Use of Biomarkers to Guide Decisions on Adjuvant Systemic Therapy for Women With Early-Stage Invasive Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline

Radiomics Nomogram Based on Dual-Sequence MRI for Assessing Ki-67 Expression in Breast Cancer

BACKGROUND

Radiomics has been extensively applied in predicting Ki-67 in breast cancer (BC). However, this is often confined to the exploration of a single sequence, without considering the varying sensitivity and specificity among different sequences.

PURPOSE

To develop a nomogram based on dual-sequence MRI derived radiomic features combined with clinical characteristics for assessing Ki-67 expression in BC.

STUDY TYPE

Retrospective.

POPULATION

227 females (average age, 51 years) with 233 lesions and pathologically confirmed BC, which were divided into the training set (n = 163) and test set (n = 70).

FIELD STRENGTH/SEQUENCE

3.0-T, T1-weighted dynamic contrast-enhanced MRI (DCE-MRI) and apparent diffusion coefficient (ADC) maps from diffusion-weighted MRI (EPI sequence).

ASSESSMENT

The regions of interest were manually delineated on ADC and DCE-MRI sequences. Three radiomics models of ADC, DCE-MRI, and dsMRI (combined ADC and DCE-MRI sequences) were constructed by logistic regression and the radiomics score (Radscore) of the best model was calculated. The correlation between Ki-67 expression and clinical characteristics such as receptor status, axillary lymph node (ALN) metastasis status, ADC value, and time signal intensity curve was analyzed, and the clinical model was established. The Radscore was combined with clinical predictors to construct a nomogram.

STATISTICAL TESTS

The independent sample t-test, Mann-Whitney U test, Chi-squared test, Interclass correlation coefficients (ICCs), single factor analysis, least absolute shrinkage and selection operator (LASSO), logistic regression, receiver operating characteristics, Delong test, Hosmer_Lemeshow test, calibration curve, decision curve. A P-value <0.05 was considered statistically significant.

RESULTS

In the test set, the prediction efficiency of the dsMRI model (AUC = 0.862) was higher than ADC model (AUC = 0.797) and DCE-MRI model (AUC = 0.755). With the inclusion of estrogen receptor (ER) and ALN metastasis, the nomogram displayed quality improvement (AUC = 0.876), which was superior to the clinical model (AUC = 0.787) and radiomics model.

DATA CONCLUSION

The nomogram based on dsMRI radiomic features and clinical characteristics may be able to assess Ki-67 expression in BC.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 3.

Nonlinear Mixed-Effects Model of Z-Endoxifen Concentrations in Tamoxifen-Treated Patients from the CEPAM Cohort

Tamoxifen is widely used in patients with hormone receptor-positive breast cancer. The polymorphic enzyme CYP2D6 is primarily responsible for metabolic activation of tamoxifen, resulting in substantial interindividual variability of plasma concentrations of its most important metabolite, Z-endoxifen. The Z-endoxifen concentration thresholds below which tamoxifen treatment is less efficacious have been proposed but not validated, and prospective trials of individualized tamoxifen treatment to achieve Z-endoxifen concentration thresholds are considered infeasible. Therefore, we aim to validate the association between Z-endoxifen concentration and tamoxifen treatment outcomes, and identify a Z-endoxifen concentration threshold of tamoxifen efficacy, using pharmacometric modeling and simulation. As a first step, the CYP2D6 Endoxifen Percentage Activity Model (CEPAM) cohort was created by pooling data from 28 clinical studies (> 7,000 patients) with measured endoxifen plasma concentrations. After cleaning, data from 6,083 patients were used to develop a nonlinear mixed-effect (NLME) model for tamoxifen and Z-endoxifen pharmacokinetics that includes a conversion factor to allow inclusion of studies that measured total endoxifen but not Z-endoxifen. The final parent-metabolite NLME model confirmed the primary role of CYP2D6, and contributions from body weight, CYP2C9 phenotype, and co-medication with CYP2D6 inhibitors, on Z-endoxifen pharmacokinetics. Future work will use the model to simulate Z-endoxifen concentrations in patients receiving single agent tamoxifen treatment within large prospective clinical trials with long-term survival to identify the Z-endoxifen concentration threshold below which tamoxifen is less efficacious. Identification of this concentration threshold would allow personalized tamoxifen treatment to improve outcomes in patients with hormone receptor-positive breast cancer.

Cancer treatments: Past, present, and future

There is a rich history of cancer treatments which provides a number of important lessons for present and future cancer therapies. We outline this history by looking in the past, reviewing the current landscape of cancer treatments, and by glancing at the potential future cancer therapies.

Potential Impact of Subphenotyping in Pharmacologic Management of Acute Respiratory Distress Syndrome

Background: Acute respiratory distress syndrome (ARDS) is an acute inflammatory process in the lungs associated with high morbidity and mortality. Previous research has studied both nonpharmacologic and pharmacologic interventions aimed at targeting this inflammatory process and improving ventilation. Hypothesis: To date, only nonpharmacologic interventions including lung protective ventilation, prone positioning, and high positive end-expiratory pressure ventilation strategies have resulted in significant improvements in patient outcomes. Given the high mortality associated with ARDS despite these advancements, interest in subphenotyping has grown, aiming to improve diagnosis and develop personalized treatment approaches. Data Collection: Previous trials evaluating pharmacologic therapies in heterogeneous populations have primarily demonstrated no positive effect, but hope to show benefit when targeting specific subphenotypes, thus increasing their efficacy, while simultaneously decreasing adverse effects. Results: Although most studies evaluating pharmacologic therapies for ARDS have not demonstrated a mortality benefit, there is limited data evaluating pharmacologic therapies in ARDS subphenotypes, which have found promising results. Neuromuscular blocking agents, corticosteroids, and simvastatin have resulted in a mortality benefit when used in patients with the hyper-inflammatory ARDS subphenotype. Therapeutic Opinion: The use of subphenotyping could revolutionize the way ARDS therapies are applied and therefore improve outcomes while also limiting the adverse effects associated with their ineffective use. Future studies should evaluate ARDS subphenotypes and their response to pharmacologic intervention to advance this area of precision medicine.

An original study assessing biomarker success rate in breast cancer recurrence biomarker research

BACKGROUND

Breast cancer is the second most common cause of cancer mortality worldwide. Biomarker discovery has led to advances in understanding molecular phenotyping and thus has a great potential for precision management of this diverse disease. Despite increased interest in the biomarker field, only a small number of breast cancer biomarkers are known to be clinically useful. Therefore, it is very important to characterise the success rate of biomarkers in this field and study potential reasons for the deficit. We therefore aim to achieve quantitative characterisation of the biomarker translation gap by tracking the progress of prognostic biomarkers associated with breast cancer recurrence.

METHODS

An electronic systematic search was conducted in Medline and Embase databases using keywords and mesh headings associated with breast cancer recurrence biomarkers (1940-2023). Abstracts were screened, and primary clinical studies involving breast cancer recurrence biomarkers were selected. Upon identification of relevant literature, we extracted the biomarker name, date of publication and journal name. All analyses were performed using IBM SPSS Statistics and GraphPad prism (La Jolla, California, USA).

RESULTS

A total of 19,195 articles were identified, from which 4597 articles reported breast cancer biomarkers associated with recurrence. Upon data extraction, 2437 individual biomarkers were identified. Out of these, 23 are currently recommended for clinical use, which corresponds to only 0.94% of all discovered biomarkers.

CONCLUSIONS

This study characterised for the first time the translational gap in the field of recurrence-related breast cancer biomarkers, indicating that only 0.94% of identified biomarkers were recommended for clinical use. This denotes an evident barrier in the biomarker research field and emphasises the need for a clearer route from biomarker discovery through to implementation.

A PET-Surrogate Signature for the Interrogation of the Metabolic Status of Breast Cancers

Metabolic alterations in cancers can be exploited for diagnostic, prognostic, and therapeutic purposes. This is exemplified by 18F-fluorodeoxyglucose (FDG)-positron emission tomography (FDG-PET), an imaging tool that relies on enhanced glucose uptake by tumors for diagnosis and staging. By performing transcriptomic analysis of breast cancer (BC) samples from patients stratified by FDG-PET, a 54-gene signature (PETsign) is identified that recapitulates FDG uptake. PETsign is independently prognostic of clinical outcome in luminal BCs, the most common and heterogeneous BC molecular subtype, which requires improved stratification criteria to guide therapeutic decision-making. The prognostic power of PETsign is stable across independent BC cohorts and disease stages including the earliest BC stage, arguing that PETsign is an ab initio metabolic signature. Transcriptomic and metabolomic analysis of BC cells reveals that PETsign predicts enhanced glycolytic dependence and reduced reliance on fatty acid oxidation. Moreover, coamplification of PETsign genes occurs frequently in BC arguing for their causal role in pathogenesis. CXCL8 and EGFR signaling pathways feature strongly in PETsign, and their activation in BC cells causes a shift toward a glycolytic phenotype. Thus, PETsign serves as a molecular surrogate for FDG-PET that could inform clinical management strategies for BC patients.

Searching for the "Holy Grail" of breast cancer recurrence risk: a narrative review of the hunt for a better biomarker and the promise of circulating tumor DNA (ctDNA)

BACKGROUND

This paper is a narrative review of a major clinical challenge at the heart of breast cancer care: determining which patients are at risk of recurrence, which require systemic therapy, and which remain at risk in the survivorship phase of care despite initial therapy.

METHODS

We review the literature on prognostic and predictive biomarkers in breast cancer with a focus on detection of minimal residual disease.

RESULTS

While we have many tools to estimate and refine risk that are used to individualize local and systemic therapy, we know that we continue to over treat many patients and undertreat others. Many patients also experience what is, at least in hindsight, needless fear of recurrence. In this review, we frame this dilemma for the practicing breast oncologist and discuss the search for what we term the "holy grail" of breast cancer evaluation: the ideal biomarker of residual distant disease. We review the history of attempts to address this problem and the up-to-date science on biomarkers, circulating tumor cells and circulating tumor DNA (ctDNA).

CONCLUSION

This review suggests that the emerging promise of ctDNA may help resolve a crticical dilemma at the heart of breast cancer care, and improve prognostication, treatment selection, and outcomes for patients with breast cancer.

Validation of CTS5 Model in Large-scale Breast Cancer Population and Combination of CTS5 and Ki-67 Status to Develop a Novel Nomogram for Prognosis Prediction

BACKGROUND

More than half of patients with early-stage estrogen receptor-positive (ER+) breast cancer relapse after completing 5 years of adjuvant endocrine therapy, so it is important to determine which patients are candidates for extended endocrine therapy. The clinical treatment score after 5 years (CTS5) is a prognostic tool developed based on postmenopausal ER+ breast cancer to assess the risk of late distant recurrence (LDR) after 5 years of adjuvant endocrine therapy for breast cancer. We aimed to externally validate the prognostic value of CTS5 in premenopausal and postmenopausal patients and combined with Ki-67 to develop a new model to improve the ability of prognosis prediction.

METHODS

We included a total of 516 patients with early-stage ER+ breast cancer who had received 5 years of adjuvant endocrine therapy and were recurrence-free for 5 years after surgery. According to menopausal status, we divided the study population into 2 groups: premenopausal and postmenopausal women. The CTS5 of each patient was calculated using a previously published formula, and the patients were divided into low, intermediate, and high CTS5 risk groups according to their CTS5 values. Based on the results of the univariate analysis ( P <0.01), a multivariate COX proportional hazards regression analysis was conducted to establish a nomogram with significant variables ( P <0.05). The discriminative power and accuracy of the nomograms were assessed using the concordance index (C-index), calibration curve, and area under the time-dependent receiver operating characteristic curve. Discrimination and calibration were evaluated by bootstrapping 1000 times. Finally, we utilized decision curve analysis to assess the performance of our novel predictive model in comparison to the CTS5 scoring system with regard to their respective benefits and advantages.

RESULTS

The median follow-up time was 7 years (6 to 9 years). The 516 women were categorized by CTS5 as follows: 246(47.7%) low risk, 179(34.7%) intermediate risk, and 91(17.6%) high risk. Using the CTS5 score as a continuous variable, patients' risk score was significantly positively associated with recurrence risk in both premenopausal and postmenopausal subgroups. For HER2- premenopausal patients and HER2+ postmenopausal patients, the CTS5 score was positively correlated with LDR risk. Patients with a Ki-67≥20% had a higher risk of LDR regardless of menopausal status. Using the CTS5 score as a categorical variable, the high-risk group of HER2- premenopausal patients had a higher risk of LDR. However, the CTS5 model could not distinguish the risk of LDR in different risk groups for HER2+ postmenopausal patients. In the high-risk group, patients with Ki-67≥20% had a higher risk of LDR, regardless of menopausal status. We developed a new nomogram model by combining the CTS5 model with Ki-67 levels. The C-indexes premenopausal and postmenopausal cohorts were 0.731 and 0.713, respectively. The nomogram model was well calibrated, and the time-dependent ROC curves indicated good specificity and sensitivity. Furthermore, decision curve analysis demonstrated that the new model had a wider and practical range of threshold probabilities, resulting in an increased net benefit compared with the CTS5 model.

CONCLUSIONS

Our study demonstrated that the CTS5 model can effectively predict the risk of LDR in early-stage ER+ breast cancer patients in both premenopausal and postmenopausal patients. Extended endocrine therapy is recommended for patients with Ki-67≥20% in the CTS5 high-risk group, as well as premenopausal patients with HER2-. Compared with CTS5, the new nomogram model has better identification and calibration capabilities, and further research is required to validate its efficacy in large-scale, multicenter, and prospective studies.

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

BACKGROUND AND PURPOSE

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

PATIENTS AND METHODS

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

RESULTS

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

INTERPRETATION

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

Caveolin-1 gene expression provides additional prognostic information combined with PAM50 risk of recurrence (ROR) score in breast cancer

Combining information from the tumor microenvironment (TME) with PAM50 Risk of Recurrence (ROR) score could improve breast cancer prognostication. Caveolin-1 (CAV1) is a marker of an active TME. CAV1 is a membrane protein involved in cell signaling, extracellular matrix organization, and tumor-stroma interactions. We sought to investigate CAV1 gene expression in relation to PAM50 subtypes, ROR score, and their joint prognostic impact. CAV1 expression was compared between PAM50 subtypes and ROR categories in two cohorts (SCAN-B, n = 5326 and METABRIC, n = 1980). CAV1 expression was assessed in relation to clinical outcomes using Cox regression and adjusted for clinicopathological predictors. Effect modifications between CAV1 expression and ROR categories on clinical outcome were investigated using multiplicative and additive two-way interaction analyses. Differential gene expression and gene set enrichment analyses were applied to compare high and low expressing CAV1 tumors. All samples expressed CAV1 with the highest expression in the Normal-like subtype. Gene modules consistent with epithelial-mesenchymal transition (EMT), hypoxia, and stromal activation were associated with high CAV1 expression. CAV1 expression was inversely associated with ROR category. Interactions between CAV1 expression and ROR categories were observed in both cohorts. High expressing CAV1 tumors conferred worse prognosis only within the group classified as ROR high. ROR gave markedly different prognostic information depending on the underlying CAV1 expression. CAV1, a potential mediator between the malignant cells and TME, could be a useful biomarker that enhances and further refines PAM50 ROR risk stratification in patients with ROR high tumors and a potential therapeutic target.

Oncotype DX in Breast Cancer Management: Insights and Outcomes From the United Arab Emirates

Introduction Breast cancer remains the most significant cancer affecting women worldwide, with an increasing incidence, especially in developing regions. The introduction of genomic tests like Oncotype DX has revolutionized personalized treatment, allowing for more tailored approaches to therapy. This study focuses on the United Arab Emirates (UAE), where breast cancer is the leading cause of cancer-related deaths among women, aiming to assess the predictive accuracy of the Oncotype DX test in categorizing patients based on recurrence risk. Materials and methods A retrospective cohort study was conducted on 95 breast cancer patients diagnosed at Tawam Hospital between 2013 and 2017 who underwent Oncotype DX testing. Data on patient demographics, tumor characteristics, treatment details, and Oncotype DX scores were collected. Survival analysis was performed using the Kaplan-Meier method, with the chi-square goodness of fit test assessing the model's adequacy. Results The cohort's age range was 27-71 years, with a mean age of 50, indicating a significant concentration of cases in the early post-menopausal period. The Oncotype DX analysis classified 55 patients (57.9%) as low risk, 29 (30.5%) as medium risk, and 11 (11.6%) as high risk of recurrence. The majority, 73 patients (76.8%), did not receive chemotherapy, highlighting the test's impact on treatment decisions. The survival analysis revealed no statistically significant difference in recurrence rates across the Oncotype DX risk categories (p = 0.268231). Conclusion The Oncotype DX test provides a valuable genomic approach to categorizing breast cancer patients by recurrence risk in the UAE. While the test influences treatment decisions, particularly the use of chemotherapy, this study did not find a significant correlation between Oncotype DX risk categories and actual recurrence events. These findings underscore the need for further research to optimize the use of genomic testing in the UAE's diverse patient population and enhance personalized treatment strategies in breast cancer management.

Increased PI3K pathway activity is associated with recurrent breast cancer in patients with low and intermediate 21-gene recurrence score

AIMS

We investigated key signalling pathways' activity and mutational status of early-stage breast carcinomas with low and intermediate 21-gene recurrence score (RS) to identify molecular features that may predict recurrence.

METHODS

This is a retrospective case-control study of 18 patients with recurrent breast carcinoma with low and intermediate 21-gene RS (<25) and control group of 15 non-recurrent breast cancer patients. DNA and mRNA were extracted from tumour tissue. mRNA expression of genes involved in oestrogen receptor (ER), androgen receptor (AR), PI3K and MAPK signalling pathways was measured by real-time quantitative reverse transcription-qPCR (OncoSIGNal G4 test, InnoSIGN). Tumour mutational landscape was assessed by targeted DNA sequencing (Oncomine Precision Assay).

RESULTS

There were no statistical differences between the groups' demographic and clinicopathological characteristics. PI3K pathway showed significantly higher activity in cases compared with controls (p=0.0014). Receiver operating characteristic curve analysis showed an area under the curve of 0.79 for PI3K pathway activity in the prediction of recurrent disease in low and intermediate 21-gene RS breast cancer. There was no difference in ER, AR and MAPK pathway activity. PIK3CA alterations were the most common driver mutations, but no difference was found between the groups (p=0.46) and no association with PI3K pathway activity (p=0.86). Higher Ki67 gene expression was associated with recurrences (p=0.042) CONCLUSION: Increased PI3K pathway activity, independent of PIK3CA mutations, may play a role in the recurrence of early-stage breast cancer with low and intermediate 21-gene RS. Pathway analysis can help to identify high-risk patients in this setting.

Establishment of a prognostic model to predict chemotherapy response and identification of RAC3 as a chemotherapeutic target in bladder cancer

Cisplatin-based chemotherapy is considered the primary treatment option for patients with advanced bladder cancer (BCa). However, the objective response rate to chemotherapy is often unsatisfactory, leading to a poor 5-year survival rate. Furthermore, current strategies for evaluating chemotherapy response and prognosis are limited and inefficient. In this study, we aimed to address these challenges by establishing a chemotherapy response type gene (CRTG) signature consisting of 9 genes and verified the prognostic value of this signature using TCGA and GEO BCa cohorts. The risk scores based on the CRTG signature were found to be associated with advanced clinicopathological status and demonstrated favorable predictive power for chemotherapy response in the TCGA cohort. Meanwhile, tumors with high risk scores exhibited a tendency toward a "cold tumor" phenotype. These tumors showed a low abundance of T cells, CD8+ T cells and cytotoxic lymphocytes, along with a high abundance of cancer-associated fibroblasts. Moreover, they displayed higher mRNA levels of these immune checkpoints: CD200, CD276, CD44, NRP1, PDCD1LG2 (PD-L2), and TNFSF9. Furthermore, we developed a nomogram that integrated the CRTG signature with clinicopathologic risk factors. This nomogram proved to be a more effective tool for predicting the prognosis of BCa patients. Additionally, we identified Rac family small GTPase 3 (RAC3) as a biomarker in our model. RAC3 was found to be overexpressed in chemoresistant BCa tissues and enhance the chemotherapeutic resistance of BCa cells in vitro and in vivo by regulating the PAK1-ERK1/2 pathway. In conclusion, our study presents a novel CRTG model for predicting chemotherapy response and prognosis in BCa. We also highlight the potential of combining chemotherapy with immunotherapy as a promising strategy for chemoresistant BCa and that RAC3 might be a latent target for therapeutic intervention.

Understanding communication between patients and healthcare professionals regarding comprehensive biomarker testing in precision oncology: A scoping review

BACKGROUND

Precision oncology, using comprehensive biomarker testing (cBT) to inform individual cancer diagnosis, prognosis and treatment, includes increasingly complex technology and clinical data sets. People impacted by cancer (patients and caregivers) and healthcare professionals (HCPs) face distinct challenges in navigating the cBT and personalized treatment landscape. This review summarizes evidence regarding cBT-related communication between people impacted by cancer and HCPs and identifies important avenues for future research in precision oncology.

METHODS

A scoping review was conducted using records published in PubMed during January 2017-August 2022, focusing on the breadth of topics on patient-HCP communication and knowledge resources used by HCPs as guidance in cBT-related communication. Data were extracted from records meeting inclusion criteria, and findings were summarized according to main topics.

RESULTS

The search identified 287 unique records and data were extracted from 42 records, including nine from expert input. Most records originated from the United States included patients with different types of cancer, and oncologists were the main HCPs. Patients' motivation for undergoing cBT and receiving results was generally high in different settings. However, patients' understanding of cBT-related concepts was limited, and their knowledge and information preferences changed based on cBT implications and significance to family members. HCPs were valued by patients as a trusted source of information. Limited evidence was available on HCPs' information-seeking behavior and factors influencing cBT-related knowledge and confidence, often self-reported as insufficient.

CONCLUSIONS

Patient education by knowledgeable and confident HCPs, information management and a caring patient-HCP relationship communicating continuity of care regardless of cBT results are crucial to empower patients and shared decision-making in precision oncology. More data on the process and structure of cBT-related communication, distinction between and characterization of different timepoints of patient-HCP interactions are needed.

Comprehensive and Accurate Molecular Profiling of Breast Cancer through mRNA Expression of ESR1, PGR, ERBB2, MKI67, and a Novel Proliferation Signature

BACKGROUND

An accurate status determination of breast cancer biomarkers (ER, PR, HER2, Ki67) is crucial for guiding patient management. The "gold standard" for assessing these biomarkers in FFPE tissue is IHC, which faces challenges in standardization and exhibits substantial variability. In this study, we compare the concordance of a new commercial RT-qPCR kit with IHC in determining BC biomarker status.

METHODS

The performance was evaluated using 634 FFPE specimens, which underwent histological analysis in accordance with standard of care methods. HER2 2+ tumors were referred to ISH testing. An immunoreactive score of ≥2/12 was considered positive for ER/PR and 20% staining was used as a cut-off for Ki67 high/low score. RT-qPCR and results calling were performed according to the manufacturer's instructions.

RESULTS

High concordance with IHC was seen for all markers (93.2% for ER, 87.1% for PR, 93.9% for HER2, 77.9% for Ki67 and 80.1% for proliferative signature (assessed against Ki67 IHC)).

CONCLUSIONS

By assessing the concordance with the results obtained through IHC, we sought to demonstrate the reliability and utility of the kit for precise BC subtyping. Our findings suggest that the kit provides a highly precise and accurate quantitative assessment of BC biomarkers.

Tata Memorial Centre Evidence Based Management of Breast cancer

ABSTRACT

The incidence of breast cancer is increasing rapidly in urban India due to the changing lifestyle and exposure to risk factors. Diagnosis at an advanced stage and in younger women are the most concerning issues of breast cancer in India. Lack of awareness and social taboos related to cancer diagnosis make women feel hesitant to seek timely medical advice. As almost half of women develop breast cancer at an age younger than 50 years, breast cancer diagnosis poses a huge financial burden on the household and impacts the entire family. Moreover, inaccessibility, unaffordability, and high out-of-pocket expenditure make this situation grimmer. Women find it difficult to get quality cancer care closer to their homes and end up traveling long distances for seeking treatment. Significant differences in the cancer epidemiology compared to the west make the adoption of western breast cancer management guidelines challenging for Indian women. In this article, we intend to provide a comprehensive review of the management of breast cancer from diagnosis to treatment for both early and advanced stages from the perspective of low-middle-income countries. Starting with a brief introduction to epidemiology and guidelines for diagnostic modalities (imaging and pathology), treatment has been discussed for early breast cancer (EBC), locally advanced, and MBC. In-depth information on loco-regional and systemic therapy has been provided focusing on standard treatment protocols as well as scenarios where treatment can be de-escalated or escalated.

Discordance of Oncotype DX scores in synchronous bilateral and unilateral multifocal breast cancers

PURPOSE

Oncotype DX, a 21-gene expression profiling test, has become standard of care in the management of estrogen receptor (ER)-positive breast cancer. In multifocal tumors, it is unclear whether testing of the different foci is necessary. We evaluated the concordance of Oncotype DX recurrence scores (RS) between 2 tumor foci in synchronous bilateral or unilateral multifocal tumors and characterized pathological predictors of discordance.

METHODS

We reviewed 713 ER+, HER2- primary invasive breast cancer patients with Oncotype RS and identified 17 bilateral synchronous patients (34 tumors) and 13 unilateral multifocal patients (26 tumors) with available Oncotype RS on all foci. Discordance in Oncotype RS between synchronous tumors was recorded and associations with clinicopathologic features including tumor size, histology, Nottingham histologic grade, progesterone receptor staining, and Ki67 index were analyzed.

RESULTS

Bilateral synchronous tumors were present in older patients (median age 59 years) and had larger tumor (median size 17 mm) and more discordant histology (10/17, 59%) as compared to unilateral multifocal tumors (median age 49 years, p < 0.01; median tumor size 12 mm, p = 0.01; discordant histology 2/13, 15%, p = 0.03). Oncotype RS were discordant in 47% (8/17) of bilateral and 54% (7/13) of unilateral multifocal tumors. Concordant Oncotype RS was associated with similar histologic grade and Ki67 index in 78% (7/9) of bilateral and 100% (6/6) of multifocal tumors. In contrast, only 25% (2/8) of bilateral (p = 0.06) and 14% (1/7) of unilateral multifocal (p < 0.01) cases with discordant Oncotype RS had concordant histology grades and Ki67 levels. In synchronous tumors with discordant Oncotype RS and Ki67 index, all (4/4) foci with higher RS had higher Ki67 index.

CONCLUSION

Discordance of Oncotype RS is common in both bilateral and unilateral multifocal breast cancer and is likely associated with discordant histologic grade or Ki67.

Gene expression alterations predict the pathological complete response in triple-negative breast cancer exploratory analysis of the NACATRINE trial

This exploratory analysis of the Neoadjuvant Carboplatin in Triple Negative Breast Cancer (NACATRINE) study aimed to identify the biomarkers of pathological complete response (pCR) in patients with triple-negative breast cancer (TNBC) treated with neoadjuvant chemotherapy (NAC) within the context of a clinical trial. The NACATRINE trial is a phase II, single-center, randomized, open-label clinical trial that investigated the addition of carboplatin to sequential anthracycline- and taxane-based NAC for TNBC. We evaluated the gene expression in untreated samples to investigate its association with pCR, overall survival (OS), and disease-free survival (DFS). RNA was extracted from the tissue biopsy, and the nCounter Breast Cancer panel was used to analyze gene expression. Of the 66 patients included in the gene expression profiling analysis, 24 (36.4%) achieved pCR and 42 (63.6%) had residual disease. In unsupervised hierarchical clustering analyses, differentially expressed genes between patients with and without pCR were identified irrespective of the treatment (24 genes), carboplatin (37 genes), and non-carboplatin (27 genes) arms. In receiver operating characteristic (ROC) curve analysis, 10 genes in the carboplatin arm (area under the ROC curve [AUC], 0.936) and three genes in the non-carboplatin arm (AUC, 0.939) were considered to be potential pCR-associated biomarkers. We identified genes that were associated with improvements in OS and DFS in addition to being related to pCR. We successfully identified gene expression signatures associated with pCR in pretreatment samples of patients with TNBC treated with NAC. Further investigation of these biomarkers is warranted.

Ki67 assessment protocol as an integral biomarker for avoiding radiotherapy in the LUMINA breast cancer trial

AIMS

The LUMINA trial demonstrated a very low local recurrence rate in women ≥55 years with low-risk luminal A breast cancer (defined as grade I-II, T1N0, hormone receptor positive, HER2 negative and Ki67 index ≤13.25%) treated with breast-conserving surgery and endocrine therapy (but no other systemic therapy), supporting the safe omission of radiation in these women. Here we describe the protocol for Ki67 assessment, the companion diagnostic used to guide omission of adjuvant radiotherapy.

METHODS

Ki67 immunohistochemistry was performed on full-face sections at one of three regional labs. Pathologists trained in the International Ki67 in Breast Cancer Working Group (IKWG) method demarcated tumour areas on scanned slides and scored 100 nuclei from each of at least five randomly selected 1-mm fields. For cases with high Ki67 heterogeneity, further virtual cores were selected and scored in order to confidently assign a case as luminal A (≤13.25%) or B (>13.25%). Interlaboratory variability was assessed through an annual quality assurance programme during the study period.

RESULTS

From the quality assurance programme, the mean Ki67 index across all cases/labs was 13%. The observed intraclass correlation coefficient (ICC) and kappa statistics were ≥0.9 and ≥0.7, respectively, indicating a substantial level of agreement. Median scoring time was 4 min per case. The IKWG-recommended scoring method, performed directly from slides, requiring up to four scored fields, is concordant with the LUMINA scoring method (ICC ≥ 0.9).

CONCLUSION

Ki67 is a practical, reproducible, and inexpensive biomarker that can identify low-risk luminal A breast cancers as potential candidates for radiation de-escalation.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov number, NCT01791829.

Breast cancers with high proliferation and low ER-related signalling have poor prognosis and unique molecular features with implications for therapy

BACKGROUND

Luminal breast cancers with high proliferation (MKShi) and low ER-related signalling (ERSlo) have a poor prognosis. We investigated treatment responses and molecular features of MKShi/ERSlo tumours to inform potential therapies.

METHODS

Gene expression data from patients who received neoadjuvant chemotherapy (NAC) without (MDACC, N = 199) or with pembrolizumab (I-SPY2, N = 40), or endocrine therapy (NET) without (POETIC, N = 172) or with palbociclib (NeoPalAna, N = 32) were analyzed to assess treatment response by MKS/ERS-subgroups. TCGA was used to assess the mutational landscape and biomarkers associated with palbociclib-resistance (Cyclin-E, RBsig, IRPR) and immunotherapy-response (TMB, TILs, T-cell inflamed) by MKS/ERS-subgroups.

RESULTS

Compared to MKShi/ERShi tumours, MKShi/ERSlo tumours had higher pathological response rates to NAC (22% vs 8%, p = 0.06) but a higher recurrence risk (4-year metastasis-free survival 70% vs 94%, p = 0.01). MKShi/ERSlo tumours frequently harboured TP53 (34%) and PIK3CA (33%) mutations, and showed high expression of Cyclin-E, RBsig and IRPR, high TMB and elevated TIL and T-cell inflamed metagene expression. MKShi/ERSlo tumours retained high proliferation after NET with or without palbociclib but had higher pathological complete response rates when pembrolizumab was added to NAC (42% vs 21%, p = 0.07).

CONCLUSIONS

MKShi/ERSlo tumours have dismal outcomes and are enriched in chemotherapy-sensitive but ET- and palbociclib-resistant tumours. Biomarker analysis and clinical data suggest a potential role for immunotherapy in this group.

A Review of AI-Based Radiomics and Computational Pathology Approaches in Triple-Negative Breast Cancer: Current Applications and Perspectives

Breast cancer is one of the most common and deadly cancers worldwide. Approximately, 20% of all breast cancers are characterized as triple negative (TNBC). TNBC typically is associated with a poorer prognosis relative to other breast cancer subtypes. Due to its aggressiveness and lack of response to hormonal therapy, conventional cytotoxic chemotherapy is the usual treatment; however, this treatment is not always effective, and an important percentage of patients develop recurrence. More recently, immunotherapy has started to be used on some populations with TNBC showing promising results. Unfortunately, immunotherapy is only applicable to a minority of patients and responses in metastatic TNBC have overall been modest in comparison to other cancer types. This situation evidences the need for developing effective biomarkers that help to stratify and personalize patient management. Thanks to recent advances in artificial intelligence (AI), there has been an increasing interest in its use for medical applications aiming at supporting clinical decision making. Several works have used AI in combination with diagnostic medical imaging, more specifically radiology and digitized histopathological tissue samples, aiming to extract disease-specific information that is difficult to quantify by the human eye. These works have demonstrated that analysis of such images in the context of TNBC has great potential for (1) risk-stratifying patients to identify those patients who are more likely to experience disease recurrence or die from the disease and (2) predicting pathologic complete response. In this manuscript, we present an overview on AI and its integration with radiology and histopathological images for developing prognostic and predictive approaches for TNBC. We present state of the art approaches in the literature and discuss the opportunities and challenges with developing AI algorithms regarding further development and clinical deployment, including identifying those patients who may benefit from certain treatments (e.g., adjuvant chemotherapy) from those who may not and thereby should be directed toward other therapies, discovering potential differences between populations, and identifying disease subtypes.

Predicting early breast cancer recurrence from histopathological images in the Carolina Breast Cancer Study

Approaches for rapidly identifying patients at high risk of early breast cancer recurrence are needed. Image-based methods for prescreening hematoxylin and eosin (H&E) stained tumor slides could offer temporal and financial efficiency. We evaluated a data set of 704 1-mm tumor core H&E images (2-4 cores per case), corresponding to 202 participants (101 who recurred; 101 non-recurrent matched on age and follow-up time) from breast cancers diagnosed between 2008-2012 in the Carolina Breast Cancer Study. We leveraged deep learning to extract image information and trained a model to identify recurrence. Cross-validation accuracy for predicting recurrence was 62.4% [95% CI: 55.7, 69.1], similar to grade (65.8% [95% CI: 59.3, 72.3]) and ER status (66.3% [95% CI: 59.8, 72.8]). Interestingly, 70% (19/27) of early-recurrent low-intermediate grade tumors were identified by our image model. Relative to existing markers, image-based analyses provide complementary information for predicting early recurrence.

Circulating tumor cells participate in the formation of microvascular invasion and impact on clinical outcomes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common malignant tumor worldwide. Although the treatment strategies have been improved in recent years, the long-term prognosis of HCC is far from satisfactory mainly due to high postoperative recurrence and metastasis rate. Vascular tumor thrombus, including microvascular invasion (MVI) and portal vein tumor thrombus (PVTT), affects the outcome of hepatectomy and liver transplantation. If vascular invasion could be found preoperatively, especially the risk of MVI, more reasonable surgical selection will be chosen to reduce the risk of postoperative recurrence and metastasis. However, there is a lack of reliable prediction methods, and the formation mechanism of MVI/PVTT is still unclear. At present, there is no study to explore the possibility of tumor thrombus formation from a single circulating tumor cell (CTC) of HCC, nor any related study to describe the possible leading role and molecular mechanism of HCC CTCs as an important component of MVI/PVTT. In this study, we review the current understanding of MVI and possible mechanisms, discuss the function of CTCs in the formation of MVI and interaction with immune cells in the circulation. In conclusion, we discuss implications for potential therapeutic targets and the prospect of clinical treatment of HCC.

Understanding the promising role of antibody drug conjugates in breast and ovarian cancer

A nascent category of anticancer therapeutic drugs called antibody-drug conjugates (ADCs) relate selectivity of aimed therapy using chemotherapeutic medicines with high cytotoxic power. Progressive linker technology led to the advancement of more efficacious and safer treatments. It offers neoteric as well as encouraging therapeutic strategies for treating cancer. ADCs selectively administer a medication by targeting antigens which are abundantly articulated on the membrane surface of tumor cells. Tumor-specific antigens are differently expressed in breast and ovarian cancers and can be utilized to direct ADCs. Compared to conventional chemotherapeutic drugs, this approach enables optimal tumor targeting while minimizing systemic damage. A cleavable linker improves the ADCs because it allows the toxic payload to be distributed to nearby cells that do not express the target protein, operating on assorted tumors with dissimilar cell aggregation. Presently fifteen ADCs are being studied in breast and ovarian carcinoma preclinically, and assortment of few have already undergone promising early-phase clinical trial testing. Furthermore, Phase I and II studies are investigating a wide variety of ADCs, and preliminary findings are encouraging. An expanding sum of ADCs will probably become feasible therapeutic choices as solo agents or in conjunction with chemotherapeutic agents. This review accentuates the most recent preclinical findings, pharmacodynamics, and upcoming applications of ADCs in breast and ovarian carcinoma.

Molecular Classification of Breast Cancer

Breast carcinomas classified based on traditional morphologic assessment provide useful prognostic information. Although morphology is still the gold standard of classification, recent advances in molecular technologies have enabled the classification of these tumors into four distinct subtypes based on its intrinsic molecular profile that provide both predictive and prognostic information. This article describes the association between the different molecular subtypes with the histologic subtypes of breast cancer and illustrates how these subtypes may affect the appearance of tumors on imaging studies.

The crosstalk between autophagy and myeloid-derived suppressor cell responses in cancer

The development of cancers is aided by the accumulation of myeloid-derived suppressor cells (MDSCs) within tumors, which are highly effective at suppressing anti-tumor immune responses. Direct cell-to-cell interaction and the production of immunosuppressive mediators have both been proposed as pathways for MDSC-mediated suppression of anti-tumor immune responses. The majority of current cancer treatments focus on altering the development and activity of MDSCs so that they have more of an immunogenic character. Autophagy is a catabolic system that contributes to the breakdown of damaged intracellular material and the recycling of metabolites. However, depending on the stage of tumor growth, autophagy can play both a prophylactic and a therapeutic function in carcinogenesis. However, several indirect lines of research have indicated that autophagy is a significant regulator of MDSC activity. The purpose of this work was to outline the interactions between MDSC and autophagy in cancer.

Neoadjuvant chemotherapy reduces the levels of HMGB1 and E-cadherin in patients with breast cancer

This study investigated the changes in serum tumor marker levels in patients with breast cancer (BC) after neoadjuvant chemotherapy (NACT) and their potential as prognostic factors in NACT. A total of 134 consecutive patients with BC treated at our hospital between January 2019 and December 2021 were retrospectively analyzed. Patients were treated with NACT based on the docetaxel, epirubicin, and cyclophosphamide (TEC) regimen and assessed for marker levels, T cell subsets, and therapeutic outcomes. Receiver operating characteristic (ROC) curves were constructed to evaluate the predictive performance of the markers. Outcome assessments showed that NACT effectively reduced the tumor size, leading to increased complete remission, partial remission, stable disease, and significantly reduced disease progression. Improved immune function has also been observed after NACT. The levels of two (E-cadherin and HMGB1) out of five markers (CA153, CK19, CEA, E-cadherin, and HMGB1) were significantly reduced after NACT before surgery compared with those at admission, suggesting that NACT modulates the levels of biomarkers. ROC analysis revealed that the area under the curve (AUC) of HMGB1 and E-cadherin combination was 0.87 for discrimination of therapeutic response with a sensitivity and specificity of 91.3% and 88.4%, respectively. Serum tumor marker levels were reduced after NACT in patients with BC. The reduction was most prominent for HMGB1, followed by E-cadherin. These biomarkers can be used to predict the therapeutic response to NACT with an AUC of 0.87, thus offering a new tool to monitor treatment progress in NACT for patients with BC.

MCM-2 Levels as a Potential Biomarker for Predicting High-Risk Breast Cancer Patients According to TAILORx Classification

Background

The minichromosome maintenance protein-2 (MCM-2) is a more sensitive proliferation marker than Ki-67. This study aimed to evaluate the relationship between MCM-2 and Oncotype DX recurrence score (ODX-RS) and determine an MCM-2 cutoff value in high-risk patients according to TAILORx risk categorization.

Methods

Hormone receptor (HR) positive HER-2 negative early-stage breast cancer patients (pT1-2, pN0-N1, M0) who had ODX-RS were included in the study. According to the TAILORx trial, patients were divided into two groups with high (ODX-RS ≥26) and low risk (ODX-RS <26) in terms of ODX-RS. Formalin-fixed-paraffin-embedded tissues of patients were re-evaluated, and 3 µm sections were prepared for MCM-2 immuno-histochemical staining. The relationship between ODX-RS and the percentage of MCM-2 staining was evaluated in two groups. The ROC curve analysis was performed to determine the MCM-2 cut-off value for the TAILORx high-risk group (ODX-RS ≥26).

Results

The mean MCM-2 value was significantly higher in the high-risk group [(60.2 ± 11.2 vs 34.4 ± 13.8, p < 0.001)]. In the multivariate analysis, MCM-2 (OR: 1.27, 95% CI: 1.08-1.49, p = 0.003) and progesterone receptor (PR) levels ≤10% (OR: 60.9, 95% CI: 4.1-89.7, p = 0.003) were found to be independent factors indicating a high-risk group. A one-unit increase in MCM-2 level increased the likelihood of being in the high-risk group by 1.27 times. In the ROC curve analysis, the optimal MCM-2 cut-off level was 50 (AUC: 0.921, sensitivity: 86.7%, specificity: 96.0%, p < 0.001).

Conclusion

Our study is the first study in the literature to investigate the relationship between ODX-RS and MCM-2 levels in HR-positive HER-2 negative early breast-cancer patients. In this study, MCM-2 was an independent risk factor in identifying high-risk patients according to TAILORx risk classification. MCM 2 cut-off value (50) may help the decision on adjuvant chemotherapy in patients where the Oncotype DX test cannot be performed.

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.

Survival results according to Oncotype Dx recurrence score in patients with hormone receptor positive HER-2 negative early-stage breast cancer: first multicenter Oncotype Dx recurrence score survival data of Turkey

Background

The Oncotype Dx recurrence score (ODx-RS) guides the adjuvant chemotherapy decision-making process for patients with early-stage hormone receptor-positive, HER-2 receptor-negative breast cancer. This study aimed to evaluate survival and its correlation with ODx-RS in pT1-2, N0-N1mic patients treated with adjuvant therapy based on tumor board decisions.

Patients and methods

Estrogen-positive HER-2 negative early-stage breast cancer patients (pT1-2 N0, N1mic) with known ODx-RS, operated on between 2010 and 2014, were included in this study. The primary aim was to evaluate 5-year disease-free survival (DFS) rates according to ODX-RS.

Results

A total of 203 eligible patients were included in the study, with a median age of 48 (range 26-75) and median follow-up of 84 (range 23-138) months. ROC curve analysis for all patients revealed a recurrence cut-off age of 45 years, prompting evaluation by grouping patients as ≤45 years vs. >45 years. No significant difference in five-year DFS rates was observed between the endocrine-only (ET) and chemo-endocrine (CE) groups. However, among the ET group, DFS was higher in patients over 45 years compared to those aged ≤45 years. When stratifying by ODx-RS as 0-17 and ≥18, DFS was significantly higher in the former group within the ET group. However, such differences were not seen in the CE group. In the ET group, an ODx-RS ≥18 and menopausal status were identified as independent factors affecting survival, with only an ODx-RS ≥18 impacting DFS in patients aged ≤45 years. The ROC curve analysis for this subgroup found the ODx-RS cut-off to be 18.

Conclusion

This first multicenter Oncotype Dx survival analysis in Turkey demonstrates the importance of Oncotype Dx recurrence score and age in determining treatment strategies for early-stage breast cancer patients. As a different aproach to the literature, our findings suggest that the addition of chemotherapy to endocrine therapy in young patients (≤45 years) with Oncotype Dx recurrence scores of ≥18 improves DFS.

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.

MRI-Based Radiomics Approach Predicts Tumor Recurrence in ER + /HER2 - Early Breast Cancer Patients

Oncotype Dx Recurrence Score (RS) has been validated in patients with ER + /HER2 - invasive breast carcinoma to estimate patient risk of recurrence and guide the use of adjuvant chemotherapy. We investigated the role of MRI-based radiomics features extracted from the tumor and the peritumoral tissues to predict the risk of tumor recurrence. A total of 62 patients with biopsy-proved ER + /HER2 - breast cancer who underwent pre-treatment MRI and Oncotype Dx were included. An RS > 25 was considered discriminant between low-intermediate and high risk of tumor recurrence. Two readers segmented each tumor. Radiomics features were extracted from the tumor and the peritumoral tissues. Partial least square (PLS) regression was used as the multivariate machine learning algorithm. PLS β-weights of radiomics features included the 5% features with the largest β-weights in magnitude (top 5%). Leave-one-out nested cross-validation (nCV) was used to achieve hyperparameter optimization and evaluate the generalizable performance of the procedure. The diagnostic performance of the radiomics model was assessed through receiver operating characteristic (ROC) analysis. A null hypothesis probability threshold of 5% was chosen (p < 0.05). The exploratory analysis for the complete dataset revealed an average absolute correlation among features of 0.51. The nCV framework delivered an AUC of 0.76 (p = 1.1∙10-3). When combining "early" and "peak" DCE images of only T or TST, a tendency toward statistical significance was obtained for TST with an AUC of 0.61 (p = 0.05). The 47 features included in the top 5% were balanced between T and TST (23 and 24, respectively). Moreover, 33/47 (70%) were texture-related, and 25/47 (53%) were derived from high-resolution images (1 mm). A radiomics-based machine learning approach shows the potential to accurately predict the recurrence risk in early ER + /HER2 - breast cancer patients.

The usefulness of CanAssist Breast over Ki67 in breast cancer recurrence risk assessment

BACKGROUND

Assessment of Ki67 by immunohistochemistry (IHC) has limited utility in clinical practice owing to analytical validity issues. According to International Ki67 Working Group (IKWG) guidelines, treatment should be guided by a prognostic test in patients expressing intermediate Ki67 range, >5%-<30%. The objective of the study is to compare the prognostic performance of CanAssist Breast (CAB) with that of Ki67 across various Ki67 prognostic groups.

METHODS

The cohort had 1701 patients. Various risk groups were compared for the distant relapse-free interval (DRFi) derived from Kaplan-Meier survival analysis. As per IKWG, patients are categorized into three risk groups: low-risk (<5%), intermediate risk (>5%-<30%), and high-risk (>30%). CAB generates two risk groups, low and high risk based on a predefined cutoff.

RESULTS

In the total cohort, 76% of the patients were low risk (LR) by CAB as against 46% by Ki67 with a similar DRFi of 94%. In the node-negative sub-cohort, 87% were LR by CAB with a DRFi of 97% against 49% by Ki67 with a DRFi of 96%. In subgroups of patients with T1 or N1 or G2 tumors, Ki67-based risk stratification was not significant while it was significant by CAB. In the intermediate Ki67 (>5%-<30%) category up to 89% (N0 sub-cohort) were LR by CAB and the percentage of LR patients was 25% (p < 0.0001) higher compared to NPI or mAOL. In the low Ki67 (≤5%) group, up to 19% were segregated as high-risk by CAB with 86% DRFi suggesting the requirement of chemotherapy in these low Ki67 patients.

CONCLUSION

CAB provided superior prognostic information in various Ki67 subgroups, especially in the intermediate Ki67 group.

DNA aneuploidy identifies a subset of Luminal subtype breast carcinoma patients with worse clinical outcome

AIM

In breast carcinoma (BC), the relationship between the ploidy pattern and molecular subtyping is still unknown. We aim to investigate the prognostic impact of DNA ploidy within molecular subtypes of a large cohort of BC patients.

METHODS

The series involved 520 BC patients with no neoadjuvant therapy and a median follow-up of 115.5 months. Immunohistochemical assessment of hormonal receptors, ERBB2 (HER2) status and Ki67 proliferative activity was the basis of the surrogate molecular subtyping. Ploidy was evaluated by DNA flow cytometry in fresh/frozen tumour samples. Kaplan-Meier (K-M) survival estimation was used for prognostic statistical analysis.

RESULTS

Luminal A subtype had the lowest prevalence of disease recurrences (23.6 %) and deaths from disease (18.3 %), while Luminal B (42.2 %/37.9 %), Triple-negative (46.4 %/40.6 %), and HER2-positive (55.9 %/50.0 %) subtypes had the highest. The Triple-positive subtype shows an intermediate/low frequency of adverse events (29.4 % of disease recurrences and 17.6 % of deaths from disease). Luminal A tumours were mostly diploid (55.3 %), while Triple-negative and HER2-positive tumours showed a high incidence of aneuploidy (82.6 % and 88.2 %, respectively). Luminal B and Triple-positive tumours had an intermediate percentage of aneuploidy (63.8 % and 70.6 %, respectively). K-M survival curves showed that DNA aneuploidy is significantly associated with shorter disease-free survival and overall survival in Luminal A and Luminal B molecular subtypes.

CONCLUSION

DNA aneuploidy identifies a subset of Luminal BC patients with worse clinical outcome, potentially eligible for more aggressive adjuvant therapy.

Reproducibility and intratumoral heterogeneity of the PAM50 breast cancer assay

BACKGROUND

The PAM50 assay is used routinely in clinical practice to determine breast cancer prognosis and management; however, research assessing how technical variation and intratumoral heterogeneity contribute to misclassification and reproducibility of these tests is limited.

METHODS

We evaluated the impact of intratumoral heterogeneity on the reproducibility of results for the PAM50 assay by testing RNA extracted from formalin-fixed paraffin embedded breast cancer blocks sampled at distinct spatial locations. Samples were classified according to intrinsic subtype (Luminal A, Luminal B, HER2-enriched, Basal-like, or Normal-like) and risk of recurrence with proliferation score (ROR-P, high, medium, or low). Intratumoral heterogeneity and technical reproducibility (replicate assays on the same RNA) were assessed as percent categorical agreement between paired intratumoral and replicate samples. Euclidean distances between samples, calculated across the PAM50 genes and the ROR-P score, were compared for concordant vs. discordant samples.

RESULTS

Technical replicates (N = 144) achieved 93% agreement for ROR-P group and 90% agreement on PAM50 subtype. For spatially distinct biological replicates (N = 40 intratumoral replicates), agreement was lower (81% for ROR-P and 76% for PAM50 subtype). The Euclidean distances between discordant technical replicates were bimodal, with discordant samples showing higher Euclidian distance and biologic heterogeneity.

CONCLUSION

The PAM50 assay achieved very high technical reproducibility for breast cancer subtyping and ROR-P, but intratumoral heterogeneity is revealed by the assay in a small proportion of cases.

A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer

Radiological imaging is currently employed as the most effective technique for screening, diagnosis, and follow up of patients with breast cancer (BC), the most common type of tumor in women worldwide. However, the introduction of the omics sciences such as metabolomics, proteomics, and molecular genomics, have optimized the therapeutic path for patients and implementing novel information parallel to the mutational asset targetable by specific clinical treatments. Parallel to the "omics" clusters, radiological imaging has been gradually employed to generate a specific omics cluster termed "radiomics". Radiomics is a novel advanced approach to imaging, extracting quantitative, and ideally, reproducible data from radiological images using sophisticated mathematical analysis, including disease-specific patterns, that could not be detected by the human eye. Along with radiomics, radiogenomics, defined as the integration of "radiology" and "genomics", is an emerging field exploring the relationship between specific features extracted from radiological images and genetic or molecular traits of a particular disease to construct adequate predictive models. Accordingly, radiological characteristics of the tissue are supposed to mimic a defined genotype and phenotype and to better explore the heterogeneity and the dynamic evolution of the tumor over the time. Despite such improvements, we are still far from achieving approved and standardized protocols in clinical practice. Nevertheless, what can we learn by this emerging multidisciplinary clinical approach? This minireview provides a focused overview on the significance of radiomics integrated by RNA sequencing in BC. We will also discuss advances and future challenges of such radiomics-based approach.

Caveolin-1 genotypes as predictor for locoregional recurrence and contralateral disease in breast cancer

PURPOSE

Caveolin-1 (CAV1) has been implicated in breast cancer oncogenesis and metastasis and may be a potential prognosticator, especially for non-distant events. CAV1 functions as a master regulator of membrane transport and cell signaling. Several CAV1 SNPs have been linked to multiple cancers, but the prognostic impact of CAV1 SNPs in breast cancer remains unclear. Here, we investigated CAV1 polymorphisms in relation to clinical outcomes in breast cancer.

METHODS

A cohort of 1017 breast cancer patients (inclusion 2002-2012, Sweden) were genotyped using Oncoarray by Ilumina. Patients were followed for up to 15 years. Five out of six CAV1 SNPs (rs10256914, rs959173, rs3807989, rs3815412, and rs8713) passed quality control and were used for haplotype construction. CAV1 genotypes and haplotypes in relation to clinical outcomes were assessed with Cox regression and adjusted for potential confounders (age, tumor characteristics, and adjuvant treatments).

RESULTS

Only one SNP was associated with lymph node status, no other SNPs or haplotypes were associated with tumor characteristics. The CAV1 rs3815412 CC genotype (5.8% of patients) was associated with increased risk of contralateral breast cancer, adjusted hazard ratio (HR_adj) 4.26 (95% CI 1.86-9.73). Moreover, the TTACA haplotype (13% of patients) conferred an increased risk for locoregional recurrence HR_adj 2.24 (95% CI 1.24-4.04). No other genotypes or haplotypes were associated with clinical outcome.

CONCLUSION

CAV1 polymorphisms were associated with increased risk for locoregional recurrence and contralateral breast cancer. These findings may identify patients that could derive benefit from more tailored treatment to prevent non-distant events, if confirmed.

Concordance of immunohistochemistry for predictive and prognostic factors in breast cancer between biopsy and surgical excision: a single-centre experience and review of the literature

PURPOSE

Accurate evaluation of breast cancer on bioptic samples is of fundamental importance to guide therapeutic decisions, especially in the neoadjuvant or metastatic setting. We aimed to assess concordance for oestrogen receptor (ER), progesterone receptor (PR), c-erbB2/HER2 and Ki-67. We also reviewed the current literature to evaluate our results in the context of the data available at present.

METHODS

We included patients who underwent both biopsy and surgical resection for breast cancer at San Matteo Hospital, Pavia, Italy, between January 2014 and December 2020. ER, PR, c-erbB2, and Ki-67 immunohistochemistry concordance between biopsy and surgical specimen was evaluated. ER was further analysed to include the recently defined ER-low-positive in our analysis.

RESULTS

We evaluated 923 patients. Concordance between biopsy and surgical specimen for ER, ER-low-positive, PR, c-erbB2 and Ki-67 was, respectively, 97.83, 47.8, 94.26, 68 and 86.13%. Cohen's κ for interobserver agreement was very good for ER and good for PR, c-erbB2 and Ki-67. Concordance was especially low (37%) in the c-erbB2 1 + category.

CONCLUSION

Oestrogen and progesterone receptor status can be safely assessed on preoperative samples. The results of this study advise caution in interpreting biopsy results regarding ER-low-positive, c-erbB2/HER and Ki-67 results due to a still suboptimal concordance. The low concordance for c-erbB2 1 + cases underlines the importance of further training in this area, in the light of the future therapeutic perspectives.

Discordance between PAM50 intrinsic subtyping and immunohistochemistry in South African women with breast cancer

PURPOSE

Breast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified using immunohistochemistry. In high-income countries multiparameter genomic assays are being utilized with implications for tumor classification and treatment.

METHODS

In a cohort of 378 breast cancer patients from the SABCHO study, we investigated the concordance between tumor samples classified by IHC and the PAM50 gene assay.

RESULTS

IHC classified patients as ER-positive (77.5%), PR-positive (70.6%), and HER2-positive (32.3%). These results, together with Ki67, were used as surrogates for intrinsic subtyping, and showed 6.9% IHC-A-clinical, 72.7% IHC-B-clinical, 5.3% IHC-HER2-clinical and 15.1% triple negative cancer (TNC). Typing using the PAM50 gave 19.3% luminal-A, 32.5% luminal-B, 23.5% HER2-enriched and 24.6% basal-like. The basal-like and TNC had the highest concordance, while the luminal-A and IHC-A group had the lowest concordance. By altering the cutoff for Ki67, and realigning the HER2/ER/PR-positive patients to IHC-HER2, we improved concordance with the intrinsic subtypes.

CONCLUSION

We suggest that the Ki67 be changed to a cutoff of 20-25% in our population to better reflect the luminal subtype classifications. This change would inform treatment options for breast cancer patients in settings where genomic assays are unaffordable.

Genetics, Treatment, and New Technologies of Hormone Receptor-Positive Breast Cancer

The current molecular classification divides breast cancer into four major subtypes, including luminal A, luminal B, HER2-positive, and basal-like, based on receptor gene expression profiling. Luminal A and luminal B are hormone receptor (HR, estrogen, and/or progesterone receptor)-positive and are the most common subtypes, accounting for around 50-60% and 15-20% of the total breast cancer cases, respectively. The drug treatment for HR-positive breast cancer includes endocrine therapy, HER2-targeted therapy (depending on the HER2 status), and chemotherapy (depending on the risk of recurrence). In this review, in addition to classification, we focused on discussing the important aspects of HR-positive breast cancer, including HR structure and signaling, genetics, including epigenetics and gene mutations, gene expression-based assays, the traditional and new drugs for treatment, and novel or new uses of technology in diagnosis and treatment. Particularly, we have summarized the commonly mutated genes and abnormally methylated genes in HR-positive breast cancer and compared four common gene expression-based assays that are used in breast cancer as prognostic and/or predictive tools in detail, including their clinical use, the factors being evaluated, patient demographics, and the scoring systems. All these topic discussions have not been fully described and summarized within other research or review articles.

SRSF3-Mediated Ki67 Exon 7-Inclusion Promotes Head and Neck Squamous Cell Carcinoma Progression via Repressing AKR1C2

Ki67 is a well-known proliferation marker with a large size of around 350 kDa, but its biological function remains largely unknown. The roles of Ki67 in tumor prognosis are still controversial. Ki67 has two isoforms generated by alternative splicing of exon 7. The roles and regulatory mechanisms of Ki67 isoforms in tumor progression are not clear. In the present study, we surprisingly find that the increased inclusion of Ki67 exon 7, not total Ki67 expression level, was significantly associated with poor prognosis in multiple cancer types, including head and neck squamous cell carcinoma (HNSCC). Importantly, the Ki67 exon 7-included isoform is required for HNSCC cell proliferation, cell cycle progression, cell migration, and tumorigenesis. Unexpectedly, Ki67 exon 7-included isoform is positively associated with intracellular reactive oxygen species (ROS) level. Mechanically, splicing factor SRSF3 could promote exon 7 inclusion via its two exonic splicing enhancers. RNA-seq revealed that aldo-keto reductase AKR1C2 is a novel tumor-suppressive gene targeted by Ki67 exon 7-included isoform in HNSCC cells. Our study illuminates that the inclusion of Ki67 exon 7 has important prognostic value in cancers and is essential for tumorigenesis. Our study also suggested a new SRSF3/Ki67/AKR1C2 regulatory axis during HNSCC tumor progression.

Protective roles of tRNA-derived small RNA tRF-Ile-AAT-019 in pathological progression of psoriasis

Psoriasis is a chronic recurrent inflammatory skin disease that is characterized by abnormal proliferation and differentiation of keratinocytes (KCs), angiogenesis and skin inflammation. Transfer RNA fragments (tRFs) are tRNA-derived small RNAs (tsRNAs), which possess regulatory functions in many diseases. Their potential roles in the pathological development of psoriasis have not been established. We first identified differentially expressed (DE) tRFs from psoriatic skin lesions using small RNA sequencing, and collected additional clinical samples for validation. Then, we investigated the function and mechanism of target tRFs in vitro. As a result of our investigation: we identified 234 DE transcripts in psoriatic skin lesions compared with normal controls. Further functional analysis showed the downregulation of tRF-Ile-AAT-019 in psoriatic lesions plays a critical role in pathogenesis since it could target 3'UTR of the serine protease serpin protein E1 (SERPINE1) gene. We next demonstrated that tRF-Ile-AAT-019 could suppress SERPINE1, thus leading to decreased expressions of vascular endothelial growth factor but increased expressions of keratinocytes (KCs) differentiation markers including Keratin1 and Involucrin. In conclusion, tRF-Ile-AAT-019 plays a protective role in the pathological progression of psoriasis via targeting SERPINE1, resulting in regulation of KCs differentiation and vascular proliferation biomarkers and providing a potential novel targeting pathway for the disease treatment.

Breast Cancer Pathology in the Era of Genomics

The era of genomic medicine provides an opportunity for pathologists to offer greater detail about the molecular underpinnings of a patient's cancer and thereby more targeted therapeutic options. In this review article, the role of genomics in breast cancer pathology is discussed, as it pertains to risk management, classification of special tumor types, predictive and prognostic testing, identification of actionable therapeutic targets, and monitoring for disease progression or development of treatment resistance.

Clinical Utility of Genomic Recurrence Risk Stratification in Early, Hormone-Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer: Real-World Experience

BACKGROUND

RNA-based genomic risk assessment estimates chemotherapy benefit in patients with hormone-receptor positive (HR+)/Human Epidermal Growth Factor 2-negative (ERBB2-) breast cancer (BC). It is virtually used in all patients with early HR+/ERBB2- BC regardless of clinical recurrence risk.

PATIENTS AND METHODS

We conducted a retrospective chart review of adult patients with early-stage (T1-3; N0; M0) HR+/ERBB2- BC who underwent genomic testing using the Oncotype DX (Exact Sciences) 21-genes assay. Clinicopathologic features were collected to assess the clinical recurrence risk, in terms of clinical risk score (CRS) and using a composite risk score of distant recurrence Regan Risk Score (RRS). CRS and RRS were compared to the genomic risk of recurrence (GRS).

RESULTS

Between January 2015 and December 2020, 517 patients with early-stage disease underwent genomic testing, and clinical data was available for 501 of them. There was statistically significant concordance between the 3 prognostication methods (P < 0.01). Within patients with low CRS (n = 349), 9.17% had a high GRS, compared to 8.93% in patients with low RRS (n = 280). In patients with grade 1 histology (n = 130), 3.85% had a high GRS and 68.46% had tumors > 1 cm, of whom only 4.49% had a high GRS. Tumor size > 1cm did not associate with a high GRS.

CONCLUSION

Genomic testing for patients with grade 1 tumors may be safely omitted, irrespective of size. Our finds call for a better understanding of the need for routine genomic testing in patients with low grade/low clinical risk of recurrence.

Low Rates of Medical Oncology Consultation for Older Women (≥ 70 Years) with Newly Diagnosed, Non-Metastatic Breast Cancer: A Population-Based Study

BACKGROUND

Curative intent cancer treatment needs to be balanced with patient comorbidities and quality of life when treating older women with breast cancer. We examined consultation patterns and association of age at diagnosis with lack of specialist cancer consultations for older women with breast cancer.

METHODS

We conducted a population-based retrospective cohort study of older women (≥ 70 years of age) with incident, non-metastatic breast cancer (2010-2018) by linking administrative databases in Ontario, Canada. The outcomes of interest were lack of specialist cancer consultation (surgeon, medical oncology, or radiation oncology) within 12 months of diagnosis. Association of age with lack of specialist cancer consultation was examined using Poisson regression modeling.

RESULTS

Of 21,849 older women, 2.4% (n = 517) did not have any specialist cancer consultation within 12 months of diagnosis; lack of any specialist cancer consultation increased with age (0.8% for age 70-74 years, 1.3% for age 75-79 years, 2.5% for age 80-84 years, and 7.0% for age ≥ 85 years; p < 0.001). The proportion of patients who did not have consultations with surgeons, medical oncologists, and radiation oncologists was 8.6% (n = 1888), 34.4% (n = 7510), and 24.7% (n = 5404), respectively. Older age group was independently associated with an increased likelihood of lacking any specialist consultation, as well as not receiving surgical and medical oncology consultations.

CONCLUSION

More than one-third of women ≥ 70 years of age with non-metastatic breast cancer did not have a consultation with a medical oncologist, with women aged ≥ 85 years least likely to have a medical oncology consultation.

Expression and clinical significance of undifferentiated embryonic cell transcription factor 1 in breast cancer

Background

At present, due to the heterogeneity of breast cancer, common tumor markers have certain limitations in clinical prognostic evaluation. This suggests an unmet need for markers to predict clinical outcomes and potentially guide targeted therapies. The present study sought to explore the expression level and clinical significance of undifferentiated embryonic cell transcription factor 1 (UTF1) in breast cancer.

Methods

Immunohistochemistry (IHC) was used to detect the expression of UTF1 in 221 breast cancer samples. The clinical significance of UTF1 protein expression in breast cancer tissues was evaluated by combining clinicopathological parameters and UTF1 expression profile. We performed 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide (MTT) and clone formation assays to evaluate the effect of UTF1 on Bcap37 cell proliferation. Wound healing assay and transwell migration assay were used to evaluate the changes of cell invasion and migration ability, respectively. All experiments were performed with 3 biological replicates. Genomic differences after UTF1 overexpression were evaluated by RNA sequencing technology and the possible functions and regulatory mechanisms were elucidated.

Results

The findings showed that UTF1 expression level was significantly correlated with tumor size (P=0.004), but not with patient age, tumor histological stage, lymph node metastasis, as well as estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2), and Ki67 expression levels. Kaplan-Meier survival analysis and Cox proportional hazard model indicated that UTF1 expression was significantly associated with overall survival (OS) time of breast cancer patients. The median survival time of patients with high expression level of UTF1 was shorter compared with that of patients with low UTF1 expression level. The results of cell experiments showed that UTF1 overexpression could significantly promote the growth, proliferation, migration, and invasion of breast cancer cells. The RNA sequencing results showed that UTF1 was not only closely related to apoptosis genes, but also closely related to the nuclear factor (NF)-kappa B pathway.

Conclusions

The findings of the current study indicate that UTF1 is involved in occurrence and tumor progression and is significantly associated with prognosis of breast cancer patients.

The Evolution of Ki-67 and Breast Carcinoma: Past Observations, Present Directions, and Future Considerations

The 1983 discovery of a mouse monoclonal antibody-the Ki-67 antibody-that recognized a nuclear antigen present only in proliferating cells represented a seminal discovery for the pathologic assessment of cellular proliferation in breast cancer and other solid tumors. Cellular proliferation is a central determinant of prognosis and response to cytotoxic chemotherapy in patients with breast cancer, and since the discovery of the Ki-67 antibody, Ki-67 has evolved as an important biomarker with both prognostic and predictive potential in breast cancer. Although there is universal recognition among the international guideline recommendations of the value of Ki-67 in breast cancer, recommendations for the actual use of Ki-67 assays in the prognostic and predictive evaluation of breast cancer remain mixed, primarily due to the lack of assay standardization and inconsistent inter-observer and inter-laboratory reproducibility. The treatment of high-risk ER-positive/human epidermal growth factor receptor-2 (HER2) negative breast cancer with the recently FDA-approved drug abemaciclib relies on a quantitative assessment of Ki-67 expression in the treatment decision algorithm. This further reinforces the urgent need for standardization of Ki-67 antibody selection and staining interpretation, which will hopefully lead to multidisciplinary consensus on the use of Ki-67 as a prognostic and predictive marker in breast cancer. The goals of this review are to highlight the historical evolution of Ki-67 in breast cancer, summarize the present literature on Ki-67 in breast cancer, and discuss the evolving literature on the use of Ki-67 as a companion diagnostic biomarker in breast cancer, with consideration for the necessary changes required across pathology practices to help increase the reliability and widespread adoption of Ki-67 as a prognostic and predictive marker for breast cancer in clinical practice.