Journal: NPJ breast cancer
In this pilot study, we introduce a machine learning framework to identify relationships between cancer tissue morphology and hormone receptor pathway activation in breast cancer pathology hematoxylin and eosin (H&E)-stained samples. As a proof-of-concept, we focus on predicting clinical estrogen receptor (ER) status-defined as greater than one percent of cells positive for estrogen receptor by immunohistochemistry staining-from spatial arrangement of nuclear features. Our learning pipeline segments nuclei from H&E images, extracts their position, shape and orientation descriptors, and then passes them to a deep neural network to predict ER status. After training on 57 tissue cores of invasive ductal carcinoma (IDC), our pipeline predicted ER status in an independent test set of patient samples (AUC ROC = 0.72, 95%CI = 0.55-0.89, n = 56). This proof of concept shows that machine-derived descriptors of morphologic histology patterns can be correlated to signaling pathway status. Unlike other deep learning approaches to pathology, our system uses deep neural networks to learn spatial relationships between pre-defined biological features, which improves the interpretability of the system and sheds light on the features the neural network uses to predict ER status. Future studies will correlate morphometry to quantitative measures of estrogen receptor status and, ultimately response to hormonal therapy.
The non-receptor tyrosine kinase, PTK6/BRK, is highly expressed in multiple tumor types, including prostate, ovarian, and breast cancers, and regulates oncogenic phenotypes such as proliferation, migration, and survival. PTK6 inhibition also overcomes targeted therapy resistance of HER2+ breast cancer. Although PTK6 is highly expressed in ER+ Luminal breast cancers, the role of PTK6 in this subtype has not been elucidated. In this study, we investigated the functions of PTK6 in ER+ Luminal breast cancer cells, including those that are relatively resistant to estrogen deprivation or targeted endocrine therapies used in the treatment of ER+ cancers. Enhanced expression of PTK6 in ER+ breast cancer cells enhances growth of ER+ breast cancer cells, including tamoxifen-treated cells. Downregulation of PTK6 in ER+ breast cancer cells, including those resistant to tamoxifen, fulvestrant, and estrogen deprivation, induces apoptosis, as evidenced by increased levels of cleaved PARP, and an increase in the AnnexinV+ population. PTK6 downregulation impairs growth of these cells in 3D Matrigel™ cultures, and virtually abrogates primary tumor growth of both tamoxifen-sensitive and resistant MCF-7 xenografts. Finally, we show that p38 MAPK activation is critical for PTK6 downregulation-induced apoptosis, a mechanism that we previously reported for survival of HER2+ breast cancer cells, highlighting conserved mechanisms of survival regulation by PTK6 across breast cancer subtypes. In conclusion, our studies elucidate critical functions of PTK6 in ER+ Luminal breast cancers and support PTK6 as an attractive therapeutic target for ER+ breast cancers.
The Recurrence Score® is increasingly used in node-positive ER+ HER2-negative breast cancer. This retrospective analysis of a prospectively designed registry evaluated treatments/outcomes in node-positive breast cancer patients who were Recurrence Score-tested through Clalit Health Services from 1/2006 through 12/2011 (N = 709). Medical records were reviewed to verify treatments/recurrences/survival. Median follow-up, 5.9 years; median age, 62 years; 53.9% grade 2; 69.8% tumors ≤ 2 cm; 84.5% invasive ductal carcinoma; 42.0% N1mi, and 37.2%/15.5%/5.2% with ½/3 positive nodes; 53.4% Recurrence Score < 18, 36.4% Recurrence Score 18-30, and 10.2% Recurrence Score ≥ 31. Overall, 26.9% received adjuvant chemotherapy: 7.1%, 39.5%, and 86.1% in the Recurrence Score < 18, 18-30, and ≥ 31 group, respectively. The 5-year Kaplan-Meier estimates for distant recurrence were 3.2%, 6.3%, and 16.9% for these respective groups and the corresponding 5-year breast cancer death estimates were 0.5%, 3.4%, and 5.7%. In Recurrence Score < 18 patients, 5-year distant-recurrence rates for N1mi/1 positive node/2-3 positive nodes were 1.2%/4.4%/5.4%. As patients were not randomized to treatment and treatment decision is heavily influenced by Recurrence Score, analysis of 5-year distant recurrence by chemotherapy use was exploratory and should be interpreted cautiously: In Recurrence Score < 18, recurrence rate was 7.7% in chemotherapy-treated (n = 27) and 2.9% in chemotherapy-untreated patients (n = 352); P = 0.245. In Recurrence Score 18-30, recurrence rate in chemotherapy-treated patients (n = 102) was significantly lower than in untreated patients (n = 156) (1.0% vs. 9.7% P = 0.019); in Recurrence Score ≤ 25 (the RxPONDER study cutoff), recurrence rate was 2.3% in chemotherapy-treated (n = 89) and 4.4% in chemotherapy-untreated patients (n = 488); P = 0.521. In conclusion, our findings support using endocrine therapy alone in ER+ HER2-negative breast cancer patients with micrometastases/1-3 positive nodes and Recurrence Score < 18.
The 21-gene Recurrence Score® (RS) assay is a validated prognostic/predictive tool in ER + early-stage breast cancer. However, clinical outcome data from prospective studies in RS ≥ 11 patients are lacking, as are relevant real-life clinical practice data. In this retrospective analysis of a prospectively designed registry, we evaluated treatments/clinical outcomes in patients undergoing RS-testing through Clalit Health Services. The analysis included N0 ER + HER2-negative breast cancer patients who were RS-tested from 1/2006 through 12/2010. Medical records were reviewed to verify treatments/recurrences/survival. The cohort included 1801 patients (median follow-up, 6.2 years). Median age was 60 years, 50.4% were grade 2 and 81.1% had invasive ductal carcinoma; 48.9% had RS < 18, 40.7% RS 18-30, and 10.4% RS ≥ 31, with chemotherapy use of 1.4, 23.7, and 87.2%, respectively. The 5-year Kaplan-Meier estimates for distant recurrence were 0.8, 3.0, and 8.6%, for patients with RS < 18, RS 18-30 and RS ≥ 31, respectively; the corresponding 5-year Kaplan-Meier estimates for breast cancer death were 0.0, 0.9, and 6.2%. Chemotherapy-untreated patients with RS < 11 (n = 304) and 11-25 (n = 1037) (TAILORx categorization) had 5-year Kaplan-Meier estimates for distant recurrence risk/breast cancer death of 1.0%/0.0% and 1.3%/0.4%, respectively. Our results extend those of the prospective TAILORx trial: the 5-year Kaplan-Meier estimates for distant recurrence and breast cancer death rate for the RS < 18 patients were very low supporting the use of endocrine therapy alone. Furthermore, in chemotherapy-untreated patients with RS 11-25 (where TAILORx patients were randomized to chemoendocrine or endocrine therapy alone), 5-year distant recurrence rates were also very low, suggesting that chemotherapy would not have conferred clinically meaningful benefit.
Breast cancer diagnosed during pregnancy (BCP) is a rare and highly challenging disease. To investigate the impact of pregnancy on the biology of breast cancer, we conducted a comparative analysis of a cohort of BCP patients and non-pregnant control patients by integrating gene expression, copy number alterations and whole genome sequencing data. We showed that BCP exhibit unique molecular characteristics including an enrichment of non-silent mutations, a higher frequency of mutations in mucin gene family and an enrichment of mismatch repair deficiency mutational signature. This provides important insights into the biology of BCP and suggests that these features may be implicated in promoting tumor progression during pregnancy. In addition, it provides an unprecedented resource for further understanding the biology of breast cancer in young women and how pregnancy could modulate tumor biology.
This study was undertaken to determine the feasibility of enrolling breast cancer patients on a single-agent-targeted therapy trial before neoadjuvant chemotherapy. Specifically, we evaluated talazoparib in patients harboring a deleterious BRCA mutation (BRCA+). Patients with a germline BRCA mutation and ≥1 cm, HER2-negative primary tumors were eligible. Study participants underwent a pretreatment biopsy, 2 months of talazoparib, off-study core biopsy, anthracycline, and taxane-based chemotherapy ± carboplatin, followed by surgery. Volumetric changes in tumor size were determined by ultrasound at 1 and 2 months of therapy. Success was defined as 20 patients accrued within 2 years and <33% experienced a grade 4 toxicity. The study was stopped early after 13 patients (BRCA1 + n = 10; BRCA2 + n = 3) were accrued within 8 months with no grade 4 toxicities and only one patient requiring dose reduction due to grade 3 neutropenia. The median age was 40 years (range 25-55) and clinical stage included I (n = 2), II (n = 9), and III (n = 2). Most tumors (n = 9) were hormone receptor-negative, and one of these was metaplastic. Decreases in tumor volume occurred in all patients following 2 months of talazoparib; the median was 88% (range 30-98%). Common toxicities were neutropenia, anemia, thrombocytopenia, nausea, dizziness, and fatigue. Single-agent-targeted therapy trials are feasible in BRCA+ patients. Given the rapid rate of accrual, profound response and favorable toxicity profile, the feasibility study was modified into a phase II study to determine pathologic complete response rates after 4-6 months of single-agent talazoparib.
Germline variants that affect the expression or function of proteins contribute to phenotypic variation in humans and likely determine individual characteristics and susceptibility to diseases including cancer. A number of high penetrance germline variants that increase cancer risk have been identified and studied, but germline functional polymorphisms are not typically considered in the context of cancer biology, where the focus is primarily on somatic mutations. Yet, there is evidence from familial cancers indicating that specific cancer subtypes tend to arise in carriers of high-risk germline variants (e.g., triple negative breast cancers in mutated BRCA carriers), which suggests that pre-existing germline variants may determine which complementary somatic driver mutations are needed to drive tumorigenesis. Recent genome sequencing studies of large breast cancer cohorts reported only a handful of highly recurrent driver mutations, suggesting that different oncogenic events drive individual cancers. Here, we propose that germline polymorphisms can function as oncogenic modifiers, or co-oncogenes, and these determine what complementary subsequent somatic events are required for full malignant transformation. Therefore, we propose that germline aberrations should be considered together with somatic mutations to determine what genes drive cancer and how they may be targeted.
Metastatic breast cancer (MBC) patients with bone only metastasis (BOM) are a unique population with limited characterization. We identified patients followed at MD Anderson Cancer Center from 01/01/1997 to 12/31/2015 for at least 6 months with a BOM diagnosis as first site of metastasis. Tumor subtype (TS) was assessed by initial breast biopsy immunohistochemistry using hormonal receptor (HR) and HER2 status, with four subtypes identified: HR+/HER2-, HR+/HER2+, HR-/HER2-, HR-/HER2+. HR+ was defined as estrogen receptor or progesterone receptor ≥1%. We identified 1445 patients with BOM, 1048 with TS data available. Among these patients, the majority were HR+/HER2- (78%). Median time from breast cancer diagnosis to first bone metastasis was 2.3 years (95% CI 2.1, 2.5) and varied significantly by TS, with longer time to distant disease in HR+/HER2- patients relative to all other TS (p < .0001). Median overall survival (OS) from breast cancer diagnosis was 8.7 years (95% CI 8.0, 9.7) and varied significantly by TS with poorer OS for HR-/HER2- and HR-/HER2+ patients relative to HR+/HER2- TS (p < .0001). The 442 patients with de novo BOM disease, defined as bone metastasis diagnosis within 4 months of breast cancer diagnosis, had significantly shorter OS (p < .0001). Overall, several higher risk BOM subsets were identified in this analysis, most notably HR-/HER2+ and HR-/HER2- TS and de novo BOM patients.
Several studies have demonstrated the feasibility of molecular screening of tumour samples for matching patients with cancer to targeted therapies. However, most of them have been carried out at institutional or national level. Herein, we report on the pilot phase of AURORA (NCT02102165), a European multinational collaborative molecular screening initiative for advanced breast cancer patients. Forty-one patients were prospectively enroled at four participating centres across Europe. Metastatic tumours were biopsied and profiled using an Ion Torrent sequencing platform at a central facility. Sequencing results were obtained for 63% of the patients in real-time with variable turnaround time stemming from delays between patient consent and biopsy. At least one clinically actionable mutation was identified in 73% of patients. We used the Illumina sequencing technology for orthogonal validation and achieved an average of 66% concordance of substitution calls per patient. Additionally, copy number aberrations inferred from the Ion Torrent sequencing were compared to single nucleotide polymorphism arrays and found to be 59% concordant on average. Although this study demonstrates that powerful next generation genomic techniques are logistically ready for international molecular screening programs in routine clinical settings, technical challenges remain to be addressed in order to ensure the accuracy and clinical utility of the genomic data.
Radiomics is an emerging technology for imaging biomarker discovery and disease-specific personalized treatment management. This paper aims to determine the benefit of using multi-modality radiomics data from PET and MR images in the characterization breast cancer phenotype and prognosis. Eighty-four features were extracted from PET and MR images of 113 breast cancer patients. Unsupervised clustering based on PET and MRI radiomic features created three subgroups. These derived subgroups were statistically significantly associated with tumor grade (p = 2.0 × 10-6), tumor overall stage (p = 0.037), breast cancer subtypes (p = 0.0085), and disease recurrence status (p = 0.0053). The PET-derived first-order statistics and gray level co-occurrence matrix (GLCM) textural features were discriminative of breast cancer tumor grade, which was confirmed by the results of L2-regularization logistic regression (with repeated nested cross-validation) with an estimated area under the receiver operating characteristic curve (AUC) of 0.76 (95% confidence interval (CI) = [0.62, 0.83]). The results of ElasticNet logistic regression indicated that PET and MR radiomics distinguished recurrence-free survival, with a mean AUC of 0.75 (95% CI = [0.62, 0.88]) and 0.68 (95% CI = [0.58, 0.81]) for 1 and 2 years, respectively. The MRI-derived GLCM inverse difference moment normalized (IDMN) and the PET-derived GLCM cluster prominence were among the key features in the predictive models for recurrence-free survival. In conclusion, radiomic features from PET and MR images could be helpful in deciphering breast cancer phenotypes and may have potential as imaging biomarkers for prediction of breast cancer recurrence-free survival.