%). Deep learning and ensemble learning provide the most accurate predictions (AUC = 0.94 each).

CONCLUSION

ML-based prediction models exhibit outstanding performance, yet their practical applicability might be hindered by limited interpretability and reduced generalization. Moreover, predictive models for BC recurrence often focus on limited variables related to tumor, treatment, molecular, and clinical features. Imbalanced classes and the lack of open-source data sets impede model development and validation. Furthermore, existing models predominantly overlook African and Middle Eastern populations, as they are trained and validated mainly on Caucasian and Asian patients.

Development of a high-performance multi-probe droplet digital PCR assay for high-sensitivity detection of human papillomavirus circulating tumor DNA from plasma

OBJECTIVES

To develop a high-performance droplet digital PCR (ddPCR) assay capable of enhancing the detection of human papillomavirus (HPV) circulating tumor DNA (ctDNA) in plasma from patients with HPV-associated oropharyngeal squamous cell carcinoma (HPV+ OPSCC).

MATERIALS AND METHODS

Plasma samples from subjects with HPV+ OPSCC were collected. We developed a high-performance ddPCR assay designed to simultaneously target nine regions of the HPV16 genome.

RESULTS

The new assay termed 'ctDNA HPV16 Assessment using Multiple Probes' (CHAMP- 16) yielded significantly higher HPV16 counts compared to our previously validated 'Single-Probe' (SP) assay and a commercially available NavDx® assay. Analytical validation demonstrated that the CHAMP-16 assay had a limit of detection (LoD) of 4.1 copies per reaction, corresponding to < 1 genome equivalent (GE) of HPV16. When tested on plasma ctDNA from 21 patients with early-stage HPV+ OPSCC and known HPV16 ctDNA using the SP assay, all patients were positive for HPV16 ctDNA in both assays and the CHAMP-16 assay displayed 6.6-fold higher HPV16 signal on average. Finally, in a longitudinal analysis of samples from a patient with recurrent disease, the CHAMP-16 assay detected HPV16 ctDNA signal ∼ 20 months prior to the conventional SP assay.

CONCLUSION

Increased HPV16 signal detection using the CHAMP-16 assay suggests the potential for detection of recurrences significantly earlier than with conventional ddPCR assays in patients with HPV16+ OPSCC. Critically, this multi-probe approach maintains the cost-benefit advantage of ddPCR over next generation sequencing (NGS) approaches, supporting the cost-effectiveness of this assay for both large population screening and routine post-treatment surveillance.

Cost-utility analysis of genomic profiling in early breast cancer in Colombia

BACKGROUND

In Colombia, the best strategy to establish indication for adjuvant chemotherapy in early breast cancer (EBC) remains unknown. This study aimed to identify the cost-utility of Oncotype DX™ (ODX) or Mammaprint™ (MMP) tests to establish the necessity of adjuvant chemotherapy.

METHODS

This study used an adapted decision-analytic model to compare cost and outcomes of care between ODX or MMP tests and routine care without ODX or MMP tests (adjuvant chemotherapy for all patients) over a 5-year time horizon from the perspective of the Colombian National Health System (NHS; payer). Inputs were obtained from national unit cost tariffs, published literature, and clinical trial database. The study population comprised women with hormone-receptor-positive (HR +), HER2-negative, lymph-node-negative (LN0) EBC with high-risk clinical criteria for recurrence. The outcome measures were discounted incremental cost-utility ratio (ICUR; 2021 United States dollar per quality-adjusted life-year [QALY] gained) and net monetary benefit (NMB). Probabilistic (PSA) and deterministic sensitivity analysis (DSA) were performed.

RESULTS

ODX increases QALYs by 0.05 and MMP by 0.03 with savings of $2374 and $554 compared with the standard strategy, respectively, and were cost-saving in cost-utility plane. NMB for ODX was $2203 and for MMP was $416. Both tests dominate the standard strategy. Sensitivity analysis revealed that with a threshold of 1 gross domestic product per capita, ODX will be cost-effective in 95.5% of the cases compared with 70.2% cases involving MMP.DSA showed that the variable with significant influence was the monthly cost of adjuvant chemotherapy. PSA revealed that ODX was a consistently superior strategy.

CONCLUSIONS

Genomic profiling using ODX or MMP tests to define the need of adjuvant chemotherapy treatment in patients with HR + and HER2 -EBC is a cost-effective strategy that allows Colombian NHS to maintain budget.

Biomarkers in Breast Cancer: An Old Story with a New End

Breast cancer is the second most frequent cancer in the world. It is a heterogeneous disease and the leading cause of cancer mortality in women. Advances in molecular technologies allowed for the identification of new and more specifics biomarkers for breast cancer diagnosis, prognosis, and risk prediction, enabling personalized treatments, improving therapy, and preventing overtreatment, undertreatment, and incorrect treatment. Several breast cancer biomarkers have been identified and, along with traditional biomarkers, they can assist physicians throughout treatment plan and increase therapy success. Despite the need of more data to improve specificity and determine the real clinical utility of some biomarkers, others are already established and can be used as a guide to make treatment decisions. In this review, we summarize the available traditional, novel, and potential biomarkers while also including gene expression profiles, breast cancer single-cell and polyploid giant cancer cells. We hope to help physicians understand tumor specific characteristics and support decision-making in patient-personalized clinical management, consequently improving treatment outcome.

Decision impact studies, evidence of clinical utility for genomic assays in cancer: A scoping review

BACKGROUND

Decision impact studies have become increasingly prevalent in cancer prognostic research in recent years. These studies aim to evaluate the impact of a genomic test on decision-making and appear to be a new form of evidence of clinical utility. The objectives of this review were to identify and characterize decision impact studies in genomic medicine in cancer care and categorize the types of clinical utility outcomes reported.

METHODS

We conducted a search of four databases, Medline, Embase, Scopus and Web of Science, from inception to June 2022. Empirical studies that reported a "decision impact" assessment of a genomic assay on treatment decisions or recommendations for cancer patients were included. We followed scoping review methodology and adapted the Fryback and Thornbury Model to collect and analyze data on clinical utility. The database searches identified 1803 unique articles for title/abstract screening; 269 articles moved to full-text review.

RESULTS

87 studies met inclusion criteria. All studies were published in the last 12 years with the majority for breast cancer (72%); followed by other cancers (28%) (lung, prostate, colon). Studies reported on the impact of 19 different proprietary (18) and generic (1) assays. Across all four levels of clinical utility, outcomes were reported for 22 discrete measures, including the impact on provider/team decision-making (100%), provider confidence (31%); change in treatment received (46%); patient psychological impacts (17%); and costing or savings impacts (21%). Based on the data synthesis, we created a comprehensive table of outcomes reported for clinical utility.

CONCLUSIONS

This scoping review is a first step in understanding the evolution and uses of decision impact studies and their influence on the integration of emerging genomic technologies in cancer care. The results imply that DIS are positioned to provide evidence of clinical utility and impact clinical practice and reimbursement decision-making in cancer care. Systematic review registration: Open Science Framework osf.io/hm3jr.

A 10 year service evaluation of the survival of 439 patients with early oestrogen receptor positive breast cancer who underwent initial OncotypeDX ® testing to guide adjuvant chemotherapy decisions

OBJECTIVE

To explore the long-term outcome of patients who underwent Oncotype DX® testing. The relationship between the RS, adjuvant treatments received, and clinical outcomes across the entire range of RS results are reported.

METHODS

10-year Kaplan-Meier estimates for distant recurrence/BC-specific survival (BCSS) in this cohort. The analysis included 439 patients. The follow-up time ranged from 14 to 142 months. All analyses were performed using the SPSS v20.

RESULTS

More than half of patients had low RS (<18) (55.6%) and 15.3% had RS ≥ 31. Chemotherapy use was consistent with the RS with 4.4%, 7.1%, 28.0%, 71.4% and 91.0% receiving adjuvant chemotherapy in patients with RS < 11, 11-17, 18-25, 26-30, and ≥31, respectively. The overall chemotherapy rate was 27.6%. Distant metastasis free survival (DMFS) differed significantly (P < 0.001) between the RS groups with 10 year DMFS rates of 99% (SE +/- 0.01) in the RS<11, 97% (SE +/- 0.03) in the RS 11-17, 97% (SE +/- 0.02) in the RS 18-25, 85% (SE +/- 0.1) in the RS 26-30 and 74% (SE +/- 0.08) in the RS ≥ 31 group. Ten year breast cancer specific survival also differed significantly (P < 0.001) between the RS groups; this risk was 100% (no deaths from breast cancer reported in the first 10 years) in RS < 11, 95% (SE +/- 0.03) in RS 11-17, 94% (SE +/- 0.04) in RS 18-25, 93% (SE +/- 0.07) in RS 26-30, and 79% (SE +/- 0.07) in the RS ≥ 31 group.

CONCLUSIONS

Use of Oncotype DX RS does guide the treatment decisions and correlates with the BCSS and disease-free survival for ER positive, Her2 negative, early-stage, node negative breast cancer patients.

A logarithmic model for hormone receptor-positive and breast cancer patients treated with neoadjuvant chemotherapy

OBJECTIVE

The aim of this study was to investigate the predictive importance of the previously validated log(ER)*log(PgR)/Ki-67 predictive model in a larger patient population.

METHODS

Patients with hormone receptor positive/HER-2 negative and clinical node positive before chemotherapy were included. Log(ER)*log(PgR)/Ki-67 values of the patients were determined, and the ideal cutoff value was calculated using a receiver operating characteristic curve analysis. It was analyzed with a logistic regression model along with other clinical and pathological characteristics.

RESULTS

A total of 181 patients were included in the study. The ideal cutoff value for pathological response was 0.12 (area under the curve=0.585, p=0.032). In the univariate analysis, no statistical correlation was observed between luminal subtype (p=0.294), histological type (p=0.238), clinical t-stage (p=0.927), progesterone receptor level (p=0.261), Ki-67 cutoff value (p=0.425), and pathological complete response. There was a positive relationship between numerical increase in age and residual disease. As the grade of the patients increased, the probability of residual disease decreased. Patients with log(ER)*log(PgR)/Ki-67 above 0.12 had an approximately threefold increased risk of residual disease when compared to patients with 0.12 and below (odds ratio: 3.17, 95% confidence interval: 1.48-6.75, p=0.003). When age, grade, and logarithmic formula were assessed together, the logarithmic formula maintained its statistical significance (odds ratio: 2.47, 95% confidence interval: 1.07-5.69, p=0.034).

CONCLUSION

In hormone receptor-positive breast cancer patients receiving neoadjuvant chemotherapy, the logarithmic model has been shown in a larger patient population to be an inexpensive, easy, and rapidly applicable predictive marker that can be used to predict response.

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.

Survival Analysis with High-Dimensional Omics Data Using a Threshold Gradient Descent Regularization-Based Neural Network Approach

Analysis of data with a censored survival response and high-dimensional omics measurements is now common. Most of the existing analyses are based on specific (semi)parametric models, in particular the Cox model. Such analyses may be limited by not having sufficient flexibility, for example, in accommodating nonlinearity. For categorical and continuous responses, neural networks (NNs) have provided a highly competitive alternative. Comparatively, NNs for censored survival data remain limited. Omics measurements are usually high-dimensional, and only a small subset is expected to be survival-associated. As such, regularized estimation and selection are needed. In the existing NN studies, this is usually achieved via penalization. In this article, we propose adopting the threshold gradient descent regularization (TGDR) technique, which has competitive performance (for example, when compared to penalization) and unique advantages in regression analysis, but has not been adopted with NNs. The TGDR-based NN has a highly sensible formulation and an architecture different from the unregularized and penalization-based ones. Simulations show its satisfactory performance. Its practical effectiveness is further established via the analysis of two cancer omics datasets. Overall, this study can provide a practical and useful new way in the NN paradigm for survival analysis with high-dimensional omics measurements.

Protein expression of the gp78 E3 ligase predicts poor breast cancer outcome based on race

Women of African ancestry suffer higher rates of breast cancer mortality compared with all other groups in the United States. Though the precise reasons for these disparities remain unclear, many recent studies have implicated a role for differences in tumor biology. Using an epitope-validated antibody against the endoplasmic reticulum-associated E3 ligase, gp78, we show that elevated levels of gp78 in patient breast cancer cells predict poor survival. Moreover, high levels of gp78 are associated with poor outcomes in both ER+ and ER- tumors, and breast cancers expressing elevated amounts of gp78 protein are enriched in gene expression pathways that influence cell cycle, metabolism, receptor-mediated signaling, and cell stress response pathways. In multivariate analysis adjusted for subtype and grade, gp78 protein is an independent predictor of poor outcomes in women of African ancestry. Furthermore, gene expression signatures, derived from patients stratified by gp78 protein expression, are strong predictors of recurrence and pathological complete response in retrospective clinical trial data and share many common features with gene sets previously identified to be overrepresented in breast cancers based on race. These findings implicate a prominent role for gp78 in tumor progression and offer insights into our understanding of racial differences in breast cancer outcomes.

Impact of genomic assays on treatment and outcomes in locally advanced breast cancer

PURPOSE

Genomic profiling in early-stage breast cancer provides prognostic and predictive information. Genomic profiling assays have not been validated in locally advanced breast cancer (LABC). We examined a large cancer registry to evaluate genomic profiling in LABC and its effect on treatment decisions and survival.

METHODS

Females with ER+/HER2- LABC who did not receive neoadjuvant therapy were selected from the National Cancer Database 2004-2017. We compared characteristics between patients with and without genomic profiling and with low genomic risk, 21-gene recurrence score ≤ 25 or low-risk 70-gene signature, treated with endocrine therapy ± chemotherapy. Propensity score methods were utilized to account for covariates that may have predicted treatment. Univariable and multivariable survival analyses were performed.

RESULTS

Of 18,437 patients with LABC, 1258 (7%) had genomic profiling and 1022 (81%) had low genomic risk results. 562 patients (55%) with low genomic risk received chemotherapy and endocrine therapy (chemoendocrine). Patients who received chemoendocrine therapy were younger, had fewer comorbidities, presented with higher stage disease, had higher grade tumors, more frequently had partial mastectomy, and more often received radiation than those who received endocrine therapy alone. On multivariable analysis, endocrine therapy alone was associated with worse OS compared to chemoendocrine therapy (HR 1.77, 95% CI 1.13-2.78, p = 0.013).

CONCLUSION

In women with LABC and low genomic risk, endocrine therapy alone was associated with worse OS compared to chemoendocrine therapy. This suggests that genomic profiling is not predictive in LABC. Accordingly, genomic profiling should not be routinely utilized to make adjuvant treatment decisions in LABC in the absence of further data which shows a benefit.

Addressing the problem of overtreatment in breast cancer

INTRODUCTION

As breast cancer treatment options have multiplied and biologic diversity within breast cancer has been recognized, the use of the same treatment strategies for patients with early-stage and favorable disease, and for those with biologically aggressive disease, has been questioned. In addition, as patient-reported outcome measures have called attention to the morbidity of many common treatments, and as the cost of breast cancer care has continued to increase, reduction in the overtreatment of breast cancer has assumed increasing importance.

AREAS COVERED

Here we review selected aspects of surgery, radiation oncology, and medical oncology for which scientific evidence supports de-escalation for invasive carcinoma and ductal carcinoma in situ, and assess strategies to address overtreatment.

EXPERT OPINION

The problems of breast cancer overtreatment we face today are based on improved understanding of the biology of breast cancer and abandonment of the 'one-size-fits-all' approach. As breast cancer care becomes increasingly complex, and as our knowledge base continues to increase exponentially, these problems will only be magnified in the future. To continue progress, the move must be made from advocating the maximum-tolerated treatment to advocating the minimum-effective one.

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.

Potential Refinement of Recurrence Score by pSTAT3 Status

The likelihood of recurrence in breast cancer patients with hormone receptor-positive (HR-positive) tumors is influenced by clinical, histopathological, and molecular features. Recent studies suggested that activated STAT3 (pSTAT3) might serve as a biomarker of outcome in breast cancer patients. In the present work, we have analyzed the added value of pSTAT3 to OncotypeDx Recurrence Score (RS) in patient prognostication. We have found that patients with low RS (<26) and low pSTAT3 might represent a population at a higher risk for cancer recurrence. Furthermore, we have observed that a positive pSTAT3 score alone can be a favorable marker for patients with HR-positive breast cancer under the age of 50. In an era of personalized medicine, these findings warrant further appraisal of chemotherapy benefit in this population.

In silico tools and databases for designing cancer immunotherapy

Immunotherapy is a rapidly growing therapy for cancer which have numerous benefits over conventional treatments like surgery, chemotherapy, and radiation. Overall survival of cancer patients has improved significantly due to the use of immunotherapy. It acts as a novel pillar for treating different malignancies from their primary to the metastatic stage. Recent preferments in high-throughput sequencing and computational immunology leads to the development of targeted immunotherapy for precision oncology. In the last few decades, several computational methods and resources have been developed for designing immunotherapy against cancer. In this review, we have summarized cancer-associated genomic, transcriptomic, and mutation profile repositories. We have also enlisted in silico methods for the prediction of vaccine candidates, HLA binders, cytokines inducing peptides, and potential neoepitopes. Of note, we have incorporated the most important bioinformatics pipelines and resources for the designing of cancer immunotherapy. Moreover, to facilitate the scientific community, we have developed a web portal entitled ImmCancer (https://webs.iiitd.edu.in/raghava/immcancer/), comprises cancer immunotherapy tools and repositories.

Precision Medicine: Technological Impact into Breast Cancer Diagnosis, Treatment and Decision Making

Breast cancer is the most common cancer in women, impacting 2.1 million women each year. The number of publications on BC is much higher than for any other type of tumor, as well as the number of clinical trials. One of the consequences of all this information is reflected in the number of approved drugs. This review aims to discuss the impact of technological advances in the diagnosis, treatment and decision making of breast cancer and the prospects for the next 10 years. Currently, the literature has described personalized medicine, but what will the treatment be called for in the coming years?

A nomogram for predicting probability of low risk of MammaPrint results in women with clinically high-risk breast cancer

We aimed to develop a prediction MammaPrint (MMP) genomic risk assessment nomogram model for hormone-receptor positive (HR+) and human epidermal growth factor receptor-2 negative (HER2–) breast cancer and minimal axillary burden (N0-1) tumors using clinicopathological factors of patients who underwent an MMP test for decision making regarding adjuvant chemotherapy. A total of 409 T1-3 N0-1 M0 HR + and HER2– breast cancer patients whose MMP genomic risk results and clinicopathological factors were available from 2017 to 2020 were analyzed. With randomly selected 306 patients, we developed a nomogram for predicting a low-risk subgroup of MMP results and externally validated with remaining patients (n = 103). Multivariate analysis revealed that the age at diagnosis, progesterone receptor (PR) score, nuclear grade, and Ki-67 were significantly associated with MMP risk results. We developed an MMP low-risk predictive nomogram. With a cut off value at 5% and 95% probability of low-risk MMP, the nomogram accurately predicted the results with 100% positive predictive value (PPV) and negative predictive value respectively. When applied to cut-off value at 35%, the specificity and PPV was 95% and 86% respectively. The area under the receiver operating characteristic curve was 0.82 (95% confidence interval [CI] 0.77 to 0.87). When applied to the validation group, the nomogram was accurate with an area under the curve of 0.77 (95% CI 0.68 to 0.86). Our nomogram, which incorporates four traditional prognostic factors, i.e., age, PR, nuclear grade, and Ki-67, could predict the probability of obtaining a low MMP risk in a cohort of high clinical risk patients. This nomogram can aid the prompt selection of patients who does not need additional MMP testing.

Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review

OBJECTIVE

To review biomarker discovery studies using omics data for patient stratification which led to clinically validated FDA-cleared tests or laboratory developed tests, in order to identify common characteristics and derive recommendations for future biomarker projects.

DESIGN

Scoping review.

METHODS

We searched PubMed, EMBASE and Web of Science to obtain a comprehensive list of articles from the biomedical literature published between January 2000 and July 2021, describing clinically validated biomarker signatures for patient stratification, derived using statistical learning approaches. All documents were screened to retain only peer-reviewed research articles, review articles or opinion articles, covering supervised and unsupervised machine learning applications for omics-based patient stratification. Two reviewers independently confirmed the eligibility. Disagreements were solved by consensus. We focused the final analysis on omics-based biomarkers which achieved the highest level of validation, that is, clinical approval of the developed molecular signature as a laboratory developed test or FDA approved tests.

RESULTS

Overall, 352 articles fulfilled the eligibility criteria. The analysis of validated biomarker signatures identified multiple common methodological and practical features that may explain the successful test development and guide future biomarker projects. These include study design choices to ensure sufficient statistical power for model building and external testing, suitable combinations of non-targeted and targeted measurement technologies, the integration of prior biological knowledge, strict filtering and inclusion/exclusion criteria, and the adequacy of statistical and machine learning methods for discovery and validation.

CONCLUSIONS

While most clinically validated biomarker models derived from omics data have been developed for personalised oncology, first applications for non-cancer diseases show the potential of multivariate omics biomarker design for other complex disorders. Distinctive characteristics of prior success stories, such as early filtering and robust discovery approaches, continuous improvements in assay design and experimental measurement technology, and rigorous multicohort validation approaches, enable the derivation of specific recommendations for future studies.

Multicenter retrospective study on the use of Curebest™ 95GC Breast for estrogen receptor-positive and node-negative early breast cancer

Background

The benefits of postoperative chemotherapy in patients with estrogen receptor (ER)-positive breast cancer remain unclear. The use of tumor grade, Ki-67, or ER expression failed to provide an accurate prognosis of the risk of relapse after surgery in patients. This study aimed to evaluate whether a multigene assay Curebest™ 95GC Breast (95GC) can identify the risk of recurrence and provide more insights into the requirements for chemotherapy in patients.

Methods

This single-arm retrospective multicenter joint study included patients with ER-positive, node-negative breast cancer who were treated at five facilities in Japan and had received endocrine therapy alone as adjuvant therapy. The primary lesion specimens obtained during surgery were analyzed using the 95GC breast cancer multigene assay. Based on the 95GC results, patients were classified into low-risk (95GC-L) and high-risk (95GC-H) groups.

Results

The 10-year relapse-free survival rates were 88.4 and 59.6% for the 95GC-L and 95GC-H groups, respectively. Histologic grade, Ki-67, and PAM50 exhibited a significant relationship with the 95GC results. The segregation into 95GC-L and 95GC-H groups within established clinical factors can identify subgroups of patients using histologic grade or PAM50 classification with good prognosis without receiving chemotherapy.

Conclusions

Based on the results of our retrospective study, 95GC could be used to evaluate the long-term prognosis of ER-positive, node-negative breast cancer. Even though further prospective validation is necessary, the inclusion of 95GC in clinical practice could help to select optimal treatments for breast cancer patients and identify those who do not benefit from the addition of chemotherapy, thus avoiding unnecessary treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08778-5.

A new paradigm for leprosy diagnosis based on host gene expression

Transcriptional profiling is a powerful tool to investigate and detect human diseases. In this study, we used bulk RNA-sequencing (RNA-Seq) to compare the transcriptomes in skin lesions of leprosy patients or controls affected by other dermal conditions such as granuloma annulare, a confounder for paucibacillary leprosy. We identified five genes capable of accurately distinguishing multibacillary and paucibacillary leprosy from other skin conditions. Indoleamine 2,3-dioxygenase 1 (IDO1) expression alone was highly discriminatory, followed by TLR10, BLK, CD38, and SLAMF7, whereas the HS3ST2 and CD40LG mRNA separated multi- and paucibacillary leprosy. Finally, from the main differentially expressed genes (DEG) and enriched pathways, we conclude that paucibacillary disease is characterized by epithelioid transformation and granuloma formation, with an exacerbated cellular immune response, while multibacillary leprosy features epithelial-mesenchymal transition with phagocytic and lipid biogenesis patterns in the skin. These findings will help catalyze the development of better diagnostic tools and potential host-based therapeutic interventions. Finally, our data may help elucidate host-pathogen interplay driving disease clinical manifestations.

Circulating Tumour DNA as a Potential Cost-Effective Biomarker to Reduce Adjuvant Chemotherapy Overtreatment in Stage II Colorectal Cancer

BACKGROUND AND OBJECTIVE

Substantial adjuvant chemotherapy (AC) overtreatment for stage II colorectal cancer results in a health and financial burden. Circulating tumour DNA (ctDNA) can improve patient selection for AC by detecting micro-metastatic disease. We estimated the health economic potential of ctDNA-guided AC for stage II colorectal cancer.

METHODS

A cost-utility analysis was performed to compare ctDNA-guided AC to standard of care, where 22.6% of standard of care patients and all ctDNA-positive patients (8.7% of tested patients) received AC and all ctDNA-negative patients (91.3%) did not. A third preference-sensitive ctDNA strategy was included where 6.8% of ctDNA-negative patients would receive AC. A state-transition model was populated using data from a prospective cohort study and clinical registries. Health and economic outcomes were discounted at 5% over a lifetime horizon from a 2019 Australian payer perspective. Extensive scenario and probabilistic analyses quantified model uncertainty.

RESULTS

Compared to standard of care, the ctDNA and preference-sensitive ctDNA strategies increased quality-adjusted life-years by 0.20 (95% confidence interval - 0.40 to 0.81) and 0.19 (- 0.40 to 0.78), and resulted in incremental costs of AUD - 4055 (- 16,853 to 8472) and AUD - 2284 (- 14,685 to 10,116), respectively. Circulating tumour DNA remained cost effective at a willingness to pay of AUD 20,000 per quality-adjusted life-year gained throughout most scenario analyses in which the proportion of ctDNA-positive patients cured by AC and compliance to a ctDNA-negative test results were decreased.

CONCLUSIONS

Circulating tumour-guided AC is a potentially cost-effective strategy towards reducing overtreatment in stage II colorectal cancer. Results from ongoing randomised clinical studies will be important to reduce uncertainty in the estimates.

Impact of Oncotype DX testing on ER+ breast cancer treatment and survival in the first decade of use

BACKGROUND

The Oncotype DX breast recurrence score has been introduced more than a decade ago to aid physicians in determining the need for systemic adjuvant chemotherapy in patients with early-stage, estrogen receptor (ER)+, lymph node-negative breast cancer.

METHODS

In this study, we utilized data from The Surveillance, Epidemiology, and End Results (SEER) Program to investigate temporal trends in Oncotype DX usage among US breast cancer patients in the first decade after the introduction of the Oncotype DX assay.

RESULTS

We found that the use of Oncotype DX has steadily increased in the first decade of use and that this increase is associated with a decreased usage of chemotherapy. Patients who utilized the Oncotype DX test tended to have improved survival compared to patients who did not use the assay even after adjusting for clinical variables associated with prognosis. In addition, chemotherapy usage in patients with high-risk scores is associated with significantly longer overall and breast cancer-specific survival compared to high-risk patients who did not receive chemotherapy. On the contrary, patients with low-risk scores who were treated with chemotherapy tended to have shorter overall survival compared to low-risk patients who forwent chemotherapy.

CONCLUSION

We have provided a comprehensive temporal overview of the use of Oncotype DX in breast cancer patients in the first decade after Oncotype DX was introduced. Our results suggest that the use of Oncotype DX is increasing in ER+ breast cancer and that the Oncotype DX test results provide valuable information for patient treatment and prognosis.

Evaluating the Clinical Utility of Routine Sentinel Lymph Node Biopsy and the Value of Adjuvant Chemotherapy in Elderly Patients Diagnosed With Oestrogen Receptor Positive, Clinically Node Negative Breast Cancer

Background

Sentinel lymph node biopsy (SLNB) provides staging information and guides adjuvant therapy in early breast cancer (EBC). Routine SLNB in oncogeriatricians with low-risk EBC remains controversial.

Aims

To evaluate axillary management in elderly patients diagnosed with oestrogen receptor positive (ER+), clinically lymph node negative (cLN-) EBC, and to assess whether SLNB affects further axillary management or adjuvant chemotherapy (ACTX) decision making.

Methods

Female patients aged > 65 years, diagnosed with ER+, human epidermal growth factor receptor-2 negative (HER2-), and cLN- breast cancer (BC), who underwent surgery and SLNB were included. Clinicopathological predictors of ACTX and completion axillary lymph node dissection (CALND) were determined. Kaplan-Meier analyses assessed survival outcomes.

Results

A total of 253 patients were included (median age: 72 years, range: 66-90), all underwent SLNB; 50 (19.8%) had lymphatic metastasis on SLNB (SLNB+). Of these, 19 proceeded to CALND (38.0%), 10 (52.6%) of whom had further axillary disease (ALND+). 20 of the 50 SLNB+ patients received ACTX (40.0%) as did 31 of the 203 SLNB- patients (15.2%) (P < .001). Oncotype DX (ODX) testing was utilized in 82 cases (32.8%). Younger age (P < .001), SLNB+ (P < .001) and ODX score (P = .003) were all associated with ACTX prescription. ODX > 25 (OR: 4.37, 95% CI: 1.38-13.80, P = .012) independently predicted receiving ACTX. Receiving ACTX and proceeding to CALND did not improve disease-free (P = .485 and P = .345) or overall survival (P = .981 and P = .646).

Conclusions

Routine SNLB may not be necessary in elderly patients diagnosed with ER+, cLN- EBC. Future oncogeriatric practice is likely to see genomic testing guiding ACTX prescription in this group.

An in vivo genome-wide shRNA screen identifies BCL6 as a targetable biomarker of paclitaxel resistance in breast cancer

Paclitaxel is a common breast cancer drug; however, some tumors are resistant. The identification of biomarkers for paclitaxel resistance or sensitivity would enable the development of strategies to improve treatment efficacy. A genome-wide in vivo shRNA screen was performed on paclitaxel-treated mice with MDA-MB-231 tumors to identify genes associated with paclitaxel sensitivity or resistance. Gene expression of the top screen hits was associated with tumor response (resistance or sensitivity) among patients who received neoadjuvant chemotherapy containing paclitaxel. We focused our validation on screen hit B-cell lymphoma 6 (BCL6), which is a therapeutic target in cancer but for which no effects on drug response have been reported. Knockdown of BCL6 resulted in increased tumor regression in mice treated with paclitaxel. Similarly, inhibiting BCL6 using a small molecule inhibitor enhanced paclitaxel treatment efficacy both in vitro and in vivo in breast cancer models. Mechanism studies revealed that reduced BCL6 enhances the efficacy of paclitaxel by inducing sustained G1/S arrest, concurrent with increased apoptosis and expression of target gene cyclin-dependent kinase inhibitor 1A. In summary, the genome-wide shRNA knockdown screen has identified BCL6 as a potential targetable resistance biomarker of paclitaxel response in breast cancer.

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.

Prosigna test in breast cancer: real-life experience

PURPOSE

Genomic tests can guide the decision to administer adjuvant chemotherapy in women with hormone receptor (HR)-positive, Human Epidermal growth Factor 2 (HER2)-negative breast cancer (BC) at intermediate risk of recurrence. We assessed the decision-making and economic impact of the Prosigna test in a real-life setting.

METHODS

Retrospective cohort study of HR + , HER2- BC patients managed from 2016 to 2020, potential candidates for adjuvant chemotherapy, at intermediate risk of recurrence, in whom a Prosigna test was performed according to contemporary guidelines. The additional cost of chemotherapy over one year in terms of direct medical and non-medical costs was estimated in this study to be €9,737 (derived from a previous study, NCT02813317). The cost of the Prosigna test, as defined by the reimbursement system, was €1,849.

RESULTS

Among the 809 patients included in this study, 2.3 Prosigna tests had to be performed to avoid adjuvant chemotherapy for one patient. The number of tests that had to be performed to avoid chemotherapy for one patient was higher for patients with grade 3 tumors and pN1mic axillary node involvement and lower for grade 1 tumors or in the absence of axillary node involvement (pN0), but did not vary according to the 10-year overall survival gain predicted by the Predict online test. The cost saving related to withholding of adjuvant chemotherapy for one patient on the basis of the Prosigna test results was €5,485.

CONCLUSION

We present one of the largest cohorts of HR + , HER2- BC patients at intermediate risk of recurrence, in whom a Prosigna test was used to guide the adjuvant therapy decision in a real-life setting, resulting in a 44% decrease in the indication for chemotherapy.

Real-world analysis of clinical and economic impact of 21-gene recurrence score (RS) testing in early-stage breast cancer (ESBC) in Ireland

PURPOSE

Results from TAILOR-X suggest that up to 70% of hormone receptor-positive (HR+) node-negative (N0) ESBC patients (pts) may avoid chemotherapy (CT) with RS ≤ 25. We assess clinical and economic impacts of RS testing on treatment using real-world data.

METHODS

From October 2011 to February 2019, a retrospective, cross-sectional observational study was conducted of HR+ N0 ESBC pts who had RS testing in Ireland. Pts were classified low risk (RS ≤ 25) and high risk (RS > 25). Clinical risk was calculated. Data were collected via electronic patient records. Cost data were supplied by the National Healthcare Pricing Regulatory Authority.

RESULTS

963 pts. Mean age is 56 years. Mean tumour size is 1.7 cm. 114 (11.8%), 635 (66%), 211 (22%), 3 (0.2%) pts had G1, G2, G3 and unknown G, respectively. 796 pts (82.8%) low RS, 159 (16.5%) high RS and 8 pts (0.7%) unknown RS. 263 pts (26%) were aged ≤ 50 at diagnosis; 117 (45%) had RS 0-15, 63 (24.5%) 16-20, 39 (15.3%) 21-25 and 40 (15.2%) RS 26-100. 4 pts (1.5%) had unknown RS. Post-RS testing, 602 pts (62.5%) had a change in CT decision; 593 changed to hormone therapy (HT) alone. In total, 262 pts received CT. Of pts receiving CT; 138 (53%) had RS > 25, 124 (47%) had RS ≤ 25. Of pts aged ≤ 50, 153 (58%) had high clinical risk, of whom 28 had RS 16-20. Assay use achieved a 62.5% change in treatment with 73% of pts avoiding CT. This resulted in savings of €4 million in treatment costs. Deducting assay costs, savings of €1.9 million were achieved.

CONCLUSION

Over the 8 years of the study, a 62.5% reduction in CT use was achieved with savings of over €1,900,000.

Clinicopathological correlates, oncological impact, and validation of Oncotype DX™ in a European Tertiary Referral Centre

Oncotype DX™ (ODX) score estimates prognosis and predicts breast cancer recurrence. It also individualizes patient adjuvant chemotherapy prescription in breast cancer. This assay relies on genetic and molecular markers; the clinicopathological phenotype of which are tested routinely. The aim of this study was determine whether clinicopathological and immunohistochemical information predicts ODX recurrence score (RS). Secondly, to assess the impact on adjuvant chemotherapy (AC) and oncological outcome of ODX testing in patients in a European tertiary referral center. Estrogen receptor positive (ER+), human epidermal growth factor receptor-2 negative (HER2-), lymph node negative (LN-), and female breast cancer patients with ODX testing performed between 2007 and 2015 were categorized into low- (<11), intermediate- (11-25), and high-risk (>25) groups. Clinicopathological and immunohistochemical correlates of RS were determined. Predictors of RS were assessed using binary logistic regression. Oncological outcome was assessed using Kaplan-Meier and Cox regression analyses. ODX was performed in 400 consecutive ER+LN- patients. Median follow-up was 74.1 months (3.0-144.4). Low grade (odds ratio [OR]:2.39; 95% confidence interval [CI]:1.04-5.51, p = 0.041) independently predicted low ODX, while high grade (OR:2.04; 95% CI: 1.19-3.49, p = 0.009) and reduced progesterone receptor (PgR) expression (OR: 2.57, 95% CI: 1.42-4.65, p = 0.002) independently predicted high ODX. Omission of AC in intermediate- (p = 0.159) and high-risk (p = 0.702) groups did not negatively impact survival. In conclusion, tumor grade independently predicts low and high RS, while PgR negativity predicts high RS. ODX reduced AC prescription without compromising oncological outcome.

TissueCypher Barrett's esophagus assay impacts clinical decisions in the management of patients with Barrett's esophagus

Background and study aims  The TissueCypher Barrett's Esophagus Assay is a novel tissue biomarker test, and has been validated to predict progression to high-grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) in patients with Barrett's esophagus (BE). The aim of this study was to evaluate the impact of TissueCypher on clinical decision-making in the management of BE. Patients and methods  TissueCypher was ordered for 60 patients with non-dysplastic (ND, n = 18) BE, indefinite for dysplasia (IND, n = 25), and low-grade dysplasia (LGD, n = 17). TissueCypher reports a risk class (low, intermediate or high) for progression to HGD or EAC within 5 years. The impact of the test results on BE management decisions was assessed. Results  Fifty-two of 60 patients were male, mean age 65.2 ± 11.8, and 43 of 60 had long segment BE. TissueCypher results impacted 55.0 % of management decisions. In 21.7 % of patients, the test upstaged the management approach, resulting in endoscopic eradication therapy (EET) or shorter surveillance interval. The test downstaged the management approach in 33.4 % of patients, leading to surveillance rather than EET. In the subset of patients whose management plan was changed, upstaging was associated with a high-risk TissueCypher result, and downstaging was associated with a low-risk result ( P  < 0.0001). Conclusions  TissueCypher was used as an adjunct to support a surveillance-only approach in 33.4 % of patients. Upstaging occurred in 21.7 % of patients, leading to therapeutic intervention or increased surveillance. These results indicate that the TissueCypher test may enable physicians to target EET for TissueCypher high-risk BE patients, while reducing unnecessary procedures in TissueCypher low-risk patients.

Identification and Complete Validation of Prognostic Gene Signatures for Human Papillomavirus-Associated Cancers: Integrated Approach Covering Different Anatomical Locations

Human papillomavirus (HPV) infects squamous epithelium and is a major cause of cervical cancer (CC) and a subset of head and neck cancers (HNC). Virus-induced tumorigenesis, molecular alterations, and related prognostic markers are expected to be similar between the two cancers, but they remain poorly understood. We present integrated molecular analysis of HPV-associated tumors from TCGA and GEO databases and identify prognostic biomarkers. Analysis of gene expression profiles identified common upregulated genes and pathways of DNA replication and repair in the HPV-associated tumors. We established 34 prognostic gene signatures with a universal cutoff value in TCGA-CC using Elastic Net Cox regression analysis. We were able to externally validate our results in the TCGA-HNC and several GEO data sets, and demonstrated prognostic power in HPV-associated HNC, but not in HPV-negative cancers. The HPV-related prognostic and predictive indicator did not discriminate other cancers, except bladder urothelial carcinoma. These results identify and completely validate a highly selective prognostic system and its cross-usefulness in HPV-associated cancers, regardless of the tumor's anatomical subsite.IMPORTANCE Persistent infection with high-risk HPV interferes with cell function regulation and causes cell mutations, which accumulate over the long term and eventually develop into cancer. Results of pathway enrichment analysis presumably showed this accumulation of intracellular damage during the chronic HPV-infected state. We used highly advanced statistical methods to identify the most appropriate genes and coefficients and developed the HPV-related prognostic and predictive indicator (HPPI) risk scoring system. We applied the same cutoff value to training and validation sets and demonstrated good prognostic performance in both data sets, and confirmed a consistent trend in external validation. Moreover, HPPI presented significant validation results for bladder cancer suspected to be related to HPV. This suggested that our risk scoring system based on the prognostic gene signature could play an important role in the development of treatment strategies for patients with HPV-related cancer.

The Level of Agreement Among Medical Oncologists on Adjuvant Chemotherapy Decision for Breast Cancer in Pre and Post-Oncotype DX Settings

INTRODUCTION

The Oncotype DX assay plays an important role in the identification of the specific subset of hormone receptor (HR)-positive and node-negative breast cancer (BC) patients, who would benefit the most from adjuvant chemotherapy. The current study aimed at assessing the level of agreement among medical oncologists on adjuvant chemotherapy decisions before and after Oncotype DX, as well as the intra-observer agreement of each medical oncologist's decision of prescribing adjuvant chemotherapy based on clinicopathological and immunohistochemical parameters only and followed by Oncotype DX recurrence score (RS) results.

METHODS

A retrospective analysis of data related to clinicopathological and immunohistochemical parameters, and Oncotype DX RS result for 145 female, estrogen receptor (ER)-positive, HER2 negative, and both node-negative and positive BC patients was performed. Initially, the data without Oncotype DX RS was sent to 16 oncologists in multiple centers in the Middle East. After one week, the same data with the shuffling of cases were sent to the oncologists with the addition of the Oncotype DX RS result for each patient. The inter and intra-observer agreement (kappa and Fleiss multi-rater kappa) among oncologists' decision of prescribing adjuvant chemotherapy pre and post-Oncotype DX RS results were assessed. Oncotype DX risk scores were used as continuous variables as well as based on old RS grouping, categorized into low (0-17), intermediate (18-30), and high risk (≥ 31) groups. A test with a p-value of < 0 .05 will be considered statistically significant.

RESULTS

The mean age ± SD of the cohort was 51.9 ± 9.4 years. Sixty-nine patients (47.6%) were premenopausal whereas 76 patients (52.4%) were postmenopausal. The mean Oncotype DX RS was 17.8 ± 8.6 and 54.5% had low recurrence risk (RR), 37.9% had intermediate RR and only 7.6% had high RR. The majority of our cases were grade two (53.1%) and T stage one (49%), whereas 29.7% had positive one to three lymph nodes. The addition of Oncotype DX results improved the agreement among oncologists' decision from fair to moderate (kappa = 0.52; p <0.001). On average, an oncologist's decision of prescribing adjuvant chemotherapy pre and post-Oncotype DX had an agreement in 70.6% of the cases, with agreement observed mostly for cases where the initial decision of adjuvant chemotherapy was (no) and it was retained with post-Oncotype DX assay (46.1%), compared to 24.5% cases where the initial decision was (yes) and it was retained with post-Oncotype DX assay (kappa = 0.39; p <0.001). The addition of the Oncotype DX RS result avoided chemotherapy in 20.4% of cases and identified 9% of cases as candidates for adjuvant chemotherapy (kappa = 0.38; p <0.001). The disagreement was highest among cases with intermediate RR (33.6%) followed by high and low RR (31.3% and 21.6%) with a statistical significance of <0.001.

CONCLUSION

We conclude that the Oncotype DX RS significantly influenced the decision to prescribe adjuvant chemotherapy among HR-positive, HER2 negative, and both node-negative and positive patients, as it increased the level of agreement among oncologists and led to a decrease in the use of adjuvant chemotherapy compared to the pre-Oncotype recommendations.

Targeting RLIP with CRISPR/Cas9 controls tumor growth

Breast cancer (BC) remains one of the major causes of cancer deaths in women. Over half of all BCs carry genetic defects in the gene encoding p53, a powerful tumor suppressor. P53 is known as the 'guardian of the genome' because it is essential for regulating cell division and preventing tumor formation. Ral-interacting protein (RLIP) is a modular protein capable of participating in many cellular functions. Blocking this stress-responsive protein, which is overexpressed during malignancy, enables BC cells to overcome the deleterious effects of p53 loss more effectively. In the clustered regularly interspaced short palindromic repeats/CRISPR-associated protein (CRISPR/Cas9) system, a single-guide RNA (sgRNA) recognizes a specific DNA sequence and directs the endonuclease Cas9 to make a double-strand break, which enables editing of targeted genes. Here, we harnessed CRISPR/Cas9 technology to target the RLIP gene in BC cells. We screened sgRNAs using a reporter system and lentivirally delivered them, along with Cas9, to BC cells for validation. We then assessed the survival, proliferation, and tumorigenicity of BC cells in vitro and the growth of tumors in vivo after CRISPR-mediated knockdown of RLIP. Doxycycline-inducible expression of Cas9 in BC cells transduced with lentiviral vectors encoding the sgRNAs disrupted the RLIP gene, leading to inhibition of BC cell proliferation both in vitro and in vivo, with resected tumors showing reduced levels of the survival and proliferation markers Ki67, RLIP, pAkt, and survivin, the cell cycle protein CDK4, and the mesenchymal marker vimentin, as well as elevated levels of the differentiation protein E-cadherin and pro-apoptotic protein Bim. Inducible Cas9/sgRNA-transduced BC cells without doxycycline treatment did not exhibit altered cell survival or proliferation in vitro or in vivo. Our study provides proof-of-concept that the CRISPR/Cas9 system can be utilized to target RLIP in vitro and in vivo.

PELP-1 regulates adverse responses to endocrine therapy in Estrogen Receptor (ER) positive breast cancer

Introduction: Endocrine therapy has played an important role in the management of ER positive breast cancer over recent decades. Despite this, not all patients respond equally to endocrine intervention, which can lead to resistance, associated disease relapse and progression. Previous reports suggest that endocrine agents themselves may induce an invasive phenotype in ER positive breast cancers with low/aberrant expression of E-cadherin. Here we investigate this phenomenon further and provide data supporting a role for the ER co-receptor, PELP-1, in mediating an adverse response to endocrine agents.

Materials and Methods: The effects of tamoxifen, fulvestrant and estrogen withdrawal (as a model for aromatase inhibitor therapy) on the invasive and migratory capacity of endocrine-sensitive MCF-7 and T47D cells, in the presence or absence of functional E-cadherin and/or PELP-1 (using siRNA knockdown), was assessed via Matrigel invasion and Boyden chamber migration assays. The effects of these endocrine therapies alongside E-cadherin/PELP-1 modulation on cell proliferation were further assessed by MTT assay. Western blotting using phospho-specific antibodies was performed to investigate signalling pathway changes associated with endocrine-induced changes in invasion and migration.

Results: Both tamoxifen and fulvestrant induced a pro-invasive and pro-migratory phenotype in ER positive breast cancer cells displaying a high basal expression of PELP-1, which was augmented in the context of poor cell-cell contact. This process occurred in a Src-dependent manner with Src inhibition reversing endocrine induced invasion/migration. While this adverse response was observed using both tamoxifen and fulvestrant therapy, it was not observed under conditions of estrogen withdrawal.

Conclusions: Our data confirms previous reports that anti-estrogens induce an adverse cell phenotype in ER+ breast cancer, particularly in the absence of homotypic cell contact. These results implicate E-cadherin and PELP-1 as potential biomarkers when deciding upon optimum adjuvant endocrine therapy, whereby tumours with high PELP-1/low E-cadherin expression may benefit from estrogen withdrawal therapy via aromatase inhibition, as opposed to ER modulation/antagonism.

Breast cancer, screening and diagnostic tools: All you need to know

Breast cancer is one of the most frequent malignancies among women worldwide. Methods for screening and diagnosis allow health care professionals to provide personalized treatments that improve the outcome and survival. Scientists and physicians are working side-by-side to develop evidence-based guidelines and equipment to detect cancer earlier. However, the lack of comprehensive interdisciplinary information and understanding between biomedical, medical, and technology professionals makes innovation of new screening and diagnosis tools difficult. This critical review gathers, for the first time, information concerning normal breast and cancer biology, established and emerging methods for screening and diagnosis, staging and grading, molecular and genetic biomarkers. Our purpose is to address key interdisciplinary information about these methods for physicians and scientists. Only the multidisciplinary interaction and communication between scientists, health care professionals, technical experts and patients will lead to the development of better detection tools and methods for an improved screening and early diagnosis.

Association of Circulating Tumor DNA With Disease-Free Survival in Breast Cancer: A Systematic Review and Meta-analysis

IMPORTANCE

Fragmented DNA is continuously released into the circulation following apoptosis and necrosis of both cancerous and noncancerous cells; when it is released by cancer cells, it is specifically known as circulating tumor DNA (ctDNA). Previous studies have suggested that ctDNA can reflect tumor burden and guide potential therapeutic targets.

OBJECTIVE

To determine the association of ctDNA with breast cancer disease-free survival (DFS) and progression-free survival in early, locally advanced, and metastatic breast cancer.

DATA SOURCES

An electronic search was conducted using the Cochrane Library, ScienceDirect, PubMed, and Embase from July 30, 2019, to October 31, 2019; all languages were included. The following search terms were used: ctDNA OR circulating tumor DNA OR liquid biopsy AND breast cancer OR breast carcinoma OR breast tumor AND prognosis OR survival. All titles were screened, and the appropriate abstracts were reviewed. If any data were missing, the authors contacted the study authors for permission to access data and extrapolate hazard ratios (HRs).

STUDY SELECTION

To be included in the analysis, the studies had to meet the following prespecified inclusion criteria: (1) a ctDNA blood sample was measured; (2) DFS, progression-free survival, or relapse-free survival was reported as an HR; and (3) the patient population only had breast cancer. Retrospective and prospective observational cohort studies were included.

DATA EXTRACTION AND SYNTHESIS

Two authors (C.C. and C.F.) independently reviewed the literature. All data were recorded independently by both authors and were compared at the end of the reviewing process to limit selection bias. Duplicates were removed and any disparities were clarified. Data were pooled using a fixed-effects or random-effects model according to the study heterogeneity. This study adhered to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) and Meta-Analysis of Observational Studies in Epidemiology (MOOSE).

MAIN OUTCOMES AND MEASURES

The primary outcome was the association of ctDNA with DFS or relapse-free survival in breast cancer. Secondary outcomes focused on subgroup analysis in the setting of early breast cancer and metastatic breast cancer.

RESULTS

From a total of 263 publications found using the predefined search terms, data from 8 studies (3.0%) reporting on 739 patients in total were suitable for inclusion. Circulating tumor DNA gene variation detection (both before and after treatment) was statistically significantly associated with shorter DFS (HR, 4.44; 95% CI, 2.29-8.61; P < .001). Detection of ctDNA was statistically significantly associated with a reduction in DFS in both the early breast cancer subgroup (HR, 8.32; 95% CI, 3.01-22.99; P < .001) and the metastatic or locally advanced subgroup (HR, 1.91; 95% CI, 1.35-2.71; P < .001). Pretreatment and posttreatment plasma sample collection was analyzed in both early and metastatic groups. The posttreatment group encompassed both surgical and oncologic therapy. Pretreatment plasma detection of ctDNA was statistically significantly associated with reduced DFS (HR, 3.30; 95% CI, 1.98-5.52; P < .001). Posttreatment sampling of ctDNA failed to achieve statistical significance (HR, 8.17; 95% CI, 1.01-65.89; P = .05).

CONCLUSIONS AND RELEVANCE

In this systematic review and meta-analysis, elevated plasma ctDNA was associated with a high risk of relapse. This finding suggests that plasma ctDNA may provide an excellent method to stratify risk and personalize patient follow-up.

Patient and physician factors associated with Oncotype DX and adjuvant chemotherapy utilization for breast cancer patients in New Hampshire, 2010-2016

BACKGROUND

Oncotype DX® (ODX) is used to assess risk of disease recurrence in hormone receptor positive, HER2-negative breast cancer and to guide decisions regarding adjuvant chemotherapy. Little is known about how physician factors impact treatment decisions. The purpose of this study was to examine patient and physician factors associated with ODX testing and adjuvant chemotherapy for breast cancer patients in New Hampshire.

METHODS

We examined New Hampshire State Cancer Registry data on 5630 female breast cancer patients diagnosed from 2010 to 2016. We performed unadjusted and adjusted hierarchical logistic regression to identify factors associated with a patient's receipt of ODX, being recommended and receiving chemotherapy, and refusing chemotherapy. We calculated intraclass correlation coefficients (ICCs) to examine the proportion of variance in clinical decisions explained by between-physician and between-hospital variation.

RESULTS

Over the study period, 1512 breast cancer patients received ODX. After adjustment for patient and tumor characteristics, we found that patients seen by a male medical oncologist were less likely to be recommended chemotherapy following ODX (OR = 0.50 (95% CI = 0.34-0.74), p < 0.01). Medical oncologists with more clinical experience (reference: less than 10 years) were more likely to recommend chemotherapy (20-29 years: OR = 4.05 (95% CI = 1.57-10.43), p < 0.01; > 29 years: OR = 4.48 (95% CI = 1.68-11.95), p < 0.01). A substantial amount of the variation in receiving chemotherapy was due to variation between physicians, particularly among low risk patients (ICC = 0.33).

CONCLUSIONS

In addition to patient clinicopathologic characteristics, physician gender and clinical experience were associated with chemotherapy treatment following ODX testing. The significant variation between physicians indicates the potential for interventions to reduce variation in care.

Patients' perceptions of 70-gene signature testing: commonly changing the initial inclination to undergo or forego chemotherapy and reducing decisional conflict

PURPOSE

Little is known about the impact of 70-gene signature (70-GS) use on patients' chemotherapy decision-making. The primary aim of this study was to evaluate the impact of 70-GS use on patients' decisions to undergo chemotherapy. The perceived decision conflict during decision-making was a secondary objective of the study.

METHODS

Patients operated for estrogen receptor positive early breast cancer were asked to fill out a questionnaire probing their inclination to undergo chemotherapy before deployment of the 70-GS test. After disclosure of the 70-GS result patients were asked about their decision regarding chemotherapy. Patients' decisional conflict was measured using the 16-item decisional conflict scale (DCS); scores < 25 are associated with a persuaded decision while a score > 37.5 implies that one feels unsure about a choice.

RESULTS

Between January 1th 2017 and December 31th 2018, 106 patients completed both questionnaires. Before deployment of the 70-GS, 58% of patients (n = 62) formulated a clear treatment preference, of whom 21 patients (34%) changed their opinion on treatment with chemotherapy following the 70-GS. The final decision regarding chemotherapy was in line with the 70-GS result in 90% of patients. The percentage of patients who felt unsure about their preference to be treated with chemotherapy decreased from 42 to 5% after disclosure of the 70-GS. The mean total DCS significantly decreased from pre-test to post-test from 35 to 23, irrespective of the risk estimate (p < 0.001).

CONCLUSION

Deployment of the 70-GS changed patients' inclination to undergo adjuvant chemotherapy in one third of patients and decreased patients' decisional conflict.

Clinicopathological characteristics, adjuvant chemotherapy decision and disease outcome in patients with breast cancer with a 21-gene recurrence score of 26-30

Recurrence score (RS) could be used to predict clinical outcomes and chemotherapy efficacy in patients with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative and lymph node-negative breast cancer. However, the clinical features and management of patients with an RS of 26–30 are not completely understood. In the present study, 783 patients with HR⁺/HER2⁻, lymph node-negative early breast cancer and RS ≥18 were included and categorized into RS=18−25 (47.8%), 26–30 (25.5%) or ≥31 (26.7%) groups. Clinicopathological characteristics, adjuvant chemotherapy usage and disease outcomes were compared. Alterations in the adjuvant chemotherapy recommendation after 21-gene RS testing were also analyzed. The results indicated that patients with RS=26−30 had higher progesterone receptor (PR) expression [odds ratio (OR)=2.84; P<0.001] and lower Ki-67 index (OR, 1.88; P=0.032) compared with patients with RS ≥31. Multivariate analysis demonstrated that age ≤50 years (OR, 5.75; P=0.001) and luminal-B subtype (OR, 7.75; P<0.001) were factors that were independently associated with chemotherapy usage in the RS=26−30 group. Among 104 patients who were not recommended chemotherapy before 21-gene RS testing, the treatment decision for 52 patients was changed to recommend chemotherapy once an RS of 26–30 was identified. The patient adherence rate to the treatment recommendation was 95.0% (190/200). After a median follow-up of 21.5 months, 6 patients displayed disease recurrence in the RS=26−30 group, and there was no significant difference between patients receiving chemotherapy and patients not receiving chemotherapy. In conclusion, patients with RS=26−30 had tumors with higher PR expression and lower Ki-67 index compared with those of patients with RS ≥31. Age, luminal subtype and RS testing influenced chemotherapy usage in patients with RS=26−30; however, no significant benefit from adjuvant chemotherapy was observed in a short term of 2 years.

A Machine Learning Platform to Optimize the Translation of Personalized Network Models to the Clinic

PURPOSE

Dynamic network models predict clinical prognosis and inform therapeutic intervention by elucidating disease-driven aberrations at the systems level. However, the personalization of model predictions requires the profiling of multiple model inputs, which hampers clinical translation.

PATIENTS AND METHODS

We applied APOPTO-CELL, a prognostic model of apoptosis signaling, to showcase the establishment of computational platforms that require a reduced set of inputs. We designed two distinct and complementary pipelines: a probabilistic approach to exploit a consistent subpanel of inputs across the whole cohort (Ensemble) and a machine learning approach to identify a reduced protein set tailored for individual patients (Tree). Development was performed on a virtual cohort of 3,200,000 patients, with inputs estimated from clinically relevant protein profiles. Validation was carried out in an in-house stage III colorectal cancer cohort, with inputs profiled in surgical resections by reverse phase protein array (n = 120) and/or immunohistochemistry (n = 117).

RESULTS

Ensemble and Tree reproduced APOPTO-CELL predictions in the virtual patient cohort with 92% and 99% accuracy while decreasing the number of inputs to a consistent subset of three proteins (40% reduction) or a personalized subset of 2.7 proteins on average (46% reduction), respectively. Ensemble and Tree retained prognostic utility in the in-house colorectal cancer cohort. The association between the Ensemble accuracy and prognostic value (Spearman ρ = 0.43; P = .02) provided a rationale to optimize the input composition for specific clinical settings. Comparison between profiling by reverse phase protein array (gold standard) and immunohistochemistry (clinical routine) revealed that the latter is a suitable technology to quantify model inputs.

CONCLUSION

This study provides a generalizable framework to optimize the development of network-based prognostic assays and, ultimately, to facilitate their integration in the routine clinical workflow.

Multigene testing in breast cancer: What have we learned from the 21-gene recurrence score assay?

Most invasive breast cancers express hormone receptors (HR) and typically have a favorable prognosis following endocrine therapy. Patients at a higher risk of recurrence can be identified by multigene prognostic classifiers such as the 21-gene recurrence score (RS) assay, 70-gene prognostic signature, PAM-50, 12-gene molecular score, and others. The 21-gene RS assay (Oncotype Dx™, Genomic Health, Redwood City, CA) has level I clinical evidence and is the most widely used multigene assay in North America. The RS assay is based on reverse transcriptase polymerase chain reaction that can be performed on the RNA isolated from formalin-fixed paraffin-embedded tissue. It evaluates the expression of 16 cancer-related genes developed based on a multi-step approach. Due to its ability to assess recurrence risk and predict potential benefit from chemotherapy, the assay is recommended for patients with node-negative, HR-positive, and human epidermal growth factor receptor 2 (HER2)-negative breast cancer by the American Society of Clinical Oncology, National Comprehensive Cancer Network clinical practice guidelines in oncology, European Society for Medical Oncology clinical practice guidelines, and St. Gallen consensus panel guidelines. The RS assay has also been incorporated in the prognostic stage groups in the 8th edition of the American Joint Commission of Cancer staging manual in order to provide essential genomic information for optimal treatment decisions. This review will focus on the utility of the RS assay in HR-positive and HER2-negative breast cancer patients, including risk of distant and locoregional recurrence in node-negative and node-positive tumors, association with radiotherapy, special subtypes of breast cancer, practical issues related to selecting tumors for testing, and overview of the recently published TailorX (Trial Assigning IndividuaLized Options for treatment [Rx]) results.

EndoPredict® in early hormone receptor-positive, HER2-negative breast cancer

Purpose

Evaluating consecutive early breast cancer patients, we analyzed both the impact of EndoPredict^® on clinical decisions as well as clinico-pathological factors influencing the decision to perform this gene expression test.

Methods

Hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative early breast cancer patients treated between 2011 and 2016 were included in this study to investigate the role of EndoPredict^® (EPclin) in the treatment of early breast cancer. A main study aim was to analyze the changes in therapy recommendations with and without EPclin. In addition, the impact of clinico-pathological parameters for the decision to perform EPclin was examined by Pearson's chi-squared test (χ²-test) and Fisher's exact test as well as univariate and multivariate logistic regressions.

Results

In a cohort of 869 consecutive early HR-positive, HER-negative breast cancer patients, EPclin was utilized in 156 (18.0%) patients. EPclin led to changes in therapy recommendations in 33.3% (n = 52), with both therapy escalation in 19.2% (n = 30) and de-escalation in 14.1% (n = 22). The clinico-pathological factors influencing the use of EPclin were age (P < 0.001, odds ratio [OR] 0.498), tumor size (P = 0.011, OR 0.071), nodal status (P = 0.021, OR 1.674), histological grade (P = 0.043, OR 0.432), and Ki-67 (P < 0.001, OR 3.599).

Conclusions

EPclin led to a change in therapy recommendations in one third of the patients. Clinico-pathological parameters such as younger age, smaller tumor size, positive nodal status, intermediate histological grade and intermediate Ki-67 had a significant influence on the use of EndoPredict^®.

Electronic supplementary material

The online version of this article (10.1007/s10549-020-05688-1) contains supplementary material, which is available to authorized users.