Technology Insight: emerging techniques to predict response to preoperative chemotherapy in breast cancer

Primary systemic therapy in HER2-positive operable breast cancer using trastuzumab and chemotherapy: efficacy data, cardiotoxicity and long-term follow-up in 142 patients diagnosed from 2005 to 2016 at a single institution

OBJECTIVE

The aim of this study was to evaluate the efficacy, cardiotoxicity profile and long-term benefits of neoadjuvant therapy in human epidermal growth factor receptor 2-positive operable breast cancer patients.

PATIENTS AND METHODS

A total of 142 patients diagnosed from 2005 to 2016 were included in the study. The treatment consisted of a sequential regimen of taxanes and anthracyclines plus trastuzumab. The clinical and pathological responses were evaluated and correlated with clinical and biological factors. The cardiotoxicity profile and long-term benefits were analyzed.

RESULTS

The median age was 49 years, and 4%, 69% and 27% of patients had stage I, II and III breast cancer, respectively, while 10% had inflammatory breast cancer at diagnosis. Hormone receptor (HR) status was negative in 43%, and 62% had grade III breast cancer. The clinical complete response rate was 49% and 63% as assessed using ultrasound and magnetic resonance imaging, respectively, and this allowed a high rate of conservative surgery (66%). The pathological complete response (pCR) rate was 52%, and it was higher in HR-negative (64%) patients than in HR-positive (41%) patients and in grade III breast cancer (53%) patients than in grade I-II breast cancer (45%) patients. Patients who achieved pCR had longer disease-free survival and a trend toward improved overall survival. A total of 2% of patients showed a 10% decrease in left ventricular ejection fraction to <50% during treatment. All patients except one recovered after discontinuation of trastuzumab.

CONCLUSION

A sequential regimen of taxanes and anthracyclines plus trastuzumab was effective, with high pCR rates and long-term benefit, and had a very good cardiotoxicity profile.

Association of immunohistochemically defined molecular subtypes with clinical response to presurgical chemotherapy in patients with advanced breast cancer

Gene expression profiling (GEP) has identified several molecular subtypes of breast cancer, with different clinico-pathologic features and exhibiting different responses to chemotherapy. However, GEP is expensive and not available in the developing countries where the majority of patients present at advanced stage. The St Gallen Consensus in 2011 proposed use of a simplified, four immunohistochemical (IHC) biomarker panel (ER, PR, HER2, Ki67/Tumor Grade) for molecular classification. The present study was conducted in 75 newly diagnosed patients of breast cancer with large (>5cm) tumors to evaluate the association of IHC surrogate molecular subtype with the clinical response to presurgical chemotherapy, evaluated by the WHO criteria, 3 weeks after the third cycle of 5 flourouracil, adriamycin, cyclophosphamide (FAC regimen). The subtypes of luminal, basal-like and HER2 enriched were found to account for 36.0 % (27/75), 34.7 % (26/75) and 29.3% (22/75) of patients respectively. Ten were luminal A and 14 luminal B (8 HER2 negative and 6HER2 positive). The triple negative breast cancer (TNBC) was most sensitive to chemotherapy with 19% achieving clinical-complete-response (cCR) followed by HER2 enriched (2/22 (9%) cCR), luminal B (1/6 (7%) cCR) and luminal A (0/10 (0%) cCR). Heterogeneity was observed within each subgroup, being most marked in the TNBC although the most responding tumors, 8% developing clinical-progressive-disease. The study supports association of molecular subtypes with response to chemotherapy in patients with advanced breast cancer and the existence of further heterogeneity within subtypes.

Gene expression profiles for predicting the efficacy of the anticancer drug 5-fluorouracil in breast cancer

Chemotherapy is an important postsurgery adjuvant therapy in the treatment of breast cancer. However, because of the individual genotype differences of patients, the drug efficacy differs from person to person, even when the same chemotherapy drug is administered. The purpose of this research was to probe the gene expression profiles to predict the efficacy of 5-fluorouracil (5-FU), the common drug used in chemotherapy for various type of cancers, in Taiwanese breast cancer patients. Microarray analysis was conducted on the cancer cell line ZR-75-1 with and without 5-FU stimulation to identify the differentially expressed genes. The significant overexpressed gene groups were selected after bioinformatics software analysis to explore the molecular mechanism of 5-FU. Six strains of breast cancer cell line purchased from American Type Culture Collection were used to analyze the expression profiles of the above target gene groups. IL18, CCL28, CXCL2, SOD1, HRAS, FDXR, and CHI3L1 genes were significantly differentially expressed in 5-FU responder and nonresponder cell lines. The selected gene groups were validated with 20 strains of breast cancer primary cultures established previously in our laboratory. The experimental results demonstrated that FAM46A, IL18, CCL28, TNF, CXCL2, PLEKHA8, HRAS, FDXR, and CHI3L1 genes showed statistically significant differential expression between primary breast cancer culture cells that respond and nonrespond to 5-FU. Six genes, IL18, CCL28, CXCL2, HRAS, FDXR, and CHI3L1, showed significant differential expression pattern in both American Type Culture Collection and primary breast cancer cultured cells. The findings of this study may serve as basis for predicting the effectiveness of 5-FU on breast cancer.

Metastatic gene signatures and emerging novel prognostic tests in the management of early stage breast cancer

Gene expression profiling using DNA microarrays allows simultaneous measurement of thousands of mRNA transcripts in a single experiment. Results from gene expression profiling studies have fundamentally altered our view of breast cancer, which is no longer regarded as a single disease but as several molecularly and biologically distinct neoplastic diseases. This technology has also yielded novel diagnostic assays that have started to have an impact on clinical care. This is a rapidly evolving field, and the constraints of space do not allow us to discuss many of the published studies. Therefore, in this review, we will summarize the results of those gene expression studies that are conceptually and practically most important and discuss some of the limitations and the future promise of this technology.

New generation of molecular prognostic and predictive tests for breast cancer

Breast cancer is a clinically heterogeneous disease, and it is generally accepted that the different clinical courses of patients with histologically similar tumors are due to molecular differences among cancers. Therefore, detailed molecular analysis of the cancer could yield prognostic information. Recent advances in molecular analytical techniques have led to rapid expansion of novel diagnostics designed to personalize breast cancer care. Diagnostic companies are also increasingly adopting a clinical trial-based approach to develop their products. This article reviews some of the most important advances in this field in the past few years, including the emergence of several multigene and prognostic predictors, as well as methods allowing enumeration of circulating tumor cells that are currently offered as commercially available diagnostic assays.

A dolphin peripheral blood leukocyte cDNA microarray for studies of immune function and stress reactions

A microarray focused on stress response and immune function genes of the bottlenosed dolphin has been developed. Random expressed sequence tags (ESTs) were isolated and sequenced from two dolphin peripheral blood leukocyte (PBL) cDNA libraries biased towards T- and B-cell gene expression by stimulation with IL-2 and LPS, respectively. A total of 2784 clones were sequenced and contig analysis yielded 1343 unigenes (archived and annotated at ). In addition, 52 dolphin genes known to be important in innate and adaptive immune function and stress responses of terrestrial mammals were specifically targeted, cloned and added to the unigene collection. The set of dolphin sequences printed on a cDNA microarray comprised the 1343 unigenes, the 52 targeted genes and 2305 randomly selected (but unsequenced) EST clones. This set was printed in duplicate spots, side by side, and in two replicates per slide, such that the total number of features per microarray slide was 19,200, including controls. The dolphin arrays were validated and transcriptomic profiles were generated using PBL from a wild dolphin, a captive dolphin and dolphin skin cells. The results demonstrate that the array is a reproducible and informative tool for assessing differential gene expression in dolphin PBL and in other tissues.

Whole genome expression analysis for biologic rational pathway modeling: application in cancer prognosis and therapy prediction

Using semi-quantitative microarray technology, almost every one of the approximately 30 000 human genes can be analyzed simultaneously with a low rate of false-positives, a high specificity, and a high quantification accuracy. This is supported by data from comparative studies of microarrays and reverse-transcription PCR for established cancer genes including those for epidermal growth factor receptor (EGFR), human epidermal growth factor receptor-2 (HER2/ERBB2), estrogen receptor (ESR1), progesterone receptor (PGR), urokinase-type plasminogen activator (PLAU), and plasminogen activator inhibitor-1 (SERPINE1). As such, semi-quantitative expression data provide an almost completely comprehensive background of biological knowledge that can be applied to cancer diagnostics. In clinical terms, expression profiling may be able to provide significant information regarding (i) the identification of high-risk patients requiring aggressive chemotherapy; (ii) the pathway control of therapy predictive parameters (e.g. ESR1 and HER2); (iii) the discovery of targets for biologically rational therapeutics (e.g. capecitabine and trastuzumab); (iv) additional support for decisions about switching therapy; (v) target discovery; and (vi) the prediction of the course of new therapies in clinical trials. In conclusion, whole genome expression analysis might be able to determine important genes related to cancer progression and adjuvant chemotherapy resistance, especially in the context of new approaches involving primary systemic chemotherapy. In this review, we will survey the current progress in whole genome expression analyses for cancer prognosis and prediction. Special emphasis is given to the approach of combining biostatistical analysis of expression data with knowledge of biochemical and genetic pathways.

DNA arrays as predictors of efficacy of adjuvant/neoadjuvant chemotherapy in breast cancer patients: current data and issues on study design

Chemotherapy provides variable benefit to patients with breast cancer, with usually modest but occasionally severe side effects. Hence, there is a need to identify predictive biomarkers for its efficacy. DNA arrays have been used in this setting as potential novel predictive diagnostic tools. Several gene signatures and single gene markers were proposed to predict response to chemotherapy. Although this technology offers interesting perspectives through large-scale analysis of the transcriptome, its ability to identify clinically relevant predictors is highly dependent on study design. In the present manuscript, we will review currently available results of breast cancer pharmacogenomics and focus on aspects of study design that are critical to reliably identify predictive biomarkers using DNA array technology. We will discuss whether studies should be done in the overall, unselected breast cancer population or in specific homogeneous molecular subclasses. Next, we will compare advantages and limitations of cohort-based and case-control studies. The choice of end-point to discriminate between sensitive and resistant patients will also be examined.

Proteomic technology for biomarker profiling in cancer: an update

The progress in the understanding of cancer progression and early detection has been slow and frustrating due to the complex multifactorial nature and heterogeneity of the cancer syndrome. To date, no effective treatment is available for advanced cancers, which remain a major cause of morbidity and mortality. Clearly, there is urgent need to unravel novel biomarkers for early detection. Most of the functional information of the cancer-associated genes resides in the proteome. The later is an exceptionally complex biological system involving several proteins that function through posttranslational modifications and dynamic intermolecular collisions with partners. These protein complexes can be regulated by signals emanating from cancer cells, their surrounding tissue microenvironment, and/or from the host. Some proteins are secreted and/or cleaved into the extracellular milieu and may represent valuable serum biomarkers for diagnosis purpose. It is estimated that the cancer proteome may include over 1.5 million proteins as a result of posttranslational processing and modifications. Such complexity clearly highlights the need for ultra-high resolution proteomic technology for robust quantitative protein measurements and data acquisition. This review is to update the current research efforts in high-resolution proteomic technology for discovery and monitoring cancer biomarkers.

Nomograms to predict pathologic complete response and metastasis-free survival after preoperative chemotherapy for breast cancer

PURPOSE

To combine clinical variables associated with pathologic complete response (pCR) and distant metastasis-free survival (DMFS) after preoperative chemotherapy (PC) into a prediction nomogram.

PATIENTS AND METHODS

Data from 496 patients treated with anthracycline PC at the Institut Gustave Roussy were used to develop and calibrate a nomogram for pCR based on multivariate logistic regression. This nomogram was tested on two independent cohorts of patients treated at the M.D. Anderson Cancer Center. The first cohort (n = 337) received anthracycline; the second cohort (n = 237) received a combination of paclitaxel and anthracycline PC. A separate nomogram to predict DMFS was developed using Cox proportional hazards regression model.

RESULTS

The pCR nomogram based on clinical stage, estrogen receptor status, histologic grade, and number of preoperative chemotherapy cycles had good discrimination and calibration in the training and the anthracycline-treated validation sets (concordance indices, 0.77, 0.79). In the paclitaxel plus anthracycline group, when the predicted pCR rate was less than 14%, the observed rate was 7.5%; for a predicted rate of > or = 38%, the actual rate was 85%. For a predicted rate between 14% to 38%, the observed rates were 50% with weekly and 27% with 3-weekly paclitaxel. This indicates that patients with intermediate chemotherapy sensitivity benefit the most from the optimized schedule of paclitaxel. Patients unlikely to achieve pCR to anthracylines remain at low probability for pCR, even after inclusion of paclitaxel. The nomogram for DMFS had a concordance index of 0.72 in the validation set and outperformed other prediction tools (P = .02).

CONCLUSION

Our nomograms predict pCR accurately and can serve as a basis to integrate future molecular markers into a clinical prediction model.

Development of pharmacogenomic markers to select preoperative chemotherapy for breast cancer

Individualized selection of the most effective adjuvant (or neoadjuvant) chemotherapy for breast cancer based on the molecular characteristics of the tumor could improve the risk:benefit ratio of current therapies. It could also streamline the development of new regimens for those who are unlikely to benefit from existing drugs. It is expected that combinations of markers will be more informative to predict response than any single gene and may yield regimen-specific predictors. Novel molecular analytical tools, particularly transcriptional profiling, provide a method to test this hypothesis. Several small exploratory studies have shown encouraging results. This article reviews recent progress in this field including experience from the breast cancer pharmacogenomic marker discovery program at the Nellie B. Connally Breast Center of the University of Texas M. D. Anderson Cancer Center. This manuscript is based on a presentation that was given during the Presidential Symposium of the annual meeting of the Japanese Breast Cancer Society in 2004.