The role of quantitative estrogen receptor status in predicting tumor response at surgery in breast cancer patients treated with neoadjuvant chemotherapy

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

BACKGROUND

Given increased neoadjuvant therapy use in early-stage, hormone receptor (HR)-positive/HER2-negative breast cancer, we sought to quantify likelihood of breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NACT) or endocrine therapy (NET) as a function of ER%/PR%/Ki-67%, 21-gene recurrence scores (RS), or 70-gene risk groups.

METHODS

We analyzed the 2010-2020 National Cancer Database. Surgery was categorized as "mastectomy/BCS." Logistic regression was performed. Adjusted odds ratios (AOR) were per 10-unit increase in ER%/PR%/Ki-67%.

RESULTS

Overall, 42.3% underwent BCS after NACT, whereas 64.0% did after NET. Increasing ER% (AOR = 0.96, 95% confidence interval [CI] 0.94-0.97) or PR% (AOR=0.98, 95% CI 0.96-0.99) was associated with lower odds of BCS after NACT. Increasing Ki-67% was associated with greater odds of BCS (AOR = 1.07, 95% CI 1.04-1.10). Breast-conserving surgery rates increased by ~20 percentage points, with Ki-67% ≥15 or RS >20. Patients with a low (43.0%, AOR = 0.50, 95% CI 0.29-0.88) or intermediate (46.4%, AOR = 0.58, 95% CI 0.41-0.81) RS were less likely than patients with a high RS (65.0%) to undergo BCS after NACT. Increasing ER% was associated with higher odds of BCS after NET (AOR = 1.09, 95% CI 1.01-1.17). Breast-conserving surgery rates increased by ~20 percentage points between ER <50% and >80%. In both cohorts, the odds of BCS were similar between 70-gene low-risk and high-risk groups. Asian or uninsured patients had lower odds of BCS.

CONCLUSIONS

Neoadjuvant chemotherapy is unlikely to downstage tumors with a low-intermediate RS, higher ER%/PR%, or lower Ki-67%. Breast-conserving surgery after NET was most dependent on ER%. Findings could facilitate treatment decision-making based on tumor biology and racial/socioeconomic disparities and improve patient counseling on the likelihood of successful BCS.

Development and Assessment of a Novel Core Biopsy-Based Prediction Model for Pathological Complete Response to Neoadjuvant Chemotherapy in Women with Breast Cancer

Purpose: Pathological complete response (pCR), the goal of NAC, is considered a surrogate for favorable outcomes in breast cancer (BC) patients administrated neoadjuvant chemotherapy (NAC). This study aimed to develop and assess a novel nomogram model for predicting the probability of pCR based on the core biopsy. Methods: This was a retrospective study involving 920 BC patients administered NAC between January 2012 and December 2018. The patients were divided into a primary cohort (769 patients from January 2012 to December 2017) and a validation cohort (151 patients from January 2017 to December 2018). After converting continuous variables to categorical variables, variables entering the model were sequentially identified via univariate analysis, a multicollinearity test, and binary logistic regression analysis, and then, a nomogram model was developed. The performance of the model was assessed concerning its discrimination, accuracy, and clinical utility. Results: The optimal predictive threshold for estrogen receptor (ER), Ki67, and p53 were 22.5%, 32.5%, and 37.5%, respectively (all p < 0.001). Five variables were selected to develop the model: clinical T staging (cT), clinical nodal (cN) status, ER status, Ki67 status, and p53 status (all p ≤ 0.001). The nomogram showed good discrimination with the area under the curve (AUC) of 0.804 and 0.774 for the primary and validation cohorts, respectively, and good calibration. Decision curve analysis (DCA) showed that the model had practical clinical value. Conclusions: This study constructed a novel nomogram model based on cT, cN, ER status, Ki67 status, and p53 status, which could be applied to personalize the prediction of pCR in BC patients treated with NAC.

Development, verification, and comparison of a risk stratification model integrating residual cancer burden to predict individual prognosis in early-stage breast cancer treated with neoadjuvant therapy

Background

A favorable model for predicting disease-free survival (DFS) and stratifying prognostic risk in breast cancer (BC) treated with neoadjuvant chemotherapy (NAC) is lacking. The aim of the current study was to formulate an excellent model specially for predicting prognosis in these patients.

Patients and methods

Between January 2012 and December 2015, 749 early-stage BC patients who received NAC in Xijing hospital were included. Patients were randomly assigned to a training cohort (n = 563) and an independent cohort (n = 186). A prognostic model was created and subsequently validated. Predictive performance and discrimination were further measured and compared with other models.

Results

Clinical American Joint Committee on Cancer stage, grade, estrogen receptor expression, human epidermal growth factor receptor 2 (HER2) status and treatment, Ki-67 expression, lymphovascular invasion, and residual cancer burden were identified as independent prognostic variables for BC treated with NAC. The C-index of the model consistently outperformed other available models as well as single independent factors with 0.78, 0.80, 0.75, 0.82, and 0.77 in the training cohort, independent cohort, luminal BC, HER2-positive BC, and triple-negative BC, respectively. With the optimal cut-off values (280 and 360) selected by X-tile, patients were categorized as low-risk (total points ≤280), moderate-risk (280 < total points ≤ 360), and high-risk (total points >360) groups presenting significantly different 5-year DFS of 89.9%, 56.9%, and 27.7%, respectively.

Conclusions

In patients with BC, the first model including residual cancer burden index was demonstrated to predict the survival of individuals with favorable performance and discrimination. Furthermore, the risk stratification generated by it could determine the risk level of recurrence in whole early-stage BC cohort and subtype-specific cohorts, help tailor personalized intensive treatment, and select comparable study cohort in clinical trials.

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Establishing the first risk stratification nomogram for BC treated with NAC and validate its performance in BC cohorts.

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Incorporating residual cancer burden index into predictive nomogram for the first time.

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Predictive model can be utilized to predict DFS for all early-stage BC treated with NAC.

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Performing a continuous rather than categorized model to predict individual survival.

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The risk stratification can be used to select comparable population in trial design.

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.

Addition of carboplatin-gemcitabine as second-line neoadjuvant chemotherapy in non-responsive locally advanced breast cancer patients to standard neoadjuvant chemotherapy and evaluation of factors affecting response: a randomized controlled trial

Background

Neoadjuvant chemotherapy (NACT) is the prime approach to the management of locally advanced breast cancer (LABC). Influenced by different factors such as pathologic tumor characteristics, hormone receptor status, HER2 and proliferation marker expressions, response to therapy cannot be easily predicted. Pathologic complete response (pCR) has been considered as an endpoint to NACT; however, pCR rates have been unsatisfactory in such patients. In this randomized trial, we studied the efficacy of carboplatin/gemcitabine as second-line NACT while evaluating the impact of different factors affecting response.

Methods

In this randomized controlled trial, 52 clinically non-responsive (confirmed by palpation and/or ultrasonography) LABC patients to 4 cycles of doxorubicin/cyclophosphamide followed by 4 cycles of paclitaxel ± trastuzumab were randomly allocated to two groups. “Control” group underwent breast surgery and were further evaluated for pCR (ypT0/is ypN0). “Intervention” group received 2 cycles of carboplatin/gemcitabine and patients were further evaluated for pCR following surgery.

Results

In a total of 52 patients, pCR rate was 30.7%. pCR and response rate in lymph nodes were higher in carboplatin/gemcitabine recipients (32% vs 29.7 and 44% vs 40.7% respectively), however differences were insignificant. In both the “intervention” group and total study population, most pCR cases were of the hormone receptor (HR)+/HER2+ subtype (87.5% and 75% respectively). HER2 positivity, ki67 expression, lower extent of ER positivity, higher tumor grade and tumor-infiltrating lymphocyte (TIL) lead to higher pCR rates. Adverse events following addition of carboplatin/gemcitabine were mostly hematologic and none required hospitalization. Anemia was the most common grade 3 adverse event observed. No grade 4 toxicity was evident.

Conclusion

Although the proposed carboplatin/gemcitabine combination could not improve pCR rates as expected, probability of immune activation following use of carboplatin in achieving response to NACT may be considered. Accounting for the highest number of pCR cases in the “intervention” group, the HR+/HER2+ subtype with high TILs may be considered as most responsive to the proposed regimen in this study. It is noteworthy that the proposed combination imposed minimal toxicity.

Trial registration

This trial was prospectively registered in IRCT.ir (IRCT2017100136491N1). Date of registration: 19 November 2017.

Multiparametric MRI-based radiomics analysis for the prediction of breast tumor regression patterns after neoadjuvant chemotherapy

OBJECTIVES

Breast cancers show different regression patterns after neoadjuvant chemotherapy. Certain regression patterns are associated with more reliable margins in breast-conserving surgery. Our study aims to establish a nomogram based on radiomic features and clinicopathological factors to predict regression patterns in breast cancer patients.

METHODS

We retrospectively reviewed 144 breast cancer patients who received neoadjuvant chemotherapy and underwent definitive surgery in our center from January 2016 to December 2019. Tumor regression patterns were categorized as type 1 (concentric regression + pCR) and type 2 (multifocal residues + SD + PD) based on pathological results. We extracted 1158 multidimensional features from 2 sequences of MRI images. After feature selection, machine learning was applied to construct a radiomic signature. Clinical characteristics were selected by backward stepwise selection. The combined prediction model was built based on both the radiomic signature and clinical factors. The predictive performance of the combined prediction model was evaluated.

RESULTS

Two radiomic features were selected for constructing the radiomic signature. Combined with two significant clinical characteristics, the combined prediction model showed excellent prediction performance, with an area under the receiver operating characteristic curve of 0.902 (95% confidence interval 0.8343-0.9701) in the primary cohort and 0.826 (95% confidence interval 0.6774-0.9753) in the validation cohort.

CONCLUSIONS

Our study established a unique model combining a radiomic signature and clinicopathological factors to predict tumor regression patterns prior to the initiation of NAC. The early prediction of type 2 regression offers the opportunity to modify preoperative treatments or aids in determining surgical options.

Estrogens Counteract Platinum-Chemosensitivity by Modifying the Subcellular Localization of MDM4

Estrogen activity towards cancer-related pathways can impact therapeutic intervention. Recent omics data suggest possible crosstalk between estrogens/gender and MDM4, a key regulator of p53. Since MDM4 can either promote cell transformation or enhance DNA damage-sensitivity, we analysed in vivo impact of estrogens on both MDM4 activities. In Mdm4 transgenic mouse, Mdm4 accelerates the formation of fibrosarcoma and increases tumor sensitivity to cisplatin as well, thus confirming in vivo Mdm4 dual mode of action. Noteworthy, Mdm4 enhances chemo- and radio-sensitivity in male but not in female animals, whereas its tumor-promoting activity is not affected by mouse gender. Combination therapy of transgenic females with cisplatin and fulvestrant, a selective estrogen receptor degrader, was able to recover tumor cisplatin-sensitivity, demonstrating the relevance of estrogens in the observed sexual dimorphism. Molecularly, estrogen receptor-α alters intracellular localization of MDM4 by increasing its nuclear fraction correlated to decreased cell death, in a p53-independent manner. Importantly, MDM4 nuclear localization and intra-tumor estrogen availability correlate with decreased platinum-sensitivity and apoptosis and predicts poor disease-free survival in high-grade serous ovarian carcinoma. These data demonstrate estrogen ability to modulate chemo-sensitivity of MDM4-expressing tumors and to impinge on intracellular trafficking. They support potential usefulness of combination therapy involving anti-estrogenic drugs.

Usefulness of serum M30 and M65 levels to predict response to neoadjuvant chemotherapy in patients with breast cancer

OBJECTIVE

M30 and M65 levels reflect tumor cell activity in patients with epithelial cancer. Cytokeratin 18 is one of the cell skeletal elements. M30 is a apoptotic marker of cytokeratin 18. M65 levels are both an apoptosis and a necrosis marker. The aim of our study was to determine the predictive value of M30 and M65 levels in neoadjuvant treatment of breast cancer.

MATERIALS AND METHODS

In this prospective study, 41 patients with breast cancer who underwent neoadjuvant chemotherapy were included. Following 4 cycles of chemotherapy with anthracycline containing regimen, patients received paclitaxel treatment for 12 weeks. Blood was collected from the patients before chemotherapy and on day 21, after the 2nd, 4th, and 8th cycles. M30 and M65 levels were measured with the ELISA method.

RESULTS

While there was an increase in M30 and M65 levels at the 4th cycle (P < 0.05), levels were decreased after the 8th cycle. In addition, there was no significant relationship among M30, M65 levels, and prognostic factors such as ER, PR, c-Erb-2, Ki-67, pathologic-T, pathologic-N, and chemotherapy responses.

CONCLUSION

M30 and M65 levels are not of predictive values of response to breast cancer patients receiving neoadjuvant chemotherapy. Nevertheless, M30 and M65 levels increased when patients kept receiving anthracycline containing chemotherapy.

Exosome-mediated delivery of MALAT1 induces cell proliferation in breast cancer

Background

Breast cancer is the most common cancer in women worldwide. Cancer-secreted exosomes have recently been recognized as important mediators of intercellular communication. The aim of this study was to determine the role of exosomal long noncoding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in breast cancer progression.

Materials and methods

Breast cancer specimens were obtained with informed consent from patients. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect MALAT1 expression, and cellular proliferation was measured using cell counting kit-8 (CCK-8) assay.

Results

MALAT1 was highly expressed in breast cancer tissues and associated with disease progression. Breast cancer exosomes promoted cell proliferation and exosome-mediated MALAT1 to induce cell proliferation.

Conclusion

These findings indicated that exosomal MALAT1 could regulate cancer progression and represent a novel strategy for overcoming breast cancer.

Colon cancer associated transcripts in human cancers

Long non-coding RNAs serve as important regulators in complicated cellular activities, including cell differentiation, proliferation and death. Dysregulation of long non-coding RNAs occurs in the formation and progression of cancers. The family of colon cancer associated transcripts, long non-coding RNAs colon cancer associated transcript-1 and colon cancer associated transcript-2 are known as oncogenes involved in various cancers. Colon cancer associated transcript-1 is a novel lncRNA located in 8q24.2, and colon cancer associated transcript-2 maps to the 8q24.21 region encompassing rs6983267. Colon cancer associated transcripts have close associations with clinical characteristics, such as lymph node metastasis, high TNM stage and short overall survival. Knockdown of them can reverse the malignant phenotypes of cancer cells, including proliferation, migration, invasion and apoptosis. Moreover, they can increase the expression level of c-MYC and oncogenic microRNAs via activating a series of complex mechanisms. In brief, the family of colon cancer associated transcripts may serve as potential biomarkers or therapeutic targets for human cancers.