Predictive factors of pathologic complete response of HER2-positive breast cancer after preoperative chemotherapy with trastuzumab: development of a specific predictor and study of its utilities using decision curve analysis

Preoperative systemic inflammation response index: Clinicopathologic predictor of pathological complete response in HER2-positive breast cancer patients receiving neoadjuvant systemic therapy

BACKGROUND

Multiple pretreatment systemic inflammatory markers (SIMs) have been reported as predictors of pathological complete response (pCR) after neoadjuvant systemic therapy (NST) in patients with breast cancer (BC). However, the most significant SIM remains to be conclusively identified, and variations among different molecular subtypes remain unknown. The objective of the study was to identify the most significant SIM in patients with human epidermal growth factor receptor 2 (HER2) positive BC, to construct a pCR-predictive nomogram combining it with other clinicopathologic factors, and to evaluate its prognostic value on survival.

METHODS

We retrospectively reviewed the findings for 240 patients with stage I-III HER2-positive BC who underwent NST and subsequent surgery at Kaohsiung and Taichung Veterans General Hospital from 2011 to 2021. Clinicopathologic factors were analyzed by stepwise logistic regression with backward selection. The data were used to construct a nomogram plot for determining the pCR probability. Kaplan-Meier curves and log-rank test were used to evaluate disease-free survival (DFS) and overall survival (OS).

RESULTS

Among the pretreatment SIMs, only the systemic inflammation response index (SIRI) was significantly related to pCR, with an optimal cutoff value of 1.27 × 10 9 /L. Stepwise logistic analyses indicated that clinical N stage, HER2 immunohistochemistry score, hormone receptor status, targeted therapy regimen, and SIRI were independent predictors of pCR, with an area under the curve of 0.722. The Hosmer-Lemeshow test and calibration curve revealed that the predictive ability was a good fit to actual observations. A nomogram was constructed based on the logistic model. The external validation of the model also revealed satisfactory discrimination and calibration. Kaplan-Meier analysis showed that patients with SIRI <1.27 had longer DFS and OS.

CONCLUSION

Pretreatment SIRI <1.27 is predictive of pCR, DFS, and OS in HER2-positive BC. Our nomogram could efficiently predict pCR and facilitate clinical decision-making before neoadjuvant treatment.

Factors affecting pathological complete response after neoadjuvant chemotherapy in breast cancer: a single-center experience

OBJECTIVE

The aim of this study was to examine the characteristics of patients admitted to our hospital with a diagnosis of breast cancer who reached pathological complete response after being operated following eight cycles of neoadjuvant chemotherapy.

METHODS

Between 2015-2020, patients with pathological complete response who were operated on after neoadjuvant chemotherapy and sent to our clinic for radiotherapy were evaluated.

RESULTS

The median age of the patients was 51 years. The most common histological type was invasive ductal cancer. The number of pathological complete response patients was 74 (28%), and the number of non-pathological complete response patients was 188 (72%). Patients with pathological complete response had a smaller tumor diameter than the non-pathological complete response group (p=0.001). For pathological complete response, T1 stage, N1 stage, NG 3, Ki-67 >20%, negative estrogen receptor, negative progesterone receptor, positive Cerb-B2, and adding trastuzumab to chemotherapy were statistically significant (p<0.05). Before neoadjuvant chemotherapy, stage T1-T2 (p=0.036), LN0-1 (p=0.026), Cerb-B2 positivity (p=0.025), and an initial nuclear grade of three (p=0.001) were found to be the factors affecting pathological complete response.

CONCLUSIONS

With neoadjuvant chemotherapy, the size of locally advanced tumors decreases, allowing breast conserving surgery. The neoadjuvant chemotherapy response can be used as an early indicator of the prognosis of patients with breast cancer. Today, neoadjuvant chemotherapy is also used for patients with early-stage, operable breast cancer because it has been shown in many studies that reaching pathological complete response is associated with positive long-term results. If we can identify patients who have reached pathological complete response before neoadjuvant chemotherapy, we think we can also determine a patient-specific treatment plan at the beginning of treatment.

Clinical and Genetic Predictive Models for the Prediction of Pathological Complete Response to Optimize the Effectiveness for Trastuzumab Based Chemotherapy

Background

Trastuzumab shows excellent benefits for HER2+ breast cancer patients, although 20% treated remain unresponsive. We conducted a retrospective cohort study to optimize neoadjuvant chemotherapy and trastuzumab treatment in HER2+ breast cancer patients.

Methods

Six hundred patients were analyzed to identify clinical characteristics of those not achieving a pathological complete response (pCR) to develop a clinical predictive model. Available RNA sequence data was also reviewed to develop a genetic model for pCR.

Results

The pCR rate was 39.8% and pCR was associated with superior disease free survival and overall survival. ER negativity and PR negativity, higher HER2 IHC scores, higher Ki-67, and trastuzumab use were associated with improved pCR. Weekly paclitaxel and carboplatin had the highest pCR rate (46.70%) and the anthracycline+taxanes regimen had the lowest rate (11.11%). Four published GEO datasets were analyzed and a 10-gene model and immune signature for pCR were developed. Non-pCR patients were ER⁺PR⁺ and had a lower immune signature and gene model score. Hormone receptor status and immune signatures were independent predictive factors of pCR.

Conclusion

Hormone receptor status and a 10-gene model could predict pCR independently and may be applied for patient selection and drug effectiveness optimization.

Development and Validation of a Nomogram for Individually Predicting Pathologic Complete Remission After Preoperative Chemotherapy in Chinese Breast Cancer: A Population-Based Study

PURPOSE

To explore the independent predictors of pathologic complete remission response (pCR) for Chinese patients with breast cancer (BC) after preoperative chemotherapy and to develop an individualized nomogram for predicting the probability of pCR.

PATIENTS AND METHODS

The clinicopathologic data of clinical stage I-III BC patients who received preoperative chemotherapy in Xijing Hospital were retrospectively analyzed. A total of 689 BC patients diagnosed in 2015-2017 were included in the training set to develop a nomogram. A separate cohort of 357 patients in the same center was regarded as a validation set for externally examining the performance of the model. The area under the receiver operating characteristic curve and calibration curve were used to verify the predictive performance of the nomogram.

RESULTS

Multivariate logistic regression analysis showed that independent predictors of pCR were menopause status at diagnosis, family history of BC, initial tumor size, estrogen receptor status, HER2/neu (human epidermal growth factor receptor 2) status, and Ki-67 expression. On the basis of these factors, a nomogram was developed using R software. Our nomogram had good discrimination in the training and validation set (area under the receiver operating characteristic curve, 0.762 and 0.768, respectively). The calibration curves further confirmed that the model performs well.

CONCLUSION

Menopause status and family history of BC were independent predictors of pCR after preoperative chemotherapy for the first time. The nomogram can accurately predict pCR rate in BC, which may provide some guidelines for breast surgery options and patient counseling.

[Comparing prediction performances of 18F-FDG PET and CGFL/Curie nomogram to predict pathologic complete response after neoadjuvant chemotherapy for HER2-positive breast cancers]

OBJECTIVES

The aim of this study was to compare the value of ¹⁸F-fluorodesoxyglucose positron emission tomography (¹⁸F-FDG PET/CT) with CGFL/Curie nomogram to predict a pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in women with human epidermal growth factor 2 (HER2)-positive breast cancer treated by trastuzumab.

METHODS

Fifty-one women with HER2-positive breast cancer treated with trastuzumab plus taxane-based NAC were retrospectively included from January 2005 to December 2015. For ¹⁸F-FDG PET/CT, the analyzed predictor was the maximum standardized uptake value of the primary tumor and axillary nodes after the first course of NAC (PET₂.SUV_max). pCR was defined by no residual infiltrative tumor but in situ tumor was accepted. Accuracy of CGFL/Curie nomogram and PET₂.SUV_max was evaluated measuring sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV). Combined prediction was evaluated testing predictor's associations.

RESULTS

For CGFL/Curie nomogram's performances, Se, Sp, PPV and NPV were respectively: 76% (95%CI: 58-90%), 57% (95%CI: 43-66%), 55% (95%CI: 42-65), 77% (95%CI: 59-90%). For PET₂.SUV_max's performances, Se, Sp, PPV and NPV were respectively: 67% (95%CI: 48-81%), 77% (95%CI: 64-97%), 67% (95%CI: 48-82%), 77% (95%CI: 64-87%). ROC curves for these predictors were similar; the areas under the curve were 0.6 (95%CI: 0.56-0.64) for PET₂.SUV_max and 0.55 (95%CI: 0.50-0.59) for CGFL/Curie nomogram. Combined prediction was efficient with Se at 80%, VPN at 76%, Sp at 78% and VPP at 81%.

CONCLUSIONS

CGFL/Curie nomogram and PET₂.SUV_max were two efficient predictors of pCR in patients with HER2-positive breast cancer. Combined prediction has an improved accuracy.

APOBEC3B gene expression as a novel predictive factor for pathological complete response to neoadjuvant chemotherapy in breast cancer

Background

Apolipoprotein B mRNA editing enzyme catalytic polypeptide-like 3B (APOBEC3B) is a gene editing enzyme with cytidine deaminase activity and high expression of its mRNA in breast tumors have been shown to be associated with progressive cases and poor prognosis. In this study, we aimed to examine the relationship between the expression of APOBEC3B and the effect of neoadjuvant chemotherapy (NAC) using pretreatment biopsy tissue, and examined whether the expression of APOBEC3B influenced chemotherapy efficacy.

Methods

We retrospectively selected a total of 274 patients with primary breast cancer who received NAC in more than 4 courses and underwent surgery at our institute. We assessed the expression of APOBEC3B mRNA using pretreatment biopsy specimens of NAC by quantitative real-time PCR (qRT-PCR) and examined the relationship between APOBEC3B mRNA expression and sensitivity to chemotherapy using pathological complete response (pCR) as an indicator. Further, we assessed the prognostic value of APOBEC3B in the patients receiving NAC.

Results

APOBEC3B mRNA expression levels were successfully assessed in 173 (63.1%) of the 274 specimens. The total pCR rate was 36.4% (n = 63). An association between APOBEC3B expression levels and pCR was observed (Wilcoxon test, P ≤ 0.0001). The patients were divided into two groups, low (n = 66) and high (n = 107), according to the APOBEC3B expression levels, using the cut-off value calculated by the receiver operating characteristics (ROC) curve for pCR. The rate of pCR was significantly higher among the patients in the high group than among those in the low group (47.7% vs 18.2%, P ≤ 0.0001). High APOBEC3B expression was significantly associated with high nuclear grade (P = 0.0078), high Ki-67 labeling index (P = 0.0087), estrogen receptor (ER) negativity (P ≤ 0.0001) and human epidermal growth factor receptor 2 (HER2) negativity (P = 0.032). Tumor size (P = 0.011), ER (P ≤ 0.0001), HER2 (P = 0.0013) and APOBEC3B expression (P = 0.037) were independent predictive factors for pCR in multivariate analysis. However, there was no association between APOBEC3B expression and prognosis.

Conclusions

Our study showed that APOBEC3B mRNA expression correlated with sensitivity to NAC in breast cancer patients. In contrast to previous studies, APOBEC3B mRNA expression was not associated with breast cancer prognosis in patients receiving NAC.

[Predictive factors of conservative breast surgery after neoadjuvant chemotherapy for breast cancer]

OBJECTIVES

The aim of our study was to evaluate the existence of predictive factors of conservative breast surgery after neoadjuvant chemotherapy (NAC) for breast cancer.

METHODS

We included all women with invasive breast cancer who received NAC and underwent breast surgery between January 2007 and December 2013 in our institution. Univariable and multivariable analyses were performed to determine the association between clinical and histological factors and conservative breast surgery.

RESULTS

During the study period, 229 women were included of whom 73 had breast conservative surgery (32%). At univariable analysis, significant predictive factors were age (OR 0.97 [CI 95% 0.95-0.99], P=0.02), radiological size (OR 0.97 [CI 95% 0.96-0.99], P<0.001), multifocality (OR 0.53 [CI 95% 0.27-1.05], P=0.06), breast inflammation (OR 0.15 [CI 95% 0.07-0.32], P<0.001) and the type of hormone receptors (P=0.12). In multivariable analysis, all these factors but age were significant factors and thus considered as independent predictive factors.

CONCLUSION

This work permitted to identify independent predictive factors of breast conservative surgery after NAC for breast cancer that will be included in a risk scoring system that we aim to evaluate prospectively.