Molecular subtype profiling of invasive breast cancers weakly positive for estrogen receptor

Progress on deep learning in digital pathology of breast cancer: a narrative review

BACKGROUND AND OBJECTIVE

Pathology is the gold standard criteria for breast cancer diagnosis and has important guiding value in formulating the clinical treatment plan and predicting the prognosis. However, traditional microscopic examinations of tissue sections are time consuming and labor intensive, with unavoidable subjective variations. Deep learning (DL) can evaluate and extract the most important information from images with less need for human instruction, providing a promising approach to assist in the pathological diagnosis of breast cancer. To provide an informative and up-to-date summary on the topic of DL-based diagnostic systems for breast cancer pathology image analysis and discuss the advantages and challenges to the routine clinical application of digital pathology.

METHODS

A PubMed search with keywords ("breast neoplasm" or "breast cancer") and ("pathology" or "histopathology") and ("artificial intelligence" or "deep learning") was conducted. Relevant publications in English published from January 2000 to October 2021 were screened manually for their title, abstract, and even full text to determine their true relevance. References from the searched articles and other supplementary articles were also studied.

KEY CONTENT AND FINDINGS

DL-based computerized image analysis has obtained impressive achievements in breast cancer pathology diagnosis, classification, grading, staging, and prognostic prediction, providing powerful methods for faster, more reproducible, and more precise diagnoses. However, all artificial intelligence (AI)-assisted pathology diagnostic models are still in the experimental stage. Improving their economic efficiency and clinical adaptability are still required to be developed as the focus of further researches.

CONCLUSIONS

Having searched PubMed and other databases and summarized the application of DL-based AI models in breast cancer pathology, we conclude that DL is undoubtedly a promising tool for assisting pathologists in routines, but further studies are needed to realize the digitization and automation of clinical pathology.

Proteomic analysis of archival breast cancer clinical specimens identifies biological subtypes with distinct survival outcomes

Despite advances in genomic classification of breast cancer, current clinical tests and treatment decisions are commonly based on protein level information. Formalin-fixed paraffin-embedded (FFPE) tissue specimens with extended clinical outcomes are widely available. Here, we perform comprehensive proteomic profiling of 300 FFPE breast cancer surgical specimens, 75 of each PAM50 subtype, from patients diagnosed in 2008-2013 (n = 178) and 1986-1992 (n = 122) with linked clinical outcomes. These two cohorts are analyzed separately, and we quantify 4214 proteins across all 300 samples. Within the aggressive PAM50-classified basal-like cases, proteomic profiling reveals two groups with one having characteristic immune hot expression features and highly favorable survival. Her2-Enriched cases separate into heterogeneous groups differing by extracellular matrix, lipid metabolism, and immune-response features. Within 88 triple-negative breast cancers, four proteomic clusters display features of basal-immune hot, basal-immune cold, mesenchymal, and luminal with disparate survival outcomes. Our proteomic analysis characterizes the heterogeneity of breast cancer in a clinically-applicable manner, identifies potential biomarkers and therapeutic targets, and provides a resource for clinical breast cancer classification.

Protein level information enables the identification of potential biomarkers and therapeutic targets for breast cancer. Here, the authors perform proteomic analysis of 2 cohorts of breast cancer surgical specimens and identify distinct subtypes, immune features and survival outcomes.

SOX10 is a highly specific biomarker of basal-like breast cancer

AIMS

Basal-like breast cancer is an aggressive molecular subtype associated with younger age and early relapse. Most cases lack expression of estrogen receptor (ER), progesterone receptor, and human epidermal growth factor receptor 2, limiting targeted therapeutic options. Basal-like breast cancer is defined by expression of genes in the outer/basally-located epithelial layer of mammary glands including those encoding cytokeratins 5 and 14, and epidermal growth factor receptor (EGFR). SOX10, a readily available immunohistochemical stain, is expressed in a subset of breast cancers, particularly triple-negative carcinomas. In this study, we sought to (i) assess the association between SOX10 expression and intrinsic molecular subtypes as defined by PAM50 gene expression and (ii) compare the performance of SOX10 to other surrogate markers of basal-like subtype, including CK5, EGFR, nestin and INPP4b.

METHODS AND RESULTS

SOX10 immunostaining was performed on tissue microarrays constructed from a contemporary series enriched for ER negative and weakly positive cancers, which had also undergone PAM50 gene profiling. A total of 211 cases were informative for both SOX10 immunohistochemistry (IHC) and PAM50 subtype, including 103 basal-like. Staining for SOX10 was positive in 73/103 basal-like cancers and only 2/108 other subtypes (p<0.001), resulting in a sensitivity of 70.9% and a specificity of 98.1%. SOX10 was more specific than the other tested basal-markers and the results were independent of estrogen receptor status.

CONCLUSIONS

SOX10 is a moderately sensitive, but highly specific IHC biomarker for the basal-like intrinsic subtype of breast cancer, which unlike other commonly used IHC biomarkers, is independent of hormone receptor status.

Looking for more reliable biomarkers in breast cancer: Comparison between routine methods and RT-qPCR

PURPOSE

Decades of quality control efforts have raised the standards of immunohistochemistry (IHC), the principle method used for biomarker testing in breast cancer; however, computational pathology and reverse transcription quantitative PCR (RT-qPCR) may also hold promise for additional substantial improvements.

METHODS

Herein, we investigated discrepancies in the assessment of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and marker of proliferation Ki67 comparing routinely obtained IHC (and FISH) data (ORI) with the results of manual (REV) and semi-automated (DIA) re-evaluation of the original IHC slides and then with RNA expression data from the same tissue block using the MammaTyper® (MT) gene expression assay.

RESULTS

Correlation for ER and PR was high between ORI IHC and the other three study methods (REV, DIA and RT-qPCR). For HER2, 10 out of 96 discrepant cases can be detected between ORI and REV that involved at least one call in the equivocal category (except for one case). For Ki67, 22 (29.1%) cases were categorized differently by either REV alone (n = 17), DIA alone (n = 15) or both (n = 10) and 28 cases (29.2%) for RT-qPCR. Most of the discrepant Ki67 cases changed from low to high between the original and following assessment and belonged to the intermediate Ki67 expression range (between 9 and 30%).

CONCLUSIONS

Determination of the breast cancer biomarkers ER, PR, HER2 and Ki67 at the mRNA level shows high degree of correlation with IHC and compares well with correlations between original with subsequent independent manual or semi-automated IHC assessments. The use of methods with wider dynamic range and higher reproducibility such as RT-qPCR may offer more precise assessment of endocrine responsiveness, improve Ki67 standardization and help resolve HER2 cases that remain equivocal or ambiguous by IHC/FISH. In summary, our findings seem to configure RT-qPCR as a complementary method to be used in cases of either equivocal results or presenting, at the traditional determination assays, biomarkers expressions close to the cut-off values.

Histology of Luminal Breast Cancer

Background

Invasive breast cancer (IBC) can be categorized into prognostic and predictive molecular subtypes (including luminal breast cancer) using gene expression profiling. Luminal IBC comprises a variety of histological subtypes with varying clinical and pathological features.

Summary

IBC of no special subtype is the most common histological subtype in general and likewise within luminal IBC. Classical invasive lobular breast cancer, typically clustering into luminal subgroup, is characterized by discohesive growth and loss of E-cadherin expression. Infrequent, morphologically distinct luminal IBC subtypes are tubular, invasive cribriform, mucinous, and invasive micropapillary carcinomas. Breast carcinoma with apocrine differentiation, with characteristic expression of androgen receptor (AR), often clusters into the luminal AR category. Rarely, neuroendocrine neoplasms of the breast can be seen. IBC of the male breast usually matches with the luminal subtype.

Key Messages

Independently from histological subtypes, invasive breast cancer (IBC) can be divided into molecular subtypes based on mRNA gene expression levels. Using this molecular subtyping, risk scores based on gene expression profiling (established for hormone receptor-positive, HER2-negative IBC), grading, and Ki-67 index, prognosis of patients with luminal breast cancer and response to chemotherapy can be predicted. In routine diagnostics, the expression of estrogen receptor (ER) and progesterone receptor (PR), HER2 status, and the proliferation rate (Ki-67) are used to determine a surrogate (molecular-like) subtype. Within luminal(-like) IBC, no special subtype and invasive lobular breast carcinoma are the most common histological subtypes. Other rare histological subtypes (e.g., tubular carcinoma) should be recognized due to their distinct clinical and pathological features.

Borderline Estrogen Receptor-Positive Breast Cancers in Black and White Women

BACKGROUND

Some breast tumors expressing greater than 1% and less than 10% estrogen receptor (ER) positivity (ER-borderline) are clinically aggressive; others exhibit luminal biology. Prior ER-borderline studies included few black participants.

METHODS

Using the Carolina Breast Cancer Study (phase I: 1993-1996; 2: 1996-2001; 3: 2008-2013), a population-based study that oversampled black women, we compared ER-borderline (n = 217) to ER-positive (n = 1885) and ER-negative (n = 757) tumors. PAM50 subtype and risk of recurrence score (ROR-PT, incorporates subtype, proliferation, tumor size) were measured. Relative frequency differences (RFD) were estimated using multivariable linear regression. Disease-free interval (DFI) was evaluated by ER category and endocrine therapy receipt, overall and by race, using Kaplan Meier and Cox models. Statistical tests were two-sided.

RESULTS

ER-borderlines were more frequently basal-like (RFD = +37.7%, 95% confidence interval [CI] = 27.1% to 48.4%) and high ROR-PT (RFD = +52.4%, 95% CI = 36.8% to 68.0%) relative to ER-positives. Having a high ROR-PT ER-borderline tumor was statistically significantly associated with black race (RFD = +26.2%, 95% CI = 9.0% to 43.3%). Compared to ER-positives, DFI of ER-borderlines treated with endocrine therapy was poorer but not statistically significantly different (hazard ratio [HR] = 2.03, 95% CI = 0.89% to 4.65%), whereas DFI was statistically significantly worse for ER-borderlines without endocrine therapy (HR = 3.33, 95% CI = 1.84% to 6.02%). However, black women with ER-borderline had worse DFI compared to ER-positives, even when treated with endocrine therapy (HR = 2.77, 95% CI = 1.09% to 7.04%).

CONCLUSIONS

ER-borderline tumors were genomically heterogeneous, with survival outcomes that differed by endocrine therapy receipt and race. Black race predicted high-risk ER-borderlines and may be associated with poorer endocrine therapy response.

Estrogen and Progesterone Receptor Testing in Breast Cancer: American Society of Clinical Oncology/College of American Pathologists Guideline Update

PURPOSE.—

To update key recommendations of the American Society of Clinical Oncology/College of American Pathologists estrogen receptor (ER) and progesterone receptor (PgR) testing in breast cancer guideline.

METHODS.—

A multidisciplinary international Expert Panel was convened to update the clinical practice guideline recommendations informed by a systematic review of the medical literature.

RECOMMENDATIONS.—

The Expert Panel continues to recommend ER testing of invasive breast cancers by validated immunohistochemistry as the standard for predicting which patients may benefit from endocrine therapy, and no other assays are recommended for this purpose. Breast cancer samples with 1% to 100% of tumor nuclei positive should be interpreted as ER positive. However, the Expert Panel acknowledges that there are limited data on endocrine therapy benefit for cancers with 1% to 10% of cells staining ER positive. Samples with these results should be reported using a new reporting category, ER Low Positive, with a recommended comment. A sample is considered ER negative if < 1% or 0% of tumor cell nuclei are immunoreactive. Additional strategies recommended to promote optimal performance, interpretation, and reporting of cases with an initial low to no ER staining result include establishing a laboratory-specific standard operating procedure describing additional steps used by the laboratory to confirm/adjudicate results. The status of controls should be reported for cases with 0% to 10% staining. Similar principles apply to PgR testing, which is used primarily for prognostic purposes in the setting of an ER-positive cancer. Testing of ductal carcinoma in situ (DCIS) for ER is recommended to determine potential benefit of endocrine therapies to reduce risk of future breast cancer, while testing DCIS for PgR is considered optional. Additional information can be found at www.asco.org/breast-cancer-guidelines .

Estrogen and Progesterone Receptor Testing in Breast Cancer: ASCO/CAP Guideline Update

PURPOSE

To update key recommendations of the American Society of Clinical Oncology/College of American Pathologists estrogen (ER) and progesterone receptor (PgR) testing in breast cancer guideline.

METHODS

A multidisciplinary international Expert Panel was convened to update the clinical practice guideline recommendations informed by a systematic review of the medical literature.

RECOMMENDATIONS

The Expert Panel continues to recommend ER testing of invasive breast cancers by validated immunohistochemistry as the standard for predicting which patients may benefit from endocrine therapy, and no other assays are recommended for this purpose. Breast cancer samples with 1% to 100% of tumor nuclei positive should be interpreted as ER positive. However, the Expert Panel acknowledges that there are limited data on endocrine therapy benefit for cancers with 1% to 10% of cells staining ER positive. Samples with these results should be reported using a new reporting category, ER Low Positive, with a recommended comment. A sample is considered ER negative if < 1% or 0% of tumor cell nuclei are immunoreactive. Additional strategies recommended to promote optimal performance, interpretation, and reporting of cases with an initial low to no ER staining result include establishing a laboratory-specific standard operating procedure describing additional steps used by the laboratory to confirm/adjudicate results. The status of controls should be reported for cases with 0% to 10% staining. Similar principles apply to PgR testing, which is used primarily for prognostic purposes in the setting of an ER-positive cancer. Testing of ductal carcinoma in situ (DCIS) for ER is recommended to determine potential benefit of endocrine therapies to reduce risk of future breast cancer, while testing DCIS for PgR is considered optional. Additional information can be found at www.asco.org/breast-cancer-guidelines.

A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy

For estrogen receptor (ER)-negative breast cancer patients, paclitaxel (P), doxorubicin (A) and cyclophosphamide (C) neoadjuvant chemotherapy (NAC) is the standard therapeutic regimen. Pathologic complete response (pCR) and residual disease (RD) are common surrogate measures of chemosensitivity. After NAC, most patients still have RD; of these, some partially respond to NAC, whereas others show extreme resistance and cannot benefit from NAC but only suffer complications resulting from drug toxicity. Here we developed a qualitative transcriptional signature, based on the within-sample relative expression ordering (REO) of gene pairs, to identify extremely resistant samples to PAC NAC. Using gene expression data for ER-negative breast cancer patients including 113 pCR samples and 137 RD samples from four datasets, we selected 61 gene pairs with reversal REO patterns between the two groups as the resistance signature, denoted as NR61. Samples with more than 37 signature gene pairs that had the same REO patterns within the extremely resistant group were defined as having extreme resistance; otherwise, they were considered responders. In the GSE25055 and GSE25065 dataset, the NR61 signature could correctly identify 44 (97.8%) of the 45 pCR samples and 22 (95.7%) of the 23 pCR samples as responder samples, respectively; it also identified 13 (16.9%) of 77 RD samples and 8 (21.1%) of 38 RD samples as extremely resistant samples, respectively. Survival analysis showed that the distant relapse-free survival (DRFS) time of the 14 extremely resistant cases was significantly shorter than that of the 108 responders (P < 0.01; HR = 3.84; 95% CI = 1.91–7.70) in GSE25055. Similar results were obtained in GSE25065. Moreover, in the integrated data of the two datasets with 94 responders and 21 extremely resistant samples identified from RD patients, the former had significantly longer DRFS than the latter (P < 0.01; HR = 2.22; 95% CI = 1.26–3.90). In summary, our signature could effectively identify patients who completely respond to PAC NAC, as well as cases of extreme resistance, which can assist decision-making on the clinical therapy for these patients.

Hormone receptor expression and outcomes in low-grade serous ovarian carcinoma

OBJECTIVE

Low-grade serous ovarian carcinomas (LGSC) are frequently ER/PR positive, though the mechanisms by which ER/PR regulate prognosis or anti-estrogen treatment efficacy are poorly understood. We studied ER/PR expression in LGSC tumors and cell lines to evaluate patient outcomes and cellular treatment responses.

METHODS

LGSC tumors and patient-derived cell lines were studied from patients with advanced-stage (III/IV) disease. Tumor samples and clinical data were obtained from the Canadian Ovarian Experimental Unified Resource (COEUR-tissue microarray) and the Ovarian Cancer Research (OvCaRe) tissue bank. ER/PR expression was assessed by both Western blot and immunohistochemistry (IHC). Two different IHC scoring systems (simple and Allred) were used. Cox regression was used to identify factors (age, disease residuum, ER/PR status, etc.) associated with progression-free (PFS) and overall survival (OS). Estradiol and tamoxifen proliferation and viability experiments were performed in LGSC cell lines.

RESULTS

In 55 LGSC cases studied, median follow-up was 56 months (range 1-227). Fifty-three (96%) cases strongly expressed ER whereas 37 (67%) expressed PR. Cox-regression analysis showed that residuum (p < 0.001) was significantly associated with PFS, whereas both ER Allred score (p = 0.005) and residuum (p = 0.004) were significant for OS. None of the LGSC cell lines expressed PR. Loss of PR and ER expression over time was detected in LGSC tumors and cell lines respectively. Estrogen and tamoxifen treatment did not alter LGSC cell proliferation or viability in-vitro.

CONCLUSIONS

In patients with advanced LGSC, higher ER Allred scores were significantly associated with better overall survival. ER/PR expression changed over time in both LGSC tumors and cell lines. Better translational research models are needed to elucidate the molecular mechanisms of ER/PR signalling in LGSC.

Basal biomarkers nestin and INPP4B predict gemcitabine benefit in metastatic breast cancer: Samples from the phase III SBG0102 clinical trial

In a formal prospective-retrospective analysis of the phase III SBG0102 clinical trial randomizing metastatic breast cancer patients to gemcitabine-docetaxel or to single agent docetaxel, patients with basal-like tumors by PAM50 gene expression had significantly better overall survival in the gemcitabine arm. By immunohistochemistry (IHC), triple negative status was not predictive, but more specific biomarkers have since become available defining basal-like by nestin positivity or loss of inositol-polyphosphate-4-phosphate (INPP4B). Here, we evaluate their capacity to identify which patients benefit from gemcitabine in the metastatic setting. Nestin and INPP4B staining and interpretation followed published methods. A prespecified statistical plan evaluated the primary hypothesis that patients with basal-like breast cancer, defined as "nestin+ or INPP4B-", would have superior overall survival on gemcitabine-docetaxel when compared to docetaxel. Interaction tests, Kaplan-Meier curves and forest plots were used to assess prognostic and predictive capacities of biomarkers relative to treatment. Among 239 cases evaluable for our study, 36 (15%) had been classified as basal-like by PAM50. "Nestin+ or INPP4B-" was observed in 41 (17%) of the total cases and was significantly associated with PAM50 basal-like subtype. Within an estimated median follow-up of 13 years, patients assigned as IHC basal "nestin+ or INPP4B-" had significantly better overall survival on gemcitabine-docetaxel versus docetaxel monotherapy (HR = 0.31, 95%CI: 0.16-0.60), whereas no differences were observed for other patients (HR = 0.99), p-interaction < 0.01. In the metastatic setting, women with IHC basal breast cancers defined as "nestin+ or INPP4B-" have superior overall survival when randomized to gemcitabine-containing chemotherapy compared to docetaxel alone. These findings need to be validated using larger prospective-retrospective phase III clinical trials series.

Outcome for triple negative breast cancer in a retrospective cohort with an emphasis on response to platinum-based neoadjuvant therapy

Purpose

The rate of pathological complete response (pCR) for patients with triple negative breast cancer (TNBC) is increased when carboplatin is added to neo-adjuvant chemotherapy (NACT). However, while phase III trial data showing a survival benefit are awaited, carboplatin is not yet standard-of-care for TNBC. The aim of this study was to examine the rate of pCR and the outcome for those treated with carboplatin and to examine the predictors of response to therapy.

Methods

The retrospective series comprised 333 consecutive patients with TNBC (median follow-up time, 43 months). Adjuvant chemotherapy was given to 51% (n = 168) of patients and 29% (n = 97) received anthracycline–taxane NACT with carboplatin given to 9% (n = 31) of patients.

Results

Overall, 25% (n = 78) of patients experienced a breast cancer recurrence and 22% (n = 68) died from disease. A pCR breast and pCR breast/axilla was more common in those who received carboplatin (n = 18, 58% and n = 17, 55%, respectively) compared those who did not (n = 23, 36% and n = 18, 28%, respectively) (p = 0.041 and p = 0.011, respectively). By multivariable analysis, carboplatin and high tumor grade were independent predictors of pCR breast/axilla (OR_non-pCR = 0.17; 95% CI 0.06–0.54; p = 0.002; and OR_non-pCR = 0.05, 95% CI 0.01–0.27; p < 0.001, respectively). pCR breast/axilla was an independent predictor of DFS (HR_non-pCR=6.23; 95% CI 1.36–28.50; p = 0.018), metastasis-free survival (HR_non-pCR = 5.08; 95% CI 1.09–23.65; p = 0.038) and BCSS (HR_non-pCR = 8.52; 95% CI 1.09–66.64; p = 0.041).

Conclusion

Carboplatin therapy and high tumor grade are associated with a significant increase in the rate of pCR, which is an independent predictor of outcome. These data support the use of carboplatin in NACT for TNBC, while results from phase III studies are awaited.

Electronic supplementary material

The online version of this article (10.1007/s10549-018-5066-6) contains supplementary material, which is available to authorized users.

Ancillary Prognostic and Predictive Testing in Breast Cancer: Focus on Discordant, Unusual, and Borderline Results

Ancillary testing in breast cancer has become standard of care to determine what therapies may be most effective for individual patients with breast cancer. Single-marker tests are required on all newly diagnosed and newly metastatic breast cancers. Markers of proliferation are also used, and include both single-marker tests like Ki67 as well as panel-based gene expression tests, which have made more recent contributions to prognostic and predictive testing in breast cancers. This review focuses on pathologist interpretation of these ancillary test results, with a focus on expected versus unexpected results and troubleshooting borderline, unusual, or discordant results.

Only estrogen receptor "positive" is not enough to predict the prognosis of breast cancer

PURPOSE

Beginning in 2018, biomarkers including estrogen receptor (ER) status were incorporated in the 8th AJCC staging system. ER expression levels were not considered in these changes. We hypothesized that the levels of ER expression could affect the prognosis of breast cancer.

METHODS

A retrospective review was conducted to identify all female patients with invasive breast cancer between 2003 and 2012. ER negative (group I), weakly ER-positive (group II), and strongly ER-positive (group III) were defined as Allred total scores of 0-2, 3-5, and 6-8, respectively. We examined a multigene panel, designated the BCT score, which is a newly developed prognostic model for predicting the risk of a distant metastasis.

RESULTS

Among the 4949 patients enrolled in this study, 1310 (26.5%), 361 (7.3%), and 3277 (66.2%) were categorized as group I, II, and III, respectively. Median F/U duration was 57.8 months. Compared to group III, patients in group II were younger, had larger tumors, and were also more likely to have PR-negative tumors, HER-2 amplification, high Ki-67, and high nuclear grade. Between group II and III, there was a significant difference in OS (P = 0.0764, 0.909, and 0.010, respectively). After adjusting for additional factors that may affect OS, the HR for OS showed higher in group II than in group III. The baseline median BCT score indicated that lower ER expression was associated with significantly higher BCT score (P < 0.0001) and significantly more likely to have high risk group (P < 0.0001) relative to higher levels of ER expression group.

CONCLUSION

ER expression levels affect the prognosis of breast cancer. The risk for patients with weakly ER-positive breast cancer should not be underestimated.

Implications of nestin in breast cancer pathogenesis (Review)

The aim of the present review was to summarize the current knowledge of the involvement of nestin in breast cancer (BC) pathogenesis. Nestin is a member of the class VI family of intermediate filament proteins, originally identified as a marker of neural stem cells and subsequently demonstrated to be expressed in BC and other cancer types. In normal breast tissue, nestin is expressed in the basal/myoepithelial cells of the mammary gland. In BC, nestin identifies basal-like tumours and predicts aggressive behaviour and poor prognosis. Nestin expression has also been detected in BC stem cells and newly-formed tumour vessels, being a factor in promoting invasion and metastasis. The present review provides an up-to-date overview of the involvement of nestin in processes facilitating BC pathogenesis and progression.

Assessment of the predictive role of pretreatment Ki-67 and Ki-67 changes in breast cancer patients receiving neoadjuvant chemotherapy according to the molecular classification: a retrospective study of 1010 patients

PURPOSE

To assess the predictive role of pretreatment ki67 and Ki67 changes in breast cancer (BC) patients treated with neoadjuvant chemotherapy (NAC) in various molecular subtypes.

METHODS

1010 BC patients who had undergone anthracycline and taxane-based NAC from January 2012 to July 2017 were retrospectively analyzed. Clinical and pathological parameters of the patients were retrieved and the predictive factors for NAC response were evaluated.

RESULTS

705 patients showed clinical response (cRes), and 131 patients acquired pathologic complete response (pCR). Patients with higher pretreatment Ki67 (≥ 14%), tumor size ≥ 4 cm, and positive clinical nodal had better clinical therapy response, while patients with negative ER and PR, higher pretreatment Ki67 (≥ 14%), and tumor size < 4 cm were more probable to attain pCR. The pretreatment Ki67 could be used as a predictor of NAC only in luminal subtypes, and 25.5% were identified as an ideal cut-off point to differentiate the cRes from non-cRes cases. Although a decrease in Ki67 had been found in almost all molecular subtypes after NAC, no statistically significant differences were found in the decrease of Ki67 were validated between the cRes and non-cRes group in HER2-rich and triple-negative subtypes (P = 0.488 and P = 0.111, respectively).

CONCLUSIONS

The best cut-off for pretreatment Ki67 in predicting the connection with the tumor size lessening was 25.5% in luminal subtype. Aggressive adjuvant systemic treatments should be considered for patients with HER2-rich and triple-negative subtype who exhibit tumor shrinkage in NAC but still have high levels of Ki67.

The ability of PAM50 risk of recurrence score to predict 10-year distant recurrence in hormone receptor-positive postmenopausal women with special histological subtypes

INTRODUCTION

The Prosigna-PAM50 risk of recurrence (ROR) score has been validated in randomized clinical trials to predict 10-year distant recurrence (DR) in hormone receptor-positive breast cancer. Here, we examine the ability of Prosigna for predicting DR at 10 years in a subgroup of postmenopausal breast cancer patients with special histological subtypes.

METHODS

Using the population based Danish Breast Cancer Group database, follow-up data were collected on all patients diagnosed from 2000 to 2003 with estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2) normal breast cancer who by nationwide guidelines were treated with 5 year of endocrine therapy (N = 2558). Among patients with 1 to 3 positive lymph nodes or a tumor size >20 mm, we identified 1570 with invasive ductal carcinoma (IDC) and 89 with special histological subtypes (apocrine, medullary, mucinous, papillary, secretory, tubular, neuroendocrine) who were tested with Prosigna. Fine and Gray models were applied to determine the prognostic value of the Prosigna-PAM50 ROR score for DR special subtypes as compared to IDC.

RESULTS

Median follow-up for DR was 9.2 year and for OS 15.2 year. The 10-year DR rate for the special subtypes was 9.2% (95% CI: 4.0% to 17.2%) as compared to 13.7% (95% CI: 11.9% to 15.7%) for IDC. The 10-year OS was 74.2% (95% CI: 63.7% to 82.0%) for the special subtypes and 75.4% (95% CI: 73.2% to 77.4%) for IDC. Prosigna showed a statistical significant association of the continuous ROR score with risk of DR for both IDC and the special subtypes (IDC: p < .0001; special subtypes: p = .01).

CONCLUSION

In the present study, we demonstrated that Prosigna-PAM50 continuous ROR score added significant prognostic information for 10-year DR in postmenopausal patients with special subtypes (tumor size >20 mm or 1 to 3 positive lymph nodes) and ER-positive, HER2-normal early breast cancer.

Nestin expression in breast cancer: association with prognosis and subtype on 3641 cases with long-term follow-up

BACKGROUND

Basal-like breast cancers, originally recognized by gene expression profiling, can be clinically identified using immunohistochemical (IHC) definitions that require estrogen receptor (ER) negativity. However, some basal cases are ER positive and are mistakenly considered to be luminal by standard IHC approaches, leading to suboptimal treatment choices. Nestin, an intermediate filament expressed in many stem cells, is a recently identified positive marker of basal-like phenotype independent of ER status. In this study, we evaluated its clinical associations and prognostic capacity in a large breast cancer cohort.

METHODS

A tissue microarray series of clinically annotated invasive breast cancers with 12.6-year median follow-up was assessed for nestin expression by IHC. Kaplan-Meier and Cox regression models were used to evaluate the prognostic significance of nestin status, for the primary endpoint of breast cancer-specific survival (BCSS).

RESULTS

Among 3641 cases interpretable for nestin by IHC, positive staining was found in 371 cases (10%) and was significantly associated with poor prognostic factors including other markers of basal-like differentiation. Patients with nestin-positive tumors had a significantly lower 10 year BCSS (HR 1.97, 95% CI 1.62-2.40; P < 0.001). Importantly, within the large group of 2323 ER+ cases, nestin positivity identified a subgroup of 120 patients (5%) with a significantly inferior 10-year BCSS (HR 1.50, 95% CI 1.10-2.13; P = 0.02).

CONCLUSIONS

Nestin IHC positivity is associated with the poor clinical outcomes and reduced survival rates that characterize the gene expression basal-like subtype. This easily applicable tool identifies ER+ poor prognosis basal phenotype patients that are currently being missed by "Triple negative" or "Core basal" IHC definitions.

Different prognosis of young breast cancer patients in their 20s and 30s depending on subtype: a nationwide study from the Korean Breast Cancer Society

PURPOSE

Numerous studies have demonstrated that breast cancer in young women (BCY) has unfavorable prognostic features and more unfavorable subtypes. However, few studies have evaluated the effect of subtype disparities on breast cancer prognosis by age, especially for BCY. We analyzed breast cancer mortality stratified by tumor subtype according to age among patients younger than 50 years.

METHODS

Data from the Korean Breast Cancer Society Registry for patients diagnosed with invasive breast cancer when aged less than 50 years between 2003 and 2010 were reviewed retrospectively.

RESULTS

We identified 30,793 patients with breast cancer who were eligible for analysis. Of these, 793 (2.6%) were aged 20-29 and 8926 (28.8%) were aged 30-39. Median follow-up duration was 84 months. Mean age was 42.4 years. Patients in their 20s were more likely to have cancer of advanced stage and higher nuclear grade, present with lymphovascular invasion, and have unfavorable subtypes. Patients in the 20s group showed worse prognosis. In multivariate analysis for overall survival (OS), the hazard ratio (HR) for patients in the 20s group was higher than that for the 30s and 40s groups, and patients with triple-negative breast cancer (TNBC) showed higher HR than patients with HER-2 or luminal subtype (all p < 0.0001). When stratified by subtype, luminal subtype showed significantly worse prognosis in the 20s group than the 30s and 40s groups, whereas HER-2 and TNBC subtypes showed no significant difference.

CONCLUSION

Patients in their 20s with breast cancer had unfavorable characteristics and worse prognosis than patients in their 30s and 40s. When stratified by tumor subtype, patients in their 20s with luminal subtype of breast cancer showed worse prognosis than older patients, whereas HER-2 and TNBC subtypes showed no significant differences.

Comparison of Estrogen and Progesterone Receptor Antibody Reagents Using Proficiency Testing Data

CONTEXT

- Immunohistochemical analysis of estrogen receptor (ER) and progesterone receptor (PgR) expression in breast cancer is the current standard of care and directly determines therapy. In 2010 the American Society of Clinical Oncology and the College of American Pathologists (ASCO/CAP) published guidelines for ER and PgR predictive testing, encompassing preanalytic, analytic, postanalytic factors; antibody validation; and proficiency testing.

OBJECTIVE

- To compare the performance of different antibody reagents for ER and PgR immunohistochemical analysis by using CAP proficiency testing data.

DESIGN

- The CAP PM2 survey uses tissue microarrays of ten 2-mm cores per slide. We analyzed survey data from 80 ER and 80 PgR cores by antibody clone from more than 1200 laboratories.

RESULTS

- Laboratories used the ER antibodies SP1 (72%), 6F11 (17%), 1D5 (3%), and the PgR antibodies 1E2 (61%), 16 (12%), PgR-636 (13%), PgR-1294 (8%) in 2015. While 63 of 80 ER cores (79%) were scored similarly using each of the 3 antibodies, there were significant differences for others, with SP1 yielding more positive interpretations. Four cores were scored as ER negative by more than half of the laboratories using 1D5 or 6F11, while SP1 produced positive results in more than 70% of laboratories using that antibody. Despite the greater variety of PgR antibody reagents and greater PgR tumor heterogeneity, 61 of 80 cores (76%) were scored similarly across the 4 PgR antibodies.

CONCLUSIONS

- Accurate ER and PgR testing in breast cancer is crucial for appropriate treatment. The CAP proficiency testing data demonstrate differences in staining results by ER clone, with SP1 yielding more positive results.