Ki67 levels as predictive and prognostic parameters in pretherapeutic breast cancer core biopsies: a translational investigation in the neoadjuvant GeparTrio trial

Neoadjuvant Therapy: Current Landscape and Future Horizons for ER-Positive/HER2-Negative and Triple-Negative Early Breast Cancer

OPINION STATEMENT

Navigating the complex landscape of breast cancer treatment involves distinct strategies for luminal and triple-negative subtypes. While neoadjuvant chemotherapy historically dominates the approach for aggressive triple-negative tumors, recent evidence highlights the transformative impact of immunotherapy, alongside chemotherapy, in reshaping treatment paradigms. In luminal cancers, endocrine therapy, notably aromatase inhibitors, demonstrates promising outcomes in postmenopausal patients with low-grade luminal A tumors. However, integrating targeted therapies like CDK4/6 inhibitors in neoadjuvant setting remains inconclusive. Identifying predictive factors for treatment response, especially in luminal tumors, poses a challenge, emphasizing the necessity for ongoing research. A multidisciplinary approach, tailored to individual patient profiles, is crucial for maximizing efficacy while minimizing toxicity. As we strive to optimize breast cancer management, a comprehensive understanding of the distinct characteristics and treatment implications of luminal and triple-negative subtypes, including the transformative role of immunotherapy, is essential for informed decision-making and personalized care.

Predictive value of lymphocyte subsets and lymphocyte-to-monocyte ratio in assessing the efficacy of neoadjuvant therapy in breast cancer

Lymphocyte subsets are the most intuitive expression of the body's immune ability, and the lymphocyte-to-monocyte ratio (LMR) also clearly reflect the degree of chronic inflammation activity. The purpose of this study is to investigate their predictive value of lymphocyte subsets and LMR to neoadjuvant therapy (NAT) efficacy in breast cancer patients. In this study, lymphocyte subsets and LMR were compared between breast cancer patients (n = 70) and benign breast tumor female populations (n = 48). Breast cancer patients were treated with NAT, and the chemotherapy response of the breast was evaluated using established criteria. The differences in lymphocyte subsets and LMR were also compared between pathological complete response (pCR) and non-pCR patients before and after NAT. Finally, data were analyzed using SPSS. The analytical results demonstrated that breast cancer patients showed significantly lower levels of CD3 + T cells, CD4 + T cells, CD4 + /CD8 + ratio, NK cells, and LMR compared to benign breast tumor women (P < 0.05). Among breast cancer patients, those who achieved pCR had higher levels of CD4 + T cells, NK cells, and LMR before NAT (P < 0.05). NAT increased CD4 + /CD8 + ratio and decreased CD8 + T cells in pCR patients (P < 0.05). Additionally, both pCR and non-pCR patients exhibited an increase in CD3 + T cells and CD4 + T cells after treatment, but the increase was significantly higher in pCR patients (P < 0.05). Conversely, both pCR and non-pCR patients experienced a decrease in LMR after treatment. However, this decrease was significantly lower in pCR patients (P < 0.05). These indicators demonstrated their predictive value for therapeutic efficacy. In conclusion, breast cancer patients experience tumor-related immunosuppression and high chronic inflammation response. But this phenomenon can be reversed to varying degrees by NAT. It has been found that lymphocyte subsets and LMR have good predictive value for pCR. Therefore, these markers can be utilized to identify individuals who are insensitive to NAT early on, enabling the adjustment of treatment plans and achieving precise breast cancer treatment.

Breast Cancer Histopathology in the Age of Molecular Oncology

For more than a century, microscopic histology has been the cornerstone for cancer diagnosis, and breast carcinoma is no exception. In recent years, clinical biomarkers, gene expression profiles, and other molecular tests have shown increasing utility for identifying the key biological features that guide prognosis and treatment of breast cancer. Indeed, the most common histologic pattern-invasive ductal carcinoma of no special type-provides relatively little guidance to management beyond triggering grading, biomarker testing, and clinical staging. However, many less common histologic patterns can be recognized by trained pathologists, which in many cases can be linked to characteristic biomarker and gene expression patterns, underlying mutations, prognosis, and therapy. Herein we describe more than a dozen such histomorphologic subtypes (including lobular, metaplastic, salivary analog, and several good prognosis special types of breast cancer) in the context of their molecular and clinical features.

Prognostic and Clinical Significance of PD-L1, EGFR and Androgen Receptor (AR) Expression in Triple-Negative Breast Cancer (TNBC) Patients

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and is associated with high recurrence rates, a high incidence of distant metastases and poor overall survival. The aim of this study was to investigate the role of PD-L1, EGFR and AR expression in TNBC promotion and progression. To that end, we analyzed the immunohistochemical expression of these genes in 125 TNBC patients and their relation to clinicopathological parameters and survival. An elevated expression of PD-L1 was significantly correlated with higher tumor and nuclear grade, while a low expression was correlated with loco-regional recurrence without any influence on survival. Contrary to this, the expression of AR showed a positive impact on the DFI and a negative association with tumor grade. Furthermore, PD-L1 and AR demonstrated simultaneous expression, and further co-expression analysis revealed that a positive expression of PD-L1/AR notably correlates with tumor and nuclear grade and has a significant impact on a longer DFI and OS, while a negative PD-L1/AR expression is significantly associated with metastases. Therefore, our results suggest that positive PD-L1/AR expression is beneficial for TNBC patients. In addition, an elevated expression of EGFR contributes to metastases and a worse DFI and OS. In conclusion, we think that low PD-L1/low AR/high EGFR expression followed by high Ki67 expression constitutes a 'high risk' profile of TNBC.

Rational and trial design of FASCINATE-N: a prospective, randomized, precision-based umbrella trial

Background

With our growing insight into the molecular heterogeneity and biological characteristics of breast cancer, individualized treatment is the future of cancer treatment. In this prospective Fudan University Shanghai Cancer Center Breast Cancer Precision Platform Series study - neoadjuvant therapy (FASCINATE-N) trial, we classify breast cancer patients using multiomic characteristics into different subtypes to evaluate the efficacy of precision-based targeted therapies compared to standard neoadjuvant chemotherapy.

Methods and design

The FASCINATE-N trial is a prospective, randomized, precision-based umbrella trial that plans to enroll 716 women with early breast cancer. After enrollment, patients will first be divided into three groups: hormone receptor (HR)+/human epidermal growth factor receptor 2 (HER2)-, HER2+, and HR-/HER2-. The HR+/HER2- patients are further stratified using fusion and clustering of similarity network fusion (SNF) algorithm into four subtypes; HER2+ patients are divided into HR+/HER2+ and HR-/HER2+ subtypes; and HR-/HER2- patients are stratified using the Fudan University Shanghai Cancer Center classification. For the assignment of drugs to patients, Bayesian methods of adaptive randomization will be used. The primary endpoint is pathological complete response rate; secondary endpoints include 3-year invasive disease-free survival, overall response rate, and toxicities according to common terminology criteria for adverse events (CTCAE) scale version 4.0 and the ratio of patients with complete cell cycle arrest (Ki67 < 2.7%) in HR+/HER2+ breast cancer.

Discussion

The goal of our trial is to test the efficacy of our subtyping-based treatment in a neoadjuvant setting and to conduct a pilot study into the efficacy of targeted therapies within each precision-based subtype. The precision-based treatment arm can be updated with the refinement of our subtyping method, the discovery of new targets, and the development of novel targeted drugs. Our trial offers a unique opportunity to provide patients with individualized neoadjuvant therapy and test promising novel treatments that may further benefit patients.

Trial registration

ClinicalTrials.gov identifier: NCT05582499 (https://classic.clinicaltrials.gov/ct2/show/NCT05582499).

Ki-67 Change in Anthracyline-containing Neoadjuvant Chemotherapy Response in Breast Cancer

OBJECTIVE

Anthracycline-containing regimens are irreplaceable in neoadjuvant chemotherapy (NAC) for breast cancer (BC) at present. However, 30% of early breast cancer (EBC) patients are resistant to anthracycline-containing chemotherapy, leading to poor prognosis and higher mortality. Ki-67 is associated with the prognosis and response to therapy, and it changes after NAC.

METHODS

A total of 105 BC patients who received anthracycline-containing NAC were enrolled. Then, the optimal model of Ki-67 was selected, and its predictive efficacy was analyzed. Immunohistochemistry (IHC) was used to determine the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) status and Ki-67 level. Fluorescent in situ hybridization (FISH) was used to verify the HER-2 when the IHC score was 2+.

RESULTS

The post-NAC Ki67 level after treatment with anthracycline drugs was lower than pre-NAC Ki-67 (19.6%±23.3% vs. 45.6%±23.1%, P<0.001). Furthermore, patients with the Ki-67 decrease had a border line higher pathological complete response (pCR) rate (17.2% vs. 0.0%, P=0.068), and a higher overall response rate (ORR) (73.6% vs. 27.8%, P<0.001), when compared to patients without the Ki-67 decrease. The ΔKi-67 and ΔKi-67% were valuable markers for the prediction of both the pCR rate and ORR. The area under the curve (AUC) for ΔKi-67 on pCR and ORR was 0.809 (0.698-0.921) and 0.755 (0.655-0.855), respectively, while the AUC for ΔKi-67% on pCR and ORR was 0.857 (0.742-0.972) and 0.720 (0.618-0.822), respectively. Multivariate logistic regression model 1 revealed that ΔKi-67 was an independent predictor for both pCR [odds ratio (OR)=61.030, 95% confidence interval (CI)=4.709-790.965; P=0.002] and ORR (OR=10.001, 95% CI: 3.044-32.858; P<0.001). Multivariate logistic regression model 2 revealed that ΔKi-67% was also an independent predictor for both pCR (OR=408.922, 95% CI=8.908-18771.224; P=0.002) and ORR (OR=5.419, 95% CI=1.842-15.943; P=0.002).

CONCLUSIONS

The present study results suggest that ΔKi67 and ΔKi67% are candidate predictors for anthracycline-containing NAC response, and that they may provide various information for further systematic therapy after surgery in clinical practice.

Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status

To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) in classifying benign and malignant breast lesions and predicting the expression status of immunohistochemistry (IHC) markers. We retrospectively analysed 121 patients with breast lesions who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and SyMRI before surgery in our hospital. DCE-MRI was used to assess the lesions, and then regions of interest (ROIs) were outlined on SyMRI (before and after enhancement), and apparent diffusion coefficient (ADC) maps to obtain quantitative values. After being grouped according to benign and malignant status, the malignant lesions were divided into high and low expression groups according to the expression status of IHC markers. Logistic regression was used to analyse the differences in independent variables between groups. The performance of the modalities in classification and prediction was evaluated by receiver operating characteristic (ROC) curves. In total, 57 of 121 lesions were benign, the other 64 were malignant, and 56 malignant lesions performed immunohistochemical staining. Quantitative values from proton density-weighted imaging prior to an injection of the contrast agent (PD-Pre) and T2-weighted imaging (T2WI) after the injection (T2-Gd), as well as its standard deviation (SD of T2-Gd), were valuable SyMRI parameters for the classification of benign and malignant breast lesions, but the performance of SyMRI (area under the curve, AUC = 0.716) was not as good as that of ADC values (AUC = 0.853). However, ADC values could not predict the expression status of breast cancer markers, for which SyMRI had excellent performance. The AUCs of androgen receptor (AR), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), p53 and Ki-67 were 0.687, 0.890, 0.852, 0.746, 0.813 and 0.774, respectively. SyMRI had certain value in distinguishing between benign and malignant breast lesions, and ADC values were still the ideal method. However, to predict the expression status of IHC markers, SyMRI had an incomparable value compared with ADC values.

Randomized phase III trial of a neoadjuvant regimen of four cycles of adriamycin plus cyclophosphamide followed by four cycles of docetaxel (AC4-D4) versus a shorter treatment of three cycles of FEC followed by three cycles of docetaxel (FEC3-D3) in node-positive breast cancer (Neo-shorter; NCT02001506)

PURPOSE

To determine whether six cycles of FEC3-D3 has a comparable efficacy to eight of AC4-D4.

METHODS

The enrolled patients (pts) were clinically diagnosed with stage II or III breast cancer. The primary endpoint was a pathologic complete response (pCR), and the secondary endpoints were 3 year disease-free survival (3Y DFS), toxicities, and health-related quality of life (HRQoL). We calculated that 252 pts were needed in each treatment group to enable the detection of non-inferiority (non-inferiority margin of 10%).

RESULTS

In terms of ITT analysis, 248 pts were finally enrolled. The 218 pts who completed the surgery were included in the current analysis. The baseline characteristics of these subjects were well balanced between the two arms. By ITT analysis, pCR was achieved in 15/121 (12.4%) pts in the FEC3-D3 arm and 18/126 (14.3%) in the AC4-D4 arm. With a median follow up of 64.1 months, the 3Y DFS was comparable between the two arms (75.8% in FEC3-D3 vs. 75.6% in AC4-D4). The most common adverse event (AE) was Grade 3/4 neutropenia, which arose in 27/126 (21.4%) AC4-D4 arm pts vs 23/121 (19.0%) FEC3-D3 arm cases. The primary HRQoL domains were similar between the two groups (FACT-B scores at baseline, P = 0.35; at the midpoint of NACT, P = 0.20; at the completion of NACT, P = 0.44).

CONCLUSION

Six cycles of FEC3-D3 could be an alternative to eight of AC4-D4. Trial registration ClinicalTrials.gov NCT02001506. Registered December 5,2013. https://clinicaltrials.gov/ct2/show/NCT02001506.

A new prognostic model including immune biomarkers, genomic proliferation tumor markers (AURKA and MYBL2) and clinical-pathological features optimizes prognosis in neoadjuvant breast cancer patients

Background

Up to 30% of breast cancer (BC) patients treated with neoadjuvant chemotherapy (NCT) will relapse. Our objective was to analyze the predictive capacity of several markers associated with immune response and cell proliferation combined with clinical parameters.

Methods

This was a single-center, retrospective cohort study of BC patients treated with NCT (2001-2010), in whom pretreatment biomarkers were analyzed: neutrophil-to-lymphocyte ratio (NLR) in peripheral blood, CD3+ tumor-infiltrating lymphocytes (TILs), and gene expression of AURKA, MYBL2 and MKI67 using qRT-PCR.

Results

A total of 121 patients were included. Median followup was 12 years. In a univariate analysis, NLR, TILs, AURKA, and MYBL2 showed prognostic value for overall survival. In multivariate analyses, including hormone receptor, HER2 status, and response to NCT, NLR (HR 1.23, 95% CI 1.01-1.75), TILs (HR 0.84, 95% CI 0.73-0.93), AURKA (HR 1.05, 95% CI 1.00-1.11) and MYBL2 (HR 1.19, 95% CI 1.05-1.35) remained as independent predictor variables.

Conclusion

Consecutive addition of these biomarkers to a regression model progressively increased its discriminatory capacity for survival. Should independent cohort studies validate these findings, management of early BC patients may well be changed.

Noninvasive prediction of node-positive breast cancer response to presurgical neoadjuvant chemotherapy therapy based on machine learning of axillary lymph node ultrasound

OBJECTIVES

To explore an optimal model to predict the response of patients with axillary lymph node (ALN) positive breast cancer to neoadjuvant chemotherapy (NAC) with machine learning using clinical and ultrasound-based radiomic features.

METHODS

In this study, 1014 patients with ALN-positive breast cancer confirmed by histological examination and received preoperative NAC in the Affiliated Hospital of Qingdao University (QUH) and Qingdao Municipal Hospital (QMH) were included. Finally, 444 participants from QUH were divided into the training cohort (n = 310) and validation cohort (n = 134) based on the date of ultrasound examination. 81 participants from QMH were used to evaluate the external generalizability of our prediction models. A total of 1032 radiomic features of each ALN ultrasound image were extracted and used to establish the prediction models. The clinical model, radiomics model, and radiomics nomogram with clinical factors (RNWCF) were built. The performance of the models was assessed with respect to discrimination and clinical usefulness.

RESULTS

Although the radiomics model did not show better predictive efficacy than the clinical model, the RNWCF showed favorable predictive efficacy in the training cohort (AUC, 0.855; 95% CI 0.817-0.893), the validation cohort (AUC, 0.882; 95% CI 0.834-0.928), and the external test cohort (AUC, 0.858; 95% CI 0.782-0.921) compared with the clinical factor model and radiomics model.

CONCLUSIONS

The RNWCF, a noninvasive, preoperative prediction tool that incorporates a combination of clinical and radiomics features, showed favorable predictive efficacy for the response of node-positive breast cancer to NAC. Therefore, the RNWCF could serve as a potential noninvasive approach to assist personalized treatment strategies, guide ALN management, avoiding unnecessary ALND.

Comprehensive Profiling of Cancer-Associated Cells in the Blood of Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy to Predict Pathological Complete Response

Neoadjuvant chemotherapy (NAC) can affect pathological complete response (pCR) in breast cancers; the resection that follows identifies patients with residual disease who are then offered second-line therapies. Circulating tumor cells (CTCs) and cancer-associated macrophage-like cells (CAMLs) in the blood can be used as potential biomarkers for predicting pCR before resection. CTCs are of epithelial origin that undergo epithelial-to-mesenchymal transition to become more motile and invasive, thereby leading to invasive mesenchymal cells that seed in distant organs, causing metastasis. Additionally, CAMLs in the blood of cancer patients are reported to either engulf or aid the transport of cancer cells to distant organs. To study these rare cancer-associated cells, we conducted a preliminary study where we collected blood from patients treated with NAC after obtaining their written and informed consent. Blood was collected before, during, and after NAC, and Labyrinth microfluidic technology was used to isolate CTCs and CAMLs. Demographic, tumor marker, and treatment response data were collected. Non-parametric tests were used to compare pCR and non-pCR groups. Univariate and multivariate models were used where CTCs and CAMLs were analyzed for predicting pCR. Sixty-three samples from 21 patients were analyzed. The median(IQR) pre-NAC total and mesenchymal CTC count/5 mL was lower in the pCR vs. non-pCR group [1(3.5) vs. 5(5.75); p = 0.096], [0 vs. 2.5(7.5); p = 0.084], respectively. The median(IQR) post-NAC CAML count/5 mL was higher in the pCR vs. non-pCR group [15(6) vs. 6(4.5); p = 0.004]. The pCR group was more likely to have >10 CAMLs post-NAC vs. non-pCR group [7(100%) vs. 3(21.4%); p = 0.001]. In a multivariate logistic regression model predicting pCR, CAML count was positively associated with the log-odds of pCR [OR = 1.49(1.01, 2.18); p = 0.041], while CTCs showed a negative trend [Odds Ratio (OR) = 0.44(0.18, 1.06); p = 0.068]. In conclusion, increased CAMLs in circulation after treatment combined with lowered CTCs was associated with pCR.

Comparison of clinicopathological characteristics and response to neoadjuvant systemic therapy in patients with HER2-low-positive and HER2-zero breast cancer

Previous studies have observed that human epidermal growth factor receptor 2 (HER2)-low-positive patients and HER2-zero patients have different prognoses. This study was conducted to investigate whether there are differences in clinicopathological characteristics and the response to neoadjuvant systemic therapy (NST) defined as systemic treatment prior to surgery between HER2-low-positive patients and HER2-zero patients. We retrospectively analyzed the data of patients with HER2-negative breast cancer who received NST at the First Affiliated Hospital of Nanjing Medical University from 2014 to 2021. There were 238 patients with HER2-low-positive status and 198 patients with HER2-zero status. The proportion of hormone receptor (HR)-positive patients in the HER2-low-positive group was significantly higher than that in the HER2-zero group (82.8% vs 52.0%, p < 0.001). The HER2-low-positive group had more patients with low Ki67 expression (23.9% vs 16.2%, p = 0.045), higher mastectomy rate (94.5% vs 88.9%, p = 0.031), and larger pathological tumor size (21.6 vs 17.8 mm, p = 0.028) than the HER2-zero group. However, no significant differences were found in pathologic complete response (pCR) rates between the two groups. We draw a conclusion that patients with HER2-low status and HER2-zero status were not found to have different pCR rates after NST, irrespective of HR status. However, differences were observed in some clinicopathological characteristics between the two groups.

Prognostic analysis of three forms of Ki-67 in patients with breast cancer with non-pathological complete response before and after neoadjuvant systemic treatment

BACKGROUND

Patients who do not achieve a pathological complete response (pCR) after neoadjuvant systemic treatment (NST) have a significantly worse prognosis. A reliable predictor of prognosis is required to further subdivide non-pCR patients. To date, the prognostic role in terms of disease-free survival (DFS) between the terminal index of Ki-67 after surgery (Ki-67_T ) and the combination of the baseline Ki-67 at biopsy before NST (Ki-67_B ) and the percentage change in Ki-67 before and after NST (Ki-67_C ) has not been compared.

AIM

This study aimed to explore the most useful form or combination of Ki-67 that can provide prognostic information to non-pCR patients.

PATIENTS AND METHODS

We retrospectively reviewed 499 patients who were diagnosed with inoperable breast cancer between August 2013 and December 2020 and received NST with anthracycline plus taxane.

RESULTS

Among all the patients, 335 did not achieve pCR (with a follow-up period of ≥1 year). The median follow-up duration was 36 months. The optimal cutoff value of Ki-67_C to predict a DFS was 30%. A significantly worse DFS was observed in patients with a low Ki-67_C (p < 0.001). In addition, the exploratory subgroup analysis showed relatively good internal consistency. Ki-67_C and Ki-67_T were considered as independent risk factors for DFS (both p < 0.001). The forecasting model combining Ki-67_B and Ki-67_C showed a significantly higher area under the curve at years 3 and 5 than Ki-67_T (p = 0.029 and p = 0.022, respectively).

CONCLUSIONS

Ki-67_C and Ki-67_T were good independent predictors of DFS, whereas Ki-67_B was a slightly inferior predictor. The combination of Ki-67_B and Ki-67_C is superior to Ki-67_T for predicting DFS, especially at longer follow-ups. Regarding clinical application, this combination could be used as a novel indicator for predicting DFS to more clearly identify high-risk 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.

Real-world data on breast pathologic complete response and disease-free survival after neoadjuvant chemotherapy for hormone receptor-positive, human epidermal growth factor receptor-2-negative breast cancer: a multicenter, retrospective study in China

BACKGROUND

The data in the real-world setting on breast pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) for hormone receptor-positive, human epidermal growth factor receptor-2-negative (HR+, HER2-) breast cancer (BC) is limited. The present study aims to screen for some predictors and investigate the prognostic significance of breast pCR after NAC in HR+, HER2- BC in China.

METHODS

This was a multicenter, retrospective study. In this study, three hundred eighty-four HR+, HER2- BC patients who received NAC were enrolled between 2010 and 2016 from Shanghai Jiaotong University Breast Cancer Database (SJTU-BCDB). These patients were dichotomized according to the presence of breast pCR after NAC. Logistic analysis was used to screen for predictors associated with breast pCR. Kaplan-Meier (K-M) curve and a propensity score matching (PSM) analysis were performed to compare the disease-free survival (DFS) between the two groups. Cox regression was used to analyze the prognostic significance of breast pCR on DFS in HR+, HER2- BC. A nomogram model was established to predict the probability of DFS at 1, 3, and 5 years after NAC.

RESULTS

Fifty-seven patients (14.8%) achieved breast pCR. Univariate analysis showed that tumor size, estrogen receptor (ER), progesterone receptor (PR), and Ki67 were associated with breast pCR. Further, multivariate analysis showed that tumor size, PR, and Ki67 remained statistically significant. K-M curves showed a statistical difference between the breast pCR and non-pCR groups before PSM (p = 0.047), and a more significant difference was shown after PSM (p = 0.033). Cox regression after PSM suggested that breast pCR, adjuvant ET, clinical T stage, and Ki67 status were the significant predictive factors for DFS in HR+, HER2- BC patients. The adjusted hazards ratio (aHR) for breast pCR was 0.228 (95% CI, 0.070~0.739; p = 0.014), for adjuvant endocrine therapy was 0.217 (95% CI, 0.059~0.801; p = 0.022), for Ki67 was 1.027 (95% CI, 1.003~1.052; p = 0.027), for cT stages 2 and 3 compared with 1, the values were 1.331 (95% CI, 0.170~10.389), and 4.699 (95% CI, 0.537~41.142), respectively (p = 0.043). A nomogram was built based on these significant predictors, providing an integrated probability of DFS at 1, 3, and 5 years. The values of area under the receiver operating characteristic (ROC) curve (AUC) were 0.967, 0.991, and 0.787, at 1 year, 3 years, and 5 years, respectively, demonstrating the ability of the nomogram to predict the DFS.

CONCLUSIONS

This real-world study demonstrates that tumor size, PR, and Ki67 were independent predictive factors for breast pCR in HR+, HER2- BC. Breast pCR after NAC was an independent predictor for DFS in HR+, HER2- patients, regardless of a change in nodes. Furthermore, the nomogram built in our study could predict the probability of individualized DFS in HR+, HER2- BC patients.

Clinical validity and clinical utility of Ki67 in early breast cancer

Ki67 represents an immunohistochemical nuclear localized marker that is widely used in surgical pathology. Nuclear immunoreactivity for Ki67 indicates that cells are cycling and are in G1- to S-phase. The percentage of Ki67-positive tumor cells (Ki67 index) therefore provides an estimate of the growth fraction in tumor specimens. In breast cancer (BC), tumor cell proliferation rate is one of the most relevant prognostic markers and Ki67 is consequently helpful in prognostication similar to histological grading and mRNA profiling-based BC risk stratification. In BCs treated with short-term preoperative endocrine therapy, Ki67 dynamics enable distinguishing between endocrine sensitive and resistant tumors. Despite its nearly universal use in pathology laboratories worldwide, no internationally accepted consensus has yet been achieved for some methodological details related to Ki67 immunohistochemistry (IHC). Controversial issues refer to choice of IHC antibody clones, scoring methods, inter-laboratory reproducibility, and the potential value of computer-assisted imaging analysis and/or artificial intelligence for Ki67 assessment. Prospective clinical trials focusing on BC treatment have proven that Ki67, as determined by standardized central pathology assessment, is of clinical validity. Clinical utility has been demonstrated in huge observational studies.

The Impact of Tumor Infiltrating Lymphocytes Densities and Ki67 Index on Residual Breast Cancer Burden following Neoadjuvant Chemotherapy

To avoid unnecessary neoadjuvant chemotherapy in case anticipating a poor therapy response, it is essential to find the pathological parameters that would predict pathological complete response or at least a decrease in tumor burden following neoadjuvant chemotherapy. The purpose of this study is to investigate the hypothesis that tumor infiltrating lymphocytes can predict the efficacy of neoadjuvant chemotherapy and to find the Ki67 cutoff value that best predicts the benefit of chemotherapy. 153 cases of breast cancer were chosen, based on their molecular subtype: triple negative subtype (77) and luminal, HER2-ve subtype (76). Histopathological assessment of pretherapy core biopsies was conducted to assess variable pathological parameters including TILs rates with the aid of immunohistochemical staining for CD20 and CD3. Moreover, core biopsies were stained for Ki67, and the findings were compared to the residual cancer burden following neoadjuvant chemotherapy. On analyzing and contrasting the two groups, a significant association between molecular subtype and pathological complete response was confirmed, while tumor-infiltrating lymphocytes in either group had no effect on therapy response. We used receiver operating characteristic curve analysis to determine that a cutoff of 36% for Ki67 is the most accurate value to predict complete therapy response.

How Reliable Are Gene Expression-Based and Immunohistochemical Biomarkers Assessed on a Core-Needle Biopsy? A Study of Paired Core-Needle Biopsies and Surgical Specimens in Early Breast Cancer

In early breast cancer, a preoperative core-needle biopsy (CNB) is vital to confirm the malignancy of suspected lesions and for assessing the expression of treatment predictive and prognostic biomarkers in the tumor to choose the optimal treatments, emphasizing the importance of obtaining reliable results when biomarker status is assessed on a CNB specimen. This study aims to determine the concordance between biomarker status assessed as part of clinical workup on a CNB compared to a medically untreated surgical specimen. Paired CNB and surgical specimens from 259 patients that were part of the SCAN-B cohort were studied. The concordance between immunohistochemical (IHC) and gene expression (GEX) based biomarker status was investigated. Biomarkers of interest included estrogen receptor (ER; specifically, the alpha variant), progesterone receptor (PgR), Ki67, HER2, and tumor molecular subtype. In general, moderate to very good correlation in biomarker status between the paired CNB and surgical specimens was observed for both IHC assessment (83–99% agreement, kappa range 0.474–0.917) and GEX assessment (70–97% agreement, kappa range 0.552–0.800), respectively. However, using IHC, 52% of cases with low Ki67 status in the CNB shifted to high Ki67 status in the surgical specimen (McNemar’s p = 0.011). Similarly, when using GEX, a significant shift from negative to positive ER (47%) and from low to high Ki67 (16%) was observed between the CNB and surgical specimen (McNemar’s p = 0.027 and p = 0.002 respectively). When comparing biomarker status between different techniques (IHC vs. GEX) performed on either CNBs or surgical specimens, the agreement in ER, PgR, and HER2 status was generally over 80% in both CNBs and surgical specimens (kappa range 0.395–0.708), but Ki67 and tumor molecular subtype showed lower concordance levels between IHC and GEX (48–62% agreement, kappa range 0.152–0.398). These results suggest that both the techniques used for collecting tissue samples and analyzing biomarker status have the potential to affect the results of biomarker assessment, potentially also impacting treatment decisions and patient survival outcomes.

Magnetic resonance spectroscopy associations with clinicopathologic features of estrogen-dependent endometrial cancer

BACKGROUND

We studied the magnetic resonance spectroscopy (MRS) associations with clinicopathologic features of estrogen-dependent endometrial cancer (type I EC).

METHODS

Totally 45 patients with type I EC who underwent preoperative multi-voxel MRS at 3.0 T were enrolled. The mean ratio of the Cho peak integral to the unsuppressed water peak integral (Cho/water) of the tumor was calculated. The Cho/water and apparent diffusion coefficient (ADC) of type I EC with and without local invasion, as well as with different levels of Ki-67 staining index (SI) (≤ 40% and > 40%), were compared. Correlation test was used to examine the relationship of Cho/water, as well as mean ADC, with Ki-67 SI, tumor stage, and tumor grade.

RESULTS

The mean Cho/water of EC with Ki-67 SI ≤ 40% (2.28 ± 0.93) × 10^-3 was lower than that with Ki-67 SI > 40% (4.08 ± 1.00) × 10^-3 (P < 0.001). The mean Cho/water of EC with deep and superficial myometrial invasion was (3.41 ± 1.26) × 10^-3 and (2.43 ± 1.11) × 10^-3, respectively (P = 0.011). There was no significant difference in Cho/water between type I EC with and without cervical invasioin ([2.68 ± 1.00] × 10^-3 and [2.77 ± 1.28] × 10^-3, P = 0.866). The mean Cho/water of type I EC with and without lymph node metastasis was (4.02 ± 1.90) × 10^-3 and (2.60 ± 1.06) × 10^-3, respectively (P = 0.014). The Cho/water was positively correlated with the Ki-67 SI (r = 0.701, P < 0.001). There were no significant differences in ADC among groups (all P > 0.05).

CONCLUSION

MRS is helpful for preoperative assessment of clinicopathological features of type I EC.

Improved Prediction of Survival Outcomes Using Residual Cancer Burden in Combination With Ki-67 in Breast Cancer Patients Underwent Neoadjuvant Chemotherapy

We developed a model for improving the prediction of survival outcome using postoperative Ki-67 value in combination with residual cancer burden (RCB) in patients with breast cancer (BC) who underwent neoadjuvant chemotherapy (NAC). We analyzed the data from BC patients who underwent NAC between 2010 and 2019 at Samsung Medical Center and developed our residual proliferative cancer burden (RPCB) model using semi-quantitative Ki-67 value and RCB class. The Cox proportional hazard model was used to develop our RPCB model according to disease free survival (DFS) and overall survival (OS). In total, 1,959 patients were included in this analysis. Of 1,959 patients, 905 patients were excluded due to RCB class 0, and 32 were due to a lack of Ki-67 data. Finally, an RPCB model was developed using data from 1,022 patients. The RPCB score was calculated for DFS and OS outcomes, respectively (RPCB-DFS and RPCB-OS). For further survival analysis, we divided the population into 3 classes according to the RPCB score. In the prediction of DFS, C-indices were 0.751 vs 0.670 and time-dependent areas under the receiver operating characteristic curves (AUCs) at 3-year were 0.740 vs 0.669 for RPCB-DFS and RCB models, respectively. In the prediction of OS, C-indices were 0.819 vs 0.720 and time-dependent AUCs at 3-year were 0.875 vs 0.747 for RPCB-OS and RCB models, respectively. The RPCB model developed using RCB class and semi-quantitative Ki-67 had superior predictive value for DFS and OS compared with that of RCB class. This prediction model could provide the basis to decide risk-stratified treatment plan for BC patients who had residual disease after NAC.

The association between body mass index and pathological complete response in neoadjuvant-treated breast cancer patients

BACKGROUND

Obesity seems to be associated with a poorer response to adjuvant chemotherapy in breast cancer (BC); however, associations in the neoadjuvant chemotherapy (NACT) setting and according to menopausal status are less studied. This study aims to investigate the association between pretreatment body mass index (BMI) and pathological complete response (pCR) following NACT in BC according to menopausal and estrogen receptor (ER) status.

MATERIAL AND METHODS

The study cohort consisted of 491 patients receiving NACT in 2005-2019. Based on pre-NACT patient and tumor characteristics, the association between BMI and achieving pCR was analyzed using logistic regression models (crude and adjusted models (age, tumor size, and node status)) with stratification by menopausal and ER status.

RESULTS

In the overall cohort, being overweight (BMI ≥25) compared by being normal-weight (BMI <25), increased the odds of accomplishing pCR by 15%. However, based on the 95% confidence interval (CI) the data were compatible with associations within the range of a decrease of 30% to an increase of 89%. Stratification according to menopausal status also showed no strong association: the odds ratio (OR) of accomplishing pCR in overweight premenopausal patients compared with normal-weight premenopausal patients was 1.76 (95% CI 0.88-3.55), whereas for postmenopausal patients the corresponding OR was 0.71 (95% CI 0.35-1.46).

DISCUSSION

In a NACT BC cohort of 491 patients, we found no evidence of high BMI as a predictive factor of accomplishing pCR, neither in the whole cohort nor stratified by menopausal status. Given the limited precision in our results, larger studies are needed before considering BMI in clinical decision-making regarding NACT or not.

Impact of HER2 Status on Pathological Response after Neoadjuvant Chemotherapy in Early Triple-Negative Breast Cancer

PURPOSE

Investigates the link between HER2 status and histological response after neoadjuvant chemotherapy in patients with early TNBC.

METHODS

We retrieved clinical and anatomopathological data retrospectively from 449 patients treated for the first time with standard neoadjuvant chemotherapy for early unilateral BC between 2005 and 2020. The primary endpoint was pathological complete response (pCR, i.e., ypT0 ypN0), according to HER2 status. Secondary endpoints included invasive disease-free survival (I-DFS) and overall survival (OS).

RESULTS

437 patients were included, and 121 (27.7%) patients had HER2-low tumours. The pCR rate was not significantly different between the HER2-low group vs. the HER2-0 group (35.7% versus 41.8%, p = 0.284) in either univariate analysis or multivariate analysis adjusted for TNM classification and grade (odds ratio [OR] = 0.70, confidence interval [CI] 95% 0.45-1.08). With a median follow-up of 72.9 months, no significant survival differences were observed between patients with HER2-low tumours vs. patients with HER2-0 tumours in terms of I-DFS (p = 0.487) and OS (p = 0.329).

CONCLUSIONS

In our cohort, HER2 status was not significantly associated with pCR in a manner consistent with data published recently on TNBC. However, the prognostic impact of HER2-low expression among TNBC patients warrants further evaluation.

The impact of metformin use on the outcomes of locally advanced breast cancer patients receiving neoadjuvant chemotherapy: an open-labelled randomized controlled trial

Recently, several clinical trials have attempted to find evidence that supports the anticancer use of metformin in breast cancer (BC) patients. The current study evaluates the anticancer activity of metformin in addition to neoadjuvant chemotherapy (NACT) in locally advanced BC patients. Additionally, we assess the safety and tolerability of this combination and its effect on the quality of life (QoL) of BC patients. Eighty non-diabetic female patients with proven locally advanced BC were randomized into two arms. The first arm received anthracycline/taxane-based NACT plus metformin. The second arm received anthracycline/taxane-based NACT only. Overall response rate (ORR), clinical complete response (cCr), pathological complete response (pCR), and breast conservative rate (BCR) were evaluated between both groups, and correlated with serum metformin concentration. ORR, cCr, pCR, and BCR increased non-significantly in the metformin group compared to the control group; 80.6% vs 68.4%, 27.8% vs 10.5%, 22.2% vs 10.5%, and 19.4% vs 13.2%, respectively. A trend towards cCR and pCR was associated with higher serum metformin concentrations. Metformin decreased the incidence of peripheral neuropathy, bone pain, and arthralgia, although worsened the gastrointestinal adverse events. Metformin combination with NACT has no effect on the QoL of BC patients. Metformin combination with NACT is safe, tolerable, and improves non-significantly the clinical and pathological tumor response of BC patients.

Gene signatures in patients with early breast cancer and relapse despite pathologic complete response

A substantial minority of early breast cancer (EBC) patients relapse despite their tumors achieving pathologic complete response (pCR) after neoadjuvant therapy. We compared gene expression (BC360; nCounter^® platform; NanoString) between primary tumors of patients with post-pCR relapse (N = 14) with: (i) matched recurrent tumors from same patient (intraindividual analysis); and (ii) primary tumors from matched controls with pCR and no relapse (N = 41; interindividual analysis). Intraindividual analysis showed lower estrogen receptor signaling signature expression in recurrent tumors versus primaries (logFC = −0.595; P = 0.022). Recurrent tumors in patients with distant metastases also exhibited reduced expression of immune-related expression parameters. In interindividual analyses, primary tumor major histocompatibility complex class II expression was lower versus controls in patients with any relapse (logFC = −0.819; P = 0.030) or distant relapse (logFC = −1.151; P = 0.013). Primaries with later distant relapse also had greater homologous recombination deficiency than controls (logFC = 0.649; P = 0.026). Although no associations remained statistically significant following adjustment for false discovery rate, our results show that transcriptomic analyses have potential for prognostic value and may help in selecting optimal treatment regimens for EBC at risk of relapse and warrant further investigation.

Development and Validation of a New Multiparametric Random Survival Forest Predictive Model for Breast Cancer Recurrence with a Potential Benefit to Individual Outcomes

Purpose

Breast cancer (BC) is a multi-factorial disease. Its individual prognosis varies; thus, individualized patient profiling is instrumental to improving BC management and individual outcomes. An economical, multiparametric, and practical model to predict BC recurrence is needed.

Patients and Methods

We retrospectively investigated the clinical data of BC patients treated at the Third Affiliated Hospital of Sun Yat-sen University and Liuzhou Women and Children’s Medical Center from January 2013 to December 2020. Random forest-recursive feature elimination (run by R caret package) was used to determine the best variable set, and the random survival forest method was used to develop a predictive model for BC recurrence.

Results

The training and validations sets included 623 and 151 patients, respectively. We selected 14 variables, the pathological (TNM) stage, gamma-glutamyl transpeptidase, total cholesterol, Ki-67, lymphocyte count, low-density lipoprotein, age, apolipoprotein B, high-density lipoprotein, globulin, neutrophil count to lymphocyte count ratio, alanine aminotransferase, triglyceride, and albumin to globulin ratio, using random survival forest (RSF)-recursive feature elimination. We developed a recurrence prediction model using RSF. Using area under the receiver operating characteristic curve and Kaplan–Meier survival analyses, the model performance was determined to be accurate. C-indexes were 0.997 and 0.936 for the training and validation sets, respectively.

Conclusion

The model could accurately predict BC recurrence. It aids clinicians in identifying high-risk patients and making treatment decisions for Breast cancer patients in China. This new multiparametric RSF model is instrumental for breast cancer recurrence prediction and potentially improves individual outcomes.

Interobserver variability in the assessment of stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative invasive breast carcinoma influences the association with pathological complete response: the IVITA study

High stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative breast cancer (TNBC) are associated with pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). Histopathological assessment of sTILs in TNBC biopsies is characterized by substantial interobserver variability, but it is unknown whether this affects its association with pCR. Here, we aimed to investigate the degree of interobserver variability in an international study, and its impact on the relationship between sTILs and pCR. Forty pathologists assessed sTILs as a percentage in digitalized biopsy slides, originating from 41 TNBC patients who were treated with NAC followed by surgery. Pathological response was quantified by the MD Anderson Residual Cancer Burden (RCB) score. Intraclass correlation coefficients (ICCs) were calculated per pathologist duo and Bland-Altman plots were constructed. The relation between sTILs and pCR or RCB class was investigated. The ICCs ranged from -0.376 to 0.947 (mean: 0.659), indicating substantial interobserver variability. Nevertheless, high sTILs scores were significantly associated with pCR for 36 participants (90%), and with RCB class for eight participants (20%). Post hoc sTILs cutoffs at 20% and 40% resulted in variable associations with pCR. The sTILs in TNBC with RCB-II and RCB-III were intermediate to those of RCB-0 and RCB-I, with lowest sTILs observed in RCB-I. However, the limited number of RCB-I cases precludes any definite conclusions due to lack of power, and this observation therefore requires further investigation. In conclusion, sTILs are a robust marker for pCR at the group level. However, if sTILs are to be used to guide the NAC scheme for individual patients, the observed interobserver variability might substantially affect the chance of obtaining a pCR. Future studies should determine the 'ideal' sTILs threshold, and attempt to fine-tune the patient selection for sTILs-based de-escalation of NAC regimens. At present, there is insufficient evidence for robust and reproducible sTILs-guided therapeutic decisions.

A Nomogram to Predict Disease-Free Survival Following Neoadjuvant Chemotherapy for Triple Negative Breast Cancer

Background

Neoadjuvant chemotherapy (NACT) is considered a standard treatment strategy for locally advanced triple negative breast cancer (TNBC). TNBC patients who achieve a pathologic complete response (pCR) are predicted to have a better prognosis while unfavorable chemo-sensitivity is still associated with a higher risk of disease relapse. The objective of this study was to construct a nomogram to predict disease-free survival (DFS) for TNBC patients following NACT.

Methods

A total of 165 TNBC patients who underwent standard NACT and surgery were retrospectively reviewed, and data on their clinicopathological factors before and after NACT were collected. Independent prognostic factors for DFS were identified by Cox regression based on lower Akaike information criteria (AIC) and Bayesian information criterion (BIC). A nomogram to predict the 2-year and 5-year DFS following NACT for TNBC was constructed based on training cohort (n = 132) and validated by a validation cohort (n = 33).

Results

Either limited or full pCR (breast-only pCR, node-only pCR, or both-pCR) indicated significantly improved DFS and overall survival (OS) (p < 0.001). Lager residual tumor size (hazard ratio [HR] 1.175, p = 0.011) and the presence of lymphatic vessel invasion (LVI) (HR 3.168, p = 0.001) were identified as independent predictors of disease relapse in the training cohort. Five variables, including age, primary tumor size, histological grade, residual tumor size, and LVI were used to establish the nomogram. The C-index of the nomogram was 0.815, and calibration curves showed an acceptable consistency between the actual and nomogram-predicted 2-year and 5-year DFS. The proposed nomogram demonstrated superior predictive performance compared with Residual Cancer Burden (RCB) classification and the 8th American Joint Committee on Cancer Post Neoadjuvant Therapy Classification (AJCC ypTNM) staging system (area under the curve [AUC] for 2-year DFS: 0.870 vs. 0.758 vs. 0.711, respectively; AUC for 5-year DFS: 0.794 vs. 0.731 vs. 0.702, respectively) in the validation cohort.

Conclusions

The nomogram proposed in our study enabled to quantify the risk of disease relapse and demonstrated superior predictive performance than a survival predict instrument. It was an easy-to-use tool for clinicians to guide individualized surveillance of TNBC patients following standard NACT.

Plasma cell infiltration and treatment effect in breast cancer patients treated with neoadjuvant chemotherapy

Background

Tumour-infiltrating lymphocyte (TIL)-high breast tumours have a high rate of pathological complete response (pCR) with neoadjuvant chemotherapy. In our routine pathological diagnoses of biopsy specimens from pCR cases, we have observed a high infiltration of plasma cells (PCs). A positive correlation of PCs with favourable patient outcome has recently been reported, but little is known about how PCs contribute to local tumour immunity.

Methods

We retrospectively examined biopsy specimens from 146 patients with invasive breast cancer who received neoadjuvant chemotherapy. CD138⁺ PC infiltration was assessed by immunohistochemistry. Multiplexed fluorescent immunohistochemistry (mfIHC) with T and B cell markers was also conducted to elucidate the profile of immune cells.

Results

Greater PC infiltration was observed in the pCR group (p = 0.028) and this trend was confirmed in another patient cohort. With mfIHC, we observed significantly more CD8⁺, T-bet⁺CD4⁺, and CD8⁺FOXP3⁺ T cells, total B cells and PCs in pCR cases. Such cases were also characterised by high expression of both PD-1 and PD-L1 on B cells and PCs. In patients with hormone receptor-negative tumours, high PC infiltration was correlated with significantly longer disease-free survival (p = 0.034).

Conclusions

We found that higher PC infiltration in biopsy specimens before neoadjuvant chemotherapy was associated with pCR. With mfIHC, we also revealed that the local cytotoxic immune response was clearly enhanced in pCR cases, as was the infiltration of B cells including PCs. Moreover, higher PC levels were correlated with favourable outcomes in hormone receptor-negative breast cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01477-w.

Which Clinicopathologic Parameters Suggest Primary Resistance to Palbociclib in Combination With Letrozole as the First-Line Treatment for Hormone Receptor-Positive, HER2-Negative Advanced Breast Cancer?

In this study, we evaluated clinical parameters to predict the primary resistance of palbociclib in combination with endocrine therapy as the first-line treatment in patients with hormone receptor (HR)+, human epidermal growth factor receptor 2 (HER2)- metastatic breast cancer (MBC). We performed a data analysis of patients diagnosed with HR+, HER2-MBC who received palbociclib plus letrozole as the first-line treatment in the metastatic setting from the clinical data warehouse in Samsung Medical Center. In this study, 305 patients were included in the final data analysis. The median follow-up duration was 31 months, and we observed 123 cases of disease progression. The median progression-free survival (PFS) was 28.7 months, and 38 patients (12.5%) had less than a 6-month PFS. The multivariate analysis suggested that primary resistance to adjuvant endocrine therapy (ET) (hazard ratio: 1.91), presence of liver metastasis (hazard ratio: 2.17), initial elevation of serum CA-15-3 (hazard ratio: 1.99), weak positivity of estrogen receptor (ER) (hazard ratio: 2.28), Ki-67 3+ or 4+ (hazard ratios: 2.58 and 10.28), and presence of mutation (hazard ratio: 9.59) were associated with a short PFS duration. A further prediction model was developed with data from 256 patients and 33 cases of disease progression in 6 months. This model included five factors-primary resistance to adjuvant ET (odds ratio, OR: 1.14), liver metastasis (OR: 1.56), initial CA-15-3 elevation (OR: 1.51), weak ER expression (OR: 2.22), and BRCA2 mutation (OR: 2.85)-and the area under the receiver operating characteristic curve was 0.842 (95% CI: 0.775, 0.909; p < 0.001). Finally, we divided them into four risk groups according to the prediction model with the five risk factors. These four groups had different PFS (p < 0.001) and primary resistance of palbociclib with letrozole [OR of group 2 vs. group 1 (ref): 2.18 (p = 0.002), OR of group 3: 3.91 (p < 0.001), and OR of group 4: 4.25 (p < 0.001)]. We developed a prediction model of primary resistance to palbociclib with letrozole as the first-line treatment for HR+, HER2-MBC. Our prediction model might be helpful for considering the first-line treatment strategies. Further well-designed clinical trials would be warranted to validate our prediction model.

MicroRNA Expression Profiles and Breast Cancer Chemotherapy

Breast cancer is the most common malignancy diagnosed in women. Traditionally, radical surgical resection was the cornerstone of breast cancer management, with limited exceptions. In recent times, our enhanced appreciation of the biomolecular characteristics of breast cancer has transformed the treatment paradigm to include prescription of chemotherapeutical agents, radiotherapies, targeted therapies, as well as more refined surgical approaches. While treatments with such modalities have enhanced clinico-oncological outcomes for breast cancer patients, the efforts of oncological and translational research have concentrated on the identification of novel biomarkers which may successfully inform prognosis and response to therapies, improve current therapeutic strategies, and enhance prognostication. Mi(cro)RNAs are small, non-coding molecules which are known to play regulatory roles in governing gene expression and cellular activity. Measurement of miRNA expression profiles have been illustrated to inform the response to therapies, such as conventional chemotherapy, and are currently undergoing assessment as means of enhancing treatment strategies with these cytotoxic agents. Herein, this review outlines how chemotherapy prescription has revolutionised breast cancer treatment and illustrates the novel role of miRNAs as biomarkers capable of enhancing current therapeutic strategies using chemotherapy in patients being treated with curative intent for breast cancer.

Ki67 as Proliferative Marker in Patients with Early Breast Cancer and Its Association with Clinicopathological Factors

INTRODUCTION

Ki67 as a proliferative marker has prognostic and therapeutic relevance in early breast cancer (EBC). However, standard cutoffs for distinguishing low and high Ki67 do not exist.

MATERIAL AND METHODS

Data from all patients treated at the University Hospital Ulm for EBC between January 2013 and December 2015 with documented results for internal Ki67 assessment of the primary (n = 917) tumor were retrospectively analyzed evaluating the associations between Ki67 and other clinicopathological factors.

RESULTS

595 (64.9%) patients had a Ki67 <20% and 322 (35.1%) a Ki67 ≥20%. The median Ki67 was 10% (range 1-90%). Median Ki67 values according to the hormone receptor (HR)/ human epidermal growth factor receptor 2 (HER2) subtypes were 10% for HR-positive/HER2 negative (HR+/HER2-) disease (n = 717), 20% for HR+/HER2+ (n = 76), 30% for HR-/HER2+ (n = 45), and 60% for HR-/HER2- (n = 75). 75.2% or 89.3% of all patients with HER2-positive or triple-negative disease had a Ki67 ≥20%, respectively. Using a multivariable logistic regression with Ki67 (<20% vs. ≥20%) as binary dependent variable, younger age, positive nodal status, higher grading, histological nonspecific type carcinoma, negative HR status, and positive HER2 status were shown to be significantly associated with a higher proliferative index (Ki67 ≥20%).

CONCLUSION

This analysis described Ki67 in different subtypes in EBC and its association with clinicopathological factors. According to more aggressive tumor biology, the respective subgroups also showed higher median Ki67 levels. However, definition of low and high proliferation index itself is difficult. It is essential to interpret Ki67 indices carefully with regard to the own institutional values and other clinicopathological factors.

Ki-67 and Its Relation With Complete Pathological Response in Patients With Breast Cancer

Introduction

Ki-67 is a nuclear antigen present in the synthesis phase of the cell cycle. Studies have shown that a high value of Ki-67 results in greater response to chemotherapy with higher incidence of complete pathological response, which ultimately results in improved overall survival.

Methods and materials

The objective of the study was to determine the frequency of high Ki-67 levels in breast cancer patients and to find the correlation of complete pathological response in breast cancer with Ki-67 levels. It is a descriptive case series with a correlational study design done at Fauji Foundation Hospital Rawalpindi. Eighty patients with locally advanced breast cancer who underwent neoadjuvant chemotherapy followed by surgery were recruited. Their Ki-67 levels were determined on trucut biopsy. Pathological response in the post-op sample was correlated with Ki-67 levels.

Results

The results showed 27 (33%) patients out of the 80 had high Ki-67 values. Among them 17 (63%) had complete pathological response, seven (26%) showed partial pathological response whereas three (11%) had disease progression. In contrast, out of the 53 patients having low Ki-67 values, only nine (17%) had complete pathological response, 31 (58%) showed partial pathological response and 13 (25%) had progressive disease. A Chi-square test was applied which showed significant correlation between Ki-67 and complete pathological response, with a p value of 0.00018.

Conclusion

Therefore high Ki-67 values in patients with breast cancer correlated well with attainment of complete pathological response. We can incorporate Ki-67 in the initial clinical assessment of breast cancer patients to help predict effectiveness as well as response to chemotherapy.

Prediction of Late Recurrence and Distant Metastasis in Early-stage Breast Cancer: Overview of Current and Emerging Biomarkers

Recently, a significant number of breast cancer (BC) patients have been diagnosed at an early stage. It is therefore critical to accurately predict the risk of recurrence and distant metastasis for better management of BC in this setting. Clinicopathologic patterns, particularly lymph node status, tumor size, and hormonal receptor status are routinely used to identify women at increased risk of recurrence. However, these factors have limitations regarding their predictive ability for late metastasis risk in patients with early BC. Emerging molecular signatures using gene expression-based approaches have improved the prognostic and predictive accuracy for this indication. However, the use of their based-scores for risk assessment has provided contradictory findings. Therefore, developing and using newly emerged alternative predictive and prognostic biomarkers for identifying patients at high- and low-risk is of great importance. The present review discusses some serum biomarkers and multigene profiling scores for predicting late recurrence and distant metastasis in early-stage BC based on recently published studies and clinical trials.

Machine learning classification of texture features of MRI breast tumor and peri-tumor of combined pre- and early treatment predicts pathologic complete response

Purpose

This study used machine learning classification of texture features from MRI of breast tumor and peri-tumor at multiple treatment time points in conjunction with molecular subtypes to predict eventual pathological complete response (PCR) to neoadjuvant chemotherapy.

Materials and method

This study employed a subset of patients (N = 166) with PCR data from the I-SPY-1 TRIAL (2002–2006). This cohort consisted of patients with stage 2 or 3 breast cancer that underwent anthracycline–cyclophosphamide and taxane treatment. Magnetic resonance imaging (MRI) was acquired pre-neoadjuvant chemotherapy, early, and mid-treatment. Texture features were extracted from post-contrast-enhanced MRI, pre- and post-contrast subtraction images, and with morphological dilation to include peri-tumoral tissue. Molecular subtypes and Ki67 were also included in the prediction model. Performance of classification models used the receiver operating characteristics curve analysis including area under the curve (AUC). Statistical analysis was done using unpaired two-tailed t-tests.

Results

Molecular subtypes alone yielded moderate prediction performance of PCR (AUC = 0.82, p = 0.07). Pre-, early, and mid-treatment data alone yielded moderate performance (AUC = 0.88, 0.72, and 0.78, p = 0.03, 0.13, 0.44, respectively). The combined pre- and early treatment data markedly improved performance (AUC = 0.96, p = 0.0003). Addition of molecular subtypes improved performance slightly for individual time points but substantially for the combined pre- and early treatment (AUC = 0.98, p = 0.0003). The optimal morphological dilation was 3–5 pixels. Subtraction of post- and pre-contrast MRI further improved performance (AUC = 0.98, p = 0.00003). Finally, among the machine-learning algorithms evaluated, the RUSBoosted Tree machine-learning method yielded the highest performance.

Conclusion

AI-classification of texture features from MRI of breast tumor at multiple treatment time points accurately predicts eventual PCR. Longitudinal changes in texture features and peri-tumoral features further improve PCR prediction performance. Accurate assessment of treatment efficacy early on could minimize unnecessary toxic chemotherapy and enable mid-treatment modification for patients to achieve better clinical outcomes.

Correlation between semiquantitative and volumetric 18F-FDG PET/computed tomography parameters and Ki-67 expression in breast cancer

OBJECTIVES

To evaluate the relationship between semiquantitative and volumetric parameters on 18F-FDG PET/computed tomography (CT), including maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), tumor to liver ratio (TLR) and tumor to mediastinum ratio (TMR) with the level of Ki-67 expression in breast cancer.

PATIENT AND METHODS

We retrospectively reviewed 105 female patients with newly diagnosed breast cancer who underwent baseline 18F-FDG PET/CT and had immunohistochemical staining to determine the level of Ki-67 expression. The following PET parameters were measured (SUVmax, SUVmean, MTV, TLG, TLR and TMR) and correlated with level of Ki-67 expression.

RESULTS

Significant moderate positive correlations were found between the PET parameters (primary SUVmax, SUVmean, TLG, TLR and TMR) and level of Ki-67 expression. The primary SUVmax had the highest correlation coefficient (r = 0.461) followed by TMR (r = 0.455) and P value of <0.001 for both. In ROC analysis, primary SUVmax had the largest area under the curve (0.806, P = 0.0001), with sensitivity of 76.5 % and specificity of 75% for prediction of high Ki-67 level. In univariate analysis, all PET parameters, patient age, tumor grade, molecular subtype, estrogen receptor and progesterone receptor status were significantly associated with Ki-67 level. In multivariate regression analysis, only tumor grade [odds ratio (OR) = 20.460, 95% confidence interval (CI): 11.360-29.559, P = <0.0001], molecular subtype (OR = -21.894, 95% CI: -37.921 to -5.866, P = 0.008), SUVmax (OR = 2.299, 95% CI: 0.703-3.895, P = 0.005) and TLR (OR = -4.908, 95% CI: -9.476 to -0.340, P = 0.035) were found to be the strongest independent predictor factors for the level of Ki-67 expression and hence proliferative activity of malignant cells in breast cancer.

CONCLUSION

The semiquantitative parameters and volumetric 18F-FDG PET/CT parameter, that is, TLG correlated well with proliferation marker Ki-67 in breast cancer. 18F-FDG PET/CT imaging can be used as a useful noninvasive diagnostic tool in imaging cellular proliferation and hence may substitute for in vitro testing of molecular markers in the diagnoses and staging of breast cancer.

Prognostic relevance of Ki67 expression in primary male breast cancer: determination of cut-off points by different evaluation methods and statistical examinations

PURPOSE

1% of all breast cancer cases occur in men. There are significant differences regarding clinical behaviour and genetic profiles between female (FBC) and male breast cancer (MBC). Parameters for decision-making on treatment and prognosis are derived from FBC. Ki67 has a high value as a prognostic and predictive factor in FBC, but accurate Ki67 cut-off points for MBC are missing. In this study, we aimed to evaluate adequate examination methods and reliable cut-off points for Ki67 to assess the highest prognostic value for patient's overall survival (OS).

METHODS

In this multicentric retrospective study, histological specimens were obtained from 104 male patients who were diagnosed and treated for primary invasive breast cancer. We applied three methods of Ki67 analysis: Tumor average scoring (TA), tumor border scoring (TB) and hot-spot scoring (HS). Calculated Ki67 cut-off points for each method were assessed as a threshold for patients' overall survival (OS).

RESULTS

Ki67 cut-off points were 13.5 for the TA group, 22.5 for the HS group and 17.5 for the TB group. Only Ki67 TA cut-off calculations demonstrated statistical significance (p = 0.04). Ki67 expression analysis of TA showed that more than 90% of patients with low Ki67 levels (< 13.5) were alive after 5-year follow-up.

CONCLUSION

Our findings demonstrate that determination of Ki67 expression in TA is the most reliable to define a cut-off point with high prognostic value. A Ki67 cut-off point of 13.5 shows highest statistical power to define luminal A subgroup and OS.

Can We Reliably Identify the Pathological Outcomes of Neoadjuvant Chemotherapy in Patients with Breast Cancer? Development and Validation of a Logistic Regression Nomogram Based on Preoperative Factors

BACKGROUND

Pathological responses of neoadjuvant chemotherapy (NCT) are associated with survival outcomes in patients with breast cancer. Previous studies constructed models using out-of-date variables to predict pathological outcomes, and lacked external validation, making them unsuitable to guide current clinical practice.

OBJECTIVE

The aim of this study was to develop and validate a nomogram to predict the objective remission rate (ORR) of NCT based on pretreatment clinicopathological variables.

METHODS

Data from 110 patients with breast cancer who received NCT were used to establish and calibrate a nomogram for pathological outcomes based on multivariate logistic regression. The predictive performance of this model was further validated using a second cohort of 55 patients with breast cancer. Discrimination of the prediction model was assessed using an area under the receiver operating characteristic curve (AUC), and calibration was assessed using calibration plots. The diagnostic odds ratio (DOR) was calculated to further evaluate the performance of the nomogram and determine the optimal cut-off value.

RESULTS

The final multivariate regression model included age, NCT cycles, estrogen receptor, human epidermal growth factor receptor 2 (HER2), and lymphovascular invasion. A nomogram was developed as a graphical representation of the model and showed good calibration and discrimination in both sets (an AUC of 0.864 and 0.750 for the training and validation cohorts, respectively). Finally, according to the Youden index and DORs, we assigned an optimal ORR cut-off value of 0.646.

CONCLUSION

We developed a nomogram to predict the ORR of NCT in patients with breast cancer. Using the nomogram, for patients who are operable and whose ORR is < 0.646, we believe that the benefits of NCT are limited and these patients can be treated directly using surgery.

Comparison of breast cancer surrogate subtyping using a closed-system RT-qPCR breast cancer assay and immunohistochemistry on 100 core needle biopsies with matching surgical specimens

Background

Routine clinical management of breast cancer (BC) currently depends on surrogate subtypes according to estrogen- (ER) and progesterone (PR) receptor, Ki-67, and HER2-status. However, there has been growing demand for reduced immunohistochemistry (IHC) turnaround times. The Xpert® Breast Cancer STRAT4* Assay (STRAT4)*, a standardized test for ESR1/PGR/MKi67/ERBB2 mRNA biomarker assessment, takes less than 2 hours. Here, we compared the concordance between the STRAT4 and IHC/SISH, thereby evaluating the effect of method choice on surrogate subtype assessment and adjuvant treatment decisions.

Methods

In total, 100 formalin-fixed paraffin-embedded core needle biopsy (CNB) samples and matching surgical specimens for 98 patients with primary invasive BC were evaluated using the STRAT4 assay. The concordance between STRAT4 and IHC was calculated for individual markers for the CNB and surgical specimens. In addition, we investigated whether changes in surrogate BC subtyping based on the STRAT4 results would change adjuvant treatment recommendations.

Results

The overall percent agreement (OPA) between STRAT4 and IHC/SISH ranged between 76 and 99% for the different biomarkers. Concordance for all four biomarkers in the surgical specimens and CNBs was only 66 and 57%, respectively. In total, 74% of surgical specimens were concordant for subtype, regardless of the method used. IHC- and STRAT4-based subtyping for the surgical specimen were shown to be discordant for 25/98 patients and 18/25 patients would theoretically have been recommended a different adjuvant treatment, primarily receiving more chemotherapy and trastuzumab.

Conclusions

A comparison of data from IHC/in situ hybridization and STRAT4 demonstrated that subsequent changes in surrogate subtyping for the surgical specimen may theoretically result in more adjuvant treatment given, primarily with chemotherapy and trastuzumab.

Prognostic role of serum thymidine kinase 1 kinetics during neoadjuvant chemotherapy for early breast cancer

Background

Emerging data support the use of thymidine kinase 1 (TK1) activity as a prognostic marker and for monitoring of response in breast cancer (BC). The long-term prognostic value of TK1 kinetics during neoadjuvant chemotherapy is unclear, which this study aimed to elucidate.

Methods

Material from patients enrolled to the single-arm prospective PROMIX trial of neoadjuvant epirubicin, docetaxel and bevacizumab for early BC was used. Ki67 in baseline biopsies was assessed both centrally and by automated digital imaging analysis. TK1 activity was measured from blood samples obtained at baseline and following two cycles of chemotherapy. The associations of TK1 and its kinetics as well as Ki67 with event-free survival and overall survival (OS) were evaluated using multivariable Cox regression models.

Results

Central Ki67 counting had excellent correlation with the results of digital image analysis (r = 0.814), but not with the diagnostic samples (r = 0.234), while it was independently prognostic for worse OS [adjusted hazard ratio (HR_adj) = 2.72, 95% confidence interval (CI) 1.19-6.21, P = 0.02]. Greater increase in TK1 activity after two cycles of chemotherapy resulted in improved event-free survival (HR_adj = 0.50, 95% CI 0.26-0.97, P = 0.04) and OS (HR_adj = 0.46, 95% CI 0.95, P = 0.04). There was significant interaction between the prognostic value of TK1 kinetics and Ki67 (p_interaction 0.04).

Conclusion

Serial measurement of serum TK1 activity during neoadjuvant chemotherapy provides long-term prognostic information in BC patients. The ease of obtaining serial samples for TK1 assessment motivates further evaluation in larger studies.

•

This is a correlative analysis of a prospective phase II study on neoadjuvant chemotherapy for breast cancer.

•

Serial measurement of serum TK1 activity during treatment provides independent long-term prognostic information.

•

We demonstrate the validity and clinical utility of both central and automated image analysis-based Ki67 assessment.

•

Finally, we explore the biologic correlations between TK1 and Ki67.

Neoadjuvant chemotherapy in hormone receptor-positive/HER2-negative early breast cancer: When, why and what?

Indication for neoadjuvant chemotherapy (NACT) in HR+/HER2-negative tumors is controversial. Pathological complete response (pCR) rates range from 0 to 18 % while breast-conserving surgery (BCS) is achievable in up to 60 % of tumors. No pathological feature definitely predicts pCR; lobular and molecular luminal A tumors are less likely to achieve pCR although experiencing better outcomes. Luminal B subtype, high proliferation, lack of progesterone receptor, high tumor-infiltrating lymphocytes are positively associated with increased pCR rates but worse outcomes and the prognostic role of pCR is inconsistent across studies. Molecular intrinsic subtyping and genomic signatures appear as more accurate predictors of benefit from NACT, but larger studies are needed. Anthracycline and taxane-based chemotherapy remains the standard NACT; however, CDK 4/6 inhibitors and immune checkpoint inhibitors are under evaluation. In conclusion, NACT may be proposed for luminal tumors requiring downsizing for BCS after multidisciplinary evaluation, provided that other contraindications to BCS are excluded.

Ki67 Immunohistochemistry Quantification in Breast Carcinoma: A Comparison of Visual Estimation, Counting, and ImmunoRatio

BACKGROUND

Molecular analysis has shown that breast carcinomas can be classified into several intrinsic subtypes, with implications for management and prognosis. In the majority of pathology laboratories molecular analysis of each case is not possible and immunohistochemistry is used for subtyping. This includes analysis of hormone receptors as well as HER2-neu and Ki67. The methodology for the interpretation of the proliferation index using Ki67 remains an area of uncertainty. We investigated the degree of agreement between different methods of Ki67 interpretation.

MATERIALS AND METHODS

We analyzed 204 breast core biopsies diagnostic of breast carcinoma using visual estimation/eyeballing (EB), ImmunoRatio, and counting by 2 pathologists (CP1 and CP2). The correlation between the different methods and the interobserver agreement between the 2 pathologists was assessed. Specific analysis was also done with respect to classification of cases into low Ki67 groups (using Ki67 values<14% and <20%) since this is critical in classifying tumors into luminal A and luminal B subtypes.

RESULTS

Correlation between the different methods was best achieved comparing ImmunoRatio and CP1, and worst comparing CP1 and EB. Correlation was better when considering interobserver variability (CP1 vs. CP2). Comparing the number of cases classified as low Ki67 (<14% and <20%) the Cohen κ statistic varied from κ=0.267 to 0.814 with different methods. When limiting the analysis to cases with a Ki67 of 10% to 25% according to any method, there was greater disagreement.

CONCLUSIONS

At the higher and lower Ki67 levels, the correlation between the methods of assessment was acceptable, however, at levels close to the cut-off values for lumial A versus luminal B, several patients would be differently classified by the different methods and therefore potentially receive suboptimal management.

Selection of neoadjuvant treatment based on the 21-GENE test results in luminal breast cancer

Neoadjuvant chemotherapy (NAC) is an optimal option in early breast cancer, but in ER-positive/HER2-negative (luminal) is still controversial, although a survival benefit has recently been observed when a histological response by Symmans’ method type 0 or I is achieved. The 21-gene Oncotype DX Breast Recurrence Score® assay (Oncotype DX®) is a validated test to assess the survival benefit of adjuvant chemotherapy in these patients but its role in the neoadjuvant setting is less established. We analyzed the results of the Oncotype DX® test in a cohort of 122 consecutive patients selected to receive NAC based on classical clinicopathological parameters and the correlation between the Oncotype DX® results and the pathological response assessed by Symmans’ method. Median age was 56.5 (range 31–84) years. Initial tumor size was T1 (<20 mm) in 46 patients (37.7%), 57 (46.7%) had a T2 tumor (20–50 mm), and 19 (15.6%) had a tumor size more than 50 mm. 59 (48.4%) had axillary node involvement. The median expression estrogen and progesteron receptors by immunohistochemistry was 280 and 120 respectively and median Ki67 index was 28%. The Recurrence Score (RS) results were <11 in 21 patients (17.2%) patients, RS 11 to 25 in 58 (47.5%), and RS > 25 in 43 (35.2%). Considering the Oncotype DX test results, neoadjuvant chemotherapy was administered to 60 patients (49%), 11 (9%) received adjuvant chemotherapy and 51 (42%) no chemotherapy. Testing with the assay has therefore led to 42% fewer chemotherapy treatments. Among 60 patients receiving NAC, pathologic response was achieved for 5 patients (8.3%) with RCB-0 and 15 RCB-1 (25%). We did not find any pathological response RCB-0 and RCB-I in the 20 patients who received NAC and had a Recurrence Score result <21 for the premenopausal group, or a RS result <25 for the postmenopausal group. For patients with highest Recurrence Score results (RS > 21 or 25 according to menopausal status) it was 12% (5/40) RCB-0 and 40% (16/40) RCB-I.

Conclusions

The Oncotype DX test could be a useful tool to select patients candidates for neoadjuvant chemotherapy in luminal breast cancer. Neoadjuvant chemotherapy could be avoided in 42% of patients. We found a correlation between Recurrence Score results and pathological response with 14% of RCB-0 and a total of 47% of significant pathological response type RCB-0 and RCB-I in patients with highest Recurrence Score results. Interestingly, patients with a Recurrence Score result inferior to 32 did not get any histological response type 0 and only 5% RCB-I.

•

All comments are reviewed in the main manuscript text.

•

We have introduced changes in tables and Figures according Editor′s comments.

•

It is an academic study and we don′t received any founding and we appreciate all patients who participated.

Concomitant use of 18F-FDG PET-CT SUVmax is useful in the assessment of Ki67 labeling index in core-needle biopsy specimens of breast cancer

Background

Ki67 is a recognized proliferative and predictive marker in invasive breast cancer. However, results of Ki67 evaluation are affected by the method employed for sample fixation or biopsy, as well as by intratumor heterogeneity. Here, we aimed to compare the Ki67 labeling index (Ki67LI) between core-needle biopsy specimens (CNBSs) and surgically resected specimens (SRSs) of invasive breast cancer, and verify whether the discordance in Ki67LI can be reduced by analyzing the maximum standardized uptake value (SUVmax) obtained from pretreatment whole-body positron emission tomography/computed tomography (PET/CT) in combination with Ki67LI.

Methods

Tumor tissues were obtained from 118 patients with invasive breast cancer. Ki67LI was evaluated in CNBSs and SRSs by immunohistochemistry. First, we directly compared Ki67LI between CNBS and SRS, "allowing a tolerance margin of 5%." We divided the Ki67LI values into three groups (Low: 0≤ Ki67LI ≤10, Intermediate: 10< Ki67LI <30, and High: 30≤ Ki67LI) and the SUVmax into three groups (SUVmax ≤4, 4< SUVmax <8, and 8≤ SUVmax). We then verified the concordance rate between CNBS and SRS in each group in combination with the SUVmax obtained by PET/CT.

Results

The median Ki67LI was 17.8% (0.5-75.9%) and 17.0% (1.0-75.7%) in CNBS and SRS, respectively. The overall Ki67LI concordance rate between CNBS and SRS was 37.3% (44/118). The concordance was improved in the Low and High Ki67LI groups by applying SUVmax thresholds of 4 [82.6% (19/23), P=0.033 and 8 (92.3% (12/13), P=0.009], respectively.

Conclusions

Our results indicated that CNBS Ki67LI alone was not able to reflect SRS Ki67LI with sufficient accuracy. By dividing CNBS Ki67LI into three classes in combination with SUVmax, tumor proliferation could be predicted with higher accuracy in patients with invasive breast carcinoma.

Current Biomarkers for Precision Medicine in Breast Cancer

Breast cancer has become the prototypical solid tumor where targets have been identified within the tumor allowing for personalized approach for systemic therapy. Biomarkers are beginning to play an important role in preparing the way for precision treatment. Mandatory biomarkers for every newly diagnosed case of breast cancer are estrogen receptors and progesterone receptors in selecting patients for endocrine treatment and HER2 for identifying patients likely to benefit from antiHER2 therapy. Although methodological problems exist in the determination of Ki67, because of its clearly established clinical value, wide availability, and low costs relative to the available multianalyte signatures, Ki67 may be used for determining prognosis, especially if values are low or high. Also, the androgen receptor (AR) pathway is emerging as a potential therapeutic target in breast cancer. AR-targeted treatments for breast cancer are in development and have shown promising preliminary results. While, most established biomarkers in breast cancer require tissue samples, serum tumor markers are easily accessible and require a less invasive procedure. Among them, tissue polypeptide-specific antigen (TPS), a specific epitope structure of a peptide in serum associated with human cytokeratin 18, is linked to the proliferative activity of tumors. TPS may be a valuable and independent prognostic biomarker for breast cancer.In order to accelerate progress towards precision treatment for women with breast cancer, we need additional predictive biomarker, especially for enhancing the positive predictive value for endocrine and antiHER2 therapies, as well as biomarkers for predicting response to specific forms of chemotherapy.

Neoadjuvant Chemotherapy for Breast Cancer: Past, Present, and Future

Neoadjuvant chemotherapy (NAC) had been developed as a systematic approach before definitive surgery for the treatment of locally advanced or inoperable breast cancer such as inflammatory breast cancer in the past. In addition to its impact on surgery, the neoadjuvant setting has a benefit of providing the opportunity to monitor the individual drug response. Currently, the subject of NAC has expanded to include patients with early-stage, operable breast cancer because it is revealed that the achievement of a pathologic complete response (pCR) is associated with excellent long-term outcomes, especially in patients with aggressive phenotype breast cancer. In addition, this approach provides the unique opportunity to escalate adjuvant therapy in those with residual disease after NAC. Neoadjuvant chemotherapy in breast cancer is a rapidly evolving topic with tremendous interest in ongoing clinical trials. Here, we review the improvements and further challenges in the NAC setting in translational breast cancer research.

The diagnostic performance of quantitative mapping in breast cancer patients: a preliminary study using synthetic MRI

Background

Previous studies have indicated that quantitative MRI (qMR) is beneficial for diagnosis of breast cancer. As a novel qMR technology, synthetic MRI (syMRI) may be advantageous by offering simultaneous generation of T1 and T2 mapping in one scan within a few minutes and without concern to the deposition of the gadolinium contrast agent in cell nucleus. In this study, the potential of quantitative mapping derived from Synthetic MRI (SyMRI) to diagnose breast cancer was investigated.

Methods

From April 2018 to May 2019, a total of 87 patients with suspicious breast lesions underwent both conventional and SyMRI before treatment. The quantitative metrics derived from SyMRI, including T1 and T2 values, were measured in breast lesions. The diagnostic performance of SyMRI was evaluated with unpaired Student’s t-tests, receiver operating characteristic curve analysis and multivariate logistic regression analysis. The AUCs of quantitative values were compared using Delong test.

Results

Among 77 patients who met the inclusion criteria, 48 were diagnosed with histopathological confirmed breast cancers, and the rest had benign lesions. The breast cancers showed significantly higher T1 (1611.61 ± 215.88 ms) values and lower T2 (80.93 ± 7.51 ms) values than benign lesions. The area under the ROC curve (AUC) values were 0.931 (95% CI: 0.874–0.989) and 0.883 (95% CI: 0.810–0.956) for T1 and T2 maps, respectively, in diagnostic discrimination between breast cancers and benign lesions. A slightly increased AUC of 0.978 (95% CI: 0.915–0.993) was achieved by combining those two relaxation-based quantitative metrics.

Conclusion

In conclusion, our preliminary study showed that the quantitative T1 and T2 values obtained by SyMRI could distinguish effectively between benign and malignant breast lesions, and T1 relaxation time showed the highest diagnostic efficiency. Furthermore, combining the two quantitative relaxation metrics further improved their diagnostic performance.

Study of Ki-67 index in the molecular subtypes of breast cancer: Inter-observer variability and automated scoring

Background

Ki-67 index is an important prognostic marker in breast cancer and is also used to differentiate luminal A subtype from luminal B. Inter-observer variations in determining the index and the cut-off value to be considered in distinguishing the two subtypes remain problems in clinical practice.

Methods

MIB-1 immunohistochemistry was done on 200 cases of breast cancer with 50 cases in each molecular subtype. The Ki-67 scoring was done manually by two observers and automated method (using the software ImmunoRatio). The mean value of Ki-67 was calculated in each molecular group and in the entire estrogen receptor and progesterone receptor (ER/PR) positive group. The inter-observer variability between the two observers and the automated method was also assessed.

Results

The mean and median values of Ki-67 of all the 200 cases obtained by manual scoring was 31.13% and 29.65% by observer 1, 28.48% and 27.90% by observer 2, and 38.27% and 35.45% by the automated method. The mean Ki-67 value obtained by manual scoring, in luminal A, luminal B, HER2 enriched and triple negative was 21.07%, 37.19%, 33.72% and 27.27%, respectively. There was significant correlation between the two observers and with the automated scoring.. The mean value of the Ki-67 index in the ER/PR positive group was 29.1%.

Conclusion

The inter-observer correlation and the correlation with the automated scoring system of the Ki-67 index was good. 29.1% was the mean Ki-67 index in the ER/PR positive group and this value was within the acceptable range as per St Galen's recommendation.