Re-interpretation of PAM50 gene expression as quantitative tumor dimensions shows utility for clinical trials: application to prognosis and response to paclitaxel in breast cancer.

BACKGROUND: We recently showed PAM50 gene expression data can be represented by five quantitative, orthogonal, multi-gene breast tumor traits. These novel tumor 'dimensions' were superior to categorical intrinsic subtypes for clustering in high-risk breast cancer pedigrees, indicating potential to represent underlying genetic susceptibilities and biological pathways. Here we explore the prognostic and predictive utility of these dimensions in a sub-study of GEICAM/9906, a Phase III randomized prospective clinical trial of paclitaxel in breast cancer. METHODS: Tumor dimensions, PC1-PC5, were calculated using pre-defined coefficients. Univariable and multivariable Cox proportional hazards (PH) models for disease-free survival (DFS) were used to identify associations between quantitative dimensions and prognosis or response to the addition of paclitaxel. Results were illustrated using Kaplan-Meier curves. RESULTS: Dimensions PC1 and PC5 were associated with DFS (Cox PH p = 6.7 [Formula: see text] 10-7 and p = 0.036), remaining significant after correction for standard clinical-pathological prognostic characteristics. Both dimensions were selected in the optimal multivariable model, together with nodal status and tumor size (Cox PH p = 1.4 [Formula: see text] 10-12). Interactions with treatment were identified for PC3 and PC4. Response to paclitaxel was restricted to tumors with low PC3 and PC4 (log-rank p = 0.0021). Women with tumors high for PC3 or PC4 showed no survival advantage. CONCLUSIONS: Our proof-of-concept application of quantitative dimensions illustrated novel findings and clinical utility beyond standard clinical-pathological characteristics and categorical intrinsic subtypes for prognosis and predicting chemotherapy response. Consideration of expression data as quantitative tumor dimensions offers new potential to identify clinically important patient subsets in clinical trials and advance precision medicine.

Differences in molecular features of triple-negative breast cancers based on the age at diagnosis.

BACKGROUND: Although the proportion of triple-negative breast cancers (TNBCs) diagnosed among older women is low, the number of TNBC cases is substantial because of the high incidence of breast cancer after the age of 65 years. The molecular features of TNBC in this age group have not been well described. METHODS: This study examined a population-based cohort of women with stage I to III TNBC diagnosed between the ages of 25 and 91 years with the PAM50 gene expression subtyping assay. The concordance between the TNBC classification by immunohistochemistry and the gene expression classification by PAM50, the expression of individual genes, and 5-year recurrence and breast cancer mortality in older women (≥65 years old) and younger women (<50 years old) was assessed. RESULTS: The molecular subtype distribution in TNBC was significantly different according to the age at diagnosis. TNBC was more likely to be classified as basal-like in women younger than 50 years (sensitivity, 0.91; 95% confidence interval, 0.77-0.97) than women 65 years old or older (sensitivity, 0.72; 95% confidence interval, 0.48-0.87); 35% of clinical TNBC cases in the latter group were the human epidermal growth factor receptor 2 (HER2)-enriched subtype by molecular classification. Older women with TNBC also had significantly higher expression of ERBB2 and lower expression of all 10 proliferation-associated genes tested (P < .01). The risk of breast cancer death within 5 years was significantly higher in women with TNBC in comparison with women with hormone receptor-positive cancers in all age groups. CONCLUSIONS: This study revealed differences in molecular subtypes among clinical TNBC cases based on patient age. A potentially targetable HER2-enriched group raises the possible need for intrinsic subtyping in older women with TNBC.

Membrane proteins significantly restrict exosome mobility.

Exosomes are membrane nanovesicles implicated in cell-to-cell signaling in which they transfer their molecular cargo from the parent to the recipient cells. This role essentially depends on the exosomes' small size, which is the prerequisite for their rapid migration through the crowded extracellular matrix and into and out of circulation. Here we report much lower exosome mobility than expected from the size of their vesicles, implicate membrane proteins in a substantially impeded rate of migration, and suggest an approach to quantifying the impact. The broadly distributed excess hydrodynamic resistance provided by surface proteins produces a highly heterogeneous and microenvironment-dependent hindrance to exosome mobility. The implications of the findings on exosome-mediated signaling are discussed.

Body mass index, PAM50 subtype, recurrence, and survival among patients with nonmetastatic breast cancer.

BACKGROUND: Studies of obesity and survival among patients with breast cancer produce conflicting results, possibly because of heterogeneity by molecular subtype. METHODS: This study examined whether the association of body mass index (BMI) at diagnosis with breast cancer recurrence and survival varied across subtypes defined by PAM50 (Prediction Analysis of Microarray 50) gene expression. Included were 1559 Kaiser Permanente Northern California members ages 18 to 79 years who had PAM50 assays and were diagnosed with American Joint Committee on Cancer stage I through III breast cancer from 1996 to 2013. Patients reported weight and height. Cox regression models were adjusted for age, menopause, race/ethnicity, stage, and chemotherapy. RESULTS: Over a median of 9 years (maximum, 19 years), 378 women developed recurrent disease, and 312 died from breast cancer. Overall, BMI was not associated with breast cancer recurrence or survival when controlling for subtype (eg, the hazard ratio per 5 kg/m2 of BMI was 1.05 [95% confidence interval, 0.95-1.15] for breast cancer-specific death). However, associations varied by subtype. Among women with luminal A cancers, those who had class II/III obesity, but not class I obesity or overweight, had worse outcomes. When women who had a BMI ≥35 kg/m2 were compared with those who had a BMI from 18.5 to <25 kg/m2 , the hazard ratio was 2.24 (95% confidence interval,1.22-4.11) for breast cancer-specific death and 1.24 (95% confidence interval, 1.00-1.54) for recurrence. There was no association within luminal B, basal-like or human epidermal growth factor over-expressing subtypes. CONCLUSIONS: Among patients who had accurately classified breast cancer subtypes based on gene expression, a BMI ≥35 kg/m2 was adversely associated with outcomes only among those who had luminal A cancers. Research is needed into whether tailoring recommendations for weight management to tumor characteristics will improve outcomes. Cancer 2017;123:2535-42. © 2017 American Cancer Society.

Basal biomarkers nestin and INPP4b identify intrinsic subtypes accurately in breast cancers that are weakly positive for oestrogen receptor.

AIMS: Recent evidence indicates that weakly positive immunohistochemical staining of oestrogen receptor (ER) is not associated reliably with a luminal subtype, with the majority reclassified as basal-like by gene expression profile. In this study we assessed the capacity of recently identified immunohistochemical markers of basal-like subtype not dependent upon ER status - positive expression of nestin or loss of inositol polyphosphate-4-phosphatase (INPP4b) - to discriminate intrinsic subtypes, focusing on clinically problematic cases with weak ER positivity. METHODS AND RESULTS: Formalin-fixed paraffin-embedded blocks, enriched for large proportions of ER-negative and ER weakly positive breast cancers, were selected from two previous studies conducted in the period 2008-13 and used for (i) RNA extraction for 50-gene subtype predictor (PAM50) intrinsic subtyping and (ii) tissue microarray construction for immunohistochemical assessment of nestin and INPP4b. Fifty-eight cases were weakly positive for ER (Allred 3-5), among which 28 (48%) were assigned as basal-like by PAM50 gene expression. In these 58 cases, the nestin/INPP4b panel identified 23 basal-like cases with a positive predictive value of 87% [95% confidence interval (CI) 78-95%] and excluded luminal subtype with a negative predictive value of 95% (95% CI 88-100%). Weakly positive ER patients assigned as basal-like by nestin/INPP4b definition demonstrated a median survival time of 45.8 months, significantly lower than 65 months among other ER weakly positive cases (P = 0.012). CONCLUSIONS: Immunohistochemical assessment of nestin and INPP4b provides an accurate, accessible and inexpensive tool to identify basal-like breast cancer subtype in the clinically problematic setting of weak ER positivity. This panel identifies poor prognosis patients who might need strong considerations for non-endocrine-based therapies.

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

The estrogen receptor (ER) is a key predictive biomarker in the treatment of breast cancer. There is uncertainty regarding the use of hormonal therapy in the setting of weakly positive ER by immunohistochemistry (IHC). We report intrinsic subtype classification on a cohort of ER weakly positive early-stage breast cancers. Consecutive cases of breast cancer treated by primary surgical resection were retrospectively identified from 4 centers that engage in routine external proficiency testing for breast biomarkers. ER-negative (Allred 0 and 2) and ER weakly positive (Allred 3-5) cases were included. Gene expression profiling was performed using qRT-PCR. Intrinsic subtype prediction was made based upon the PAM50 gene expression signature. 148 cases were included in the series: 60 cases originally diagnosed as ER weakly positive and 88 ER negative. Of the cases originally assessed as ER weakly positive, only 6 (10 %) were confirmed to be of luminal subtype by gene expression profiling; the remaining 90 % of cases were classified as basal-like or HER2-enriched subtypes. This was not significantly different than the fraction of luminal cases identified in the IHC ER-negative cohort (5 (5 %) luminal, 83(95 %) non-luminal). Recurrence-free, and overall, survival rates were similar in both groups (p = 0.4 and 0.5, respectively) despite adjuvant hormonal therapy prescribed in the majority (59 %) of weakly positive ER cases. Weak ER expression by IHC is a poor correlate of luminal subtype in invasive breast cancer. In the setting of highly sensitive and robust IHC methodology, cutoffs for ER status determination and subsequent systemic therapy should be revisited.

Prognostic ability of EndoPredict compared to research-based versions of the PAM50 risk of recurrence (ROR) scores in node-positive, estrogen receptor-positive, and HER2-negative breast cancer. A GEICAM/9906 sub-study.

There are several prognostic multigene-based tests for managing breast cancer (BC), but limited data comparing them in the same cohort. We compared the prognostic performance of the EndoPredict (EP) test (standardized for pathology laboratory) with the research-based PAM50 non-standardized qRT-PCR assay in node-positive estrogen receptor-positive (ER+) and HER2-negative (HER2-) BC patients receiving adjuvant chemotherapy followed by endocrine therapy (ET) in the GEICAM/9906 trial. EP and PAM50 risk of recurrence (ROR) scores [based on subtype (ROR-S) and on subtype and proliferation (ROR-P)] were compared in 536 ER+/HER2- patients. Scores combined with clinical information were evaluated: ROR-T (ROR-S, tumor size), ROR-PT (ROR-P, tumor size), and EPclin (EP, tumor size, nodal status). Patients were assigned to risk-categories according to prespecified cutoffs. Distant metastasis-free survival (MFS) was analyzed by Kaplan-Meier. ROR-S, ROR-P, and EP scores identified a low-risk group with a relative better outcome (10-year MFS: ROR-S 87 %; ROR-P 89 %; EP 93 %). There was no significant difference between tests. Predictors including clinical information showed superior prognostic performance compared to molecular scores alone (10-year MFS, low-risk group: ROR-T 88 %; ROR-PT 92 %; EPclin 100 %). The EPclin-based risk stratification achieved a significantly improved prediction of MFS compared to ROR-T, but not ROR-PT. All signatures added prognostic information to common clinical parameters. EPclin provided independent prognostic information beyond ROR-T and ROR-PT. ROR and EP can reliably predict risk of distant metastasis in node-positive ER+/HER2- BC patients treated with chemotherapy and ET. Addition of clinical parameters into risk scores improves their prognostic ability.

Defining breast cancer intrinsic subtypes by quantitative receptor expression.

PURPOSE: To determine intrinsic breast cancer subtypes represented within categories defined by quantitative hormone receptor (HR) and HER2 expression. METHODS: We merged 1,557 cases from three randomized phase III trials into a single data set. These breast tumors were centrally reviewed in each trial for quantitative ER, PR, and HER2 expression by immunohistochemistry (IHC) stain and by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), with intrinsic subtyping by research-based PAM50 RT-qPCR assay. RESULTS: Among 283 HER2-negative tumors with <1% HR expression by IHC, 207 (73%) were basal-like; other subtypes, particularly HER2-enriched (48, 17%), were present. Among the 1,298 HER2-negative tumors, borderline HR (1%-9% staining) was uncommon (n = 39), and these tumors were heterogeneous: 17 (44%) luminal A/B, 12 (31%) HER2-enriched, and only 7 (18%) basal-like. Including them in the definition of triple-negative breast cancer significantly diminished enrichment for basal-like cancer (p < .05). Among 106 HER2-positive tumors with <1% HR expression by IHC, the HER2-enriched subtype was the most frequent (87, 82%), whereas among 127 HER2-positive tumors with strong HR (>10%) expression, only 69 (54%) were HER2-enriched and 55 (43%) were luminal (39 luminal B, 16 luminal A). Quantitative HR expression by RT-qPCR gave similar results. Regardless of methodology, basal-like cases seldom expressed ER/ESR1 or PR/PGR and were associated with the lowest expression level of HER2/ERBB2 relative to other subtypes. CONCLUSION: Significant discordance remains between clinical assay-defined subsets and intrinsic subtype. For identifying basal-like breast cancer, the optimal HR IHC cut point was <1%, matching the American Society of Clinical Oncology and College of American Pathologists guidelines. Tumors with borderline HR staining are molecularly diverse and may require additional assays to clarify underlying biology.

Association of high obesity with PAM50 breast cancer intrinsic subtypes and gene expression.

BACKGROUND: Invasive breast cancers are now commonly classified using gene expression into biologically and clinically distinct tumor subtypes. However, the role of obesity in breast tumor gene expression and intrinsic subtype is unknown. METHODS: Early-stage breast cancer (BC) patients (n = 1,676) were sampled from two prospective cohorts. The PAM50 qRT-PCR assay was used to: a) assess tumor gene expression levels for ESR1, PGR, ERBB2, and 10 proliferation genes and b) classify tumors into intrinsic subtype (Luminal A, Luminal B, Basal-like, HER2-enriched, Normal-like). Body mass index (BMI) around BC diagnosis (kg/m(2)) was categorized as: underweight (<18.5), normal (18.5-24), overweight (25-29), mildly obese (30-34), and highly obese (≥35). In a cross-sectional analysis, we evaluated associations of BMI with gene expression using linear regression models, and associations of BMI with non-Luminal A intrinsic subtypes, compared with Luminal A subtype, using multinomial logistic regression. Statistical significance tests were two-sided. RESULTS: Highly obese women had tumors with higher expression of proliferation genes compared with normal weight women (adjusted mean difference = 0.44; 95% CI: 0.18, 0.71), yet mildly obese (adjusted mean difference = 0.16; 95% CI: -0.06, 0.38) and overweight (adjusted mean difference = 0.18; 95% CI: -0.01, 0.36) women did not. This association was stronger in postmenopausal women (p for interaction = 0.06). Being highly obese, however, was inversely associated with ESR1 expression (adjusted mean difference = -0.95; 95% CI: -1.47, -0.42) compared with being normal weight, whereas being mildly obese and overweight were not. In addition, women with Basal-like and Luminal B subtypes, relative to those with Luminal A subtype, were more likely to be highly obese, compared with normal-weight. CONCLUSIONS: ER expression may not increase correspondingly with increasing degree of obesity. Highly obese patients are more likely to have tumor subtypes associated with high proliferation and poorer prognosis.

Size and shape characterization of hydrated and desiccated exosomes.

Exosomes are stable nanovesicles secreted by cells into the circulation. Their reported sizes differ substantially, which likely reflects the difference in the isolation techniques used, the cells that secreted them, and the methods used in their characterization. We analyzed the influence of the last factor on the measured sizes and shapes of hydrated and desiccated exosomes isolated from the serum of a pancreatic cancer patient and a healthy control. We found that hydrated exosomes are close-to-spherical nanoparticles with a hydrodynamic radius that is substantially larger than the geometric size. For desiccated exosomes, we found that the desiccated shape and sizing are influenced by the manner in which drying occurred. Isotropic desiccation in aerosol preserves the near-spherical shape of the exosomes, whereas drying on a surface likely distorts their shapes and influences the sizing results obtained by techniques that require surface fixation prior to analysis.

A phase II study of UCN-01 in combination with irinotecan in patients with metastatic triple negative breast cancer.

Mutations in TP53 lead to a defective G1 checkpoint and the dependence on checkpoint kinase 1 (Chk1) for G2 or S phase arrest in response to DNA damage. In preclinical studies, Chk1 inhibition resulted in enhanced cytotoxicity of several chemotherapeutic agents. The high frequency of TP53 mutations in triple negative breast cancer (TNBC: negative for estrogen receptor, progesterone receptor, and HER2) make Chk1 an attractive therapeutic target. UCN-01, a non-selective Chk1 inhibitor, combined with irinotecan demonstrated activity in advanced TNBC in our Phase I study. The goal of this trial was to further evaluate this treatment in women with TNBC. Patients with metastatic TNBC previously treated with anthracyclines and taxanes received irinotecan (100-125 mg/m(2) IV days 1, 8, 15, 22) and UCN-01 (70 mg/m(2) IV day 2, 35 mg/m(2) day 23 and subsequent doses) every 42-day cycle. Peripheral blood mononuclear cells (PBMC) and tumor specimens were collected. Twenty five patients were enrolled. The overall response (complete response (CR) + partial response (PR)) rate was 4 %. The clinical benefit rate (CR + PR + stable disease ≥6 months) was 12 %. Since UCN-01 inhibits PDK1, phosphorylated ribosomal protein S6 (pS6) in PBMC was assessed. Although reduced 24 h post UCN-01, pS6 levels rose to baseline by day 8, indicating loss of UCN-01 bioavailability. Immunostains of γH2AX and pChk1(S296) on serial tumor biopsies from four patients demonstrated an induction of DNA damage and Chk1 activation following irinotecan. However, Chk1 inhibition by UCN-01 was not observed in all tumors. Most tumors were basal-like (69 %), and carried mutations in TP53 (53 %). Median overall survival in patients with TP53 mutant tumors was poor compared to wild type (5.5 vs. 20.3 months, p = 0.004). This regimen had limited activity in TNBC. Inconsistent Chk1 inhibition was likely due to the pharmacokinetics of UCN-01. TP53 mutations were associated with a poor prognosis in metastatic TNBC.

PAM50 proliferation score as a predictor of weekly paclitaxel benefit in breast cancer.

To identify a group of patients who might benefit from the addition of weekly paclitaxel to conventional anthracycline-containing chemotherapy as adjuvant therapy of node-positive operable breast cancer. The predictive value of PAM50 subtypes and the 11-gene proliferation score contained within the PAM50 assay were evaluated in 820 patients from the GEICAM/9906 randomized phase III trial comparing adjuvant FEC to FEC followed by weekly paclitaxel (FEC-P). Multivariable Cox regression analyses of the secondary endpoint of overall survival (OS) were performed to determine the significance of the interaction between treatment and the (1) PAM50 subtypes, (2) PAM50 proliferation score, and (3) clinical and pathological variables. Similar OS analyses were performed in 222 patients treated with weekly paclitaxel versus paclitaxel every 3 weeks in the CALGB/9342 and 9840 metastatic clinical trials. In GEICAM/9906, with a median follow up of 8.7 years, OS of the FEC-P arm was significantly superior compared to the FEC arm (unadjusted HR = 0.693, p = 0.013). A benefit from paclitaxel was only observed in the group of patients with a low PAM50 proliferation score (unadjusted HR = 0.23, p < 0.001; and interaction test, p = 0.006). No significant interactions between treatment and the PAM50 subtypes or the various clinical-pathological variables, including Ki-67 and histologic grade, were identified. Finally, similar OS results were obtained in the CALGB data set, although the interaction test did not reach statistical significance (p = 0.109). The PAM50 proliferation score identifies a subset of patients with a low proliferation status that may derive a larger benefit from weekly paclitaxel.

A survey of immunohistochemical biomarkers for basal-like breast cancer against a gene expression profile gold standard.

Gene expression profiling of breast cancer delineates a particularly aggressive subtype referred to as 'basal-like', which comprises ∼15% of all breast cancers, afflicts younger women and is refractory to endocrine and anti-HER2 therapies. Immunohistochemical surrogate definitions for basal-like breast cancer, such as the clinical ER/PR/HER2 triple-negative phenotype and models incorporating positive expression for CK5 (CK5/6) and/or EGFR are heavily cited. However, many additional biomarkers for basal-like breast cancer have been described in the literature. A parallel comparison of 46 proposed immunohistochemical biomarkers of basal-like breast cancer was performed against a gene expression profile gold standard on a tissue microarray containing 42 basal-like and 80 non-basal-like breast cancer cases. Ki67 and PPH3 were the most sensitive biomarkers (both 92%) positively expressed in the basal-like subtype, whereas CK14, IMP3 and NGFR were the most specific (100%). Among biomarkers surveyed, loss of INPP4B (a negative regulator of phosphatidylinositol signaling) was 61% sensitive and 99% specific with the highest odds ratio (OR) at 108, indicating the strongest association with basal-like breast cancer. Expression of nestin, a common marker of neural progenitor cells that is also associated with the triple-negative/basal-like phenotype and poor breast cancer prognosis, possessed the second highest OR at 29 among the 46 biomarkers surveyed, as well as 54% sensitivity and 96% specificity. As a positively expressed biomarker, nestin possesses technical advantages over INPP4B that make it a more ideal biomarker for identification of basal-like breast cancer. The comprehensive immunohistochemical biomarker survey presented in this study is a necessary step for determining an optimized surrogate immunopanel that best defines basal-like breast cancer in a practical and clinically accessible way.

TRIM29 functions as a tumor suppressor in nontumorigenic breast cells and invasive ER+ breast cancer.

Tripartite motif-containing 29 (TRIM29) is a member of the TRIM protein family that has been implicated in hematologic and solid tumor cancers. We found that TRIM29 functions as a tumor suppressor in both the nontumorigenic MCF10A [estrogen receptor (ER)-/TRIM29+] breast cell line and the invasive MCF7 (ER+/TRIM29-) breast cell line. Silencing TRIM29 in MCF10A cells resulted in preneoplastic changes that included loss of polarity in three-dimensional culture, increased proliferation, anchorage-independent growth, and increased migration and invasion. Conversely, the introduction of TRIM29 into MCF7 cells caused reversion to a less aggressive phenotype by antagonizing the growth effect of 17ß-estradiol. The interaction between TRIM29 and ER signaling in MCF7 cells was supported by a reduction in ERE binding in the presence of TRIM29 and suppression of ER-dependent gene expression of TFF1, FOS, and GREB1. By microarray analyses, we showed that younger women (<55 years of age) with early-stage, ER+ breast cancer who were given no adjuvant systemic therapy had a significantly lower risk of relapse when their tumor had high TRIM29 expression (P = 0.02). This effect was not observed in older women (>55 years of age) and thus may be due to menopause and loss of circulating estrogens. Our results suggest that loss of TRIM29 expression in normal breast luminal cells can contribute to malignant transformation and lead to progression of ER+ breast cancer in premenopausal women.

Molecular portraits and the family tree of cancer.

The twenty-first century heralds a new era for the biological sciences and medicine. The tools of our time are allowing us to analyze complex genomes more comprehensively than ever before. A principal technology contributing to this explosion of information is the DNA microarray, which enables us to study genome-wide expression patterns in complex biological systems. Although the potential of microarrays is yet to be fully realized, these tools have shown great promise in deciphering complex diseases such as cancer. The early results are painting a detailed portrait of cancer that illustrates the individuality of each tumor and allows familial relationships to be recognized through the identification of cell types sharing common expression patterns.

Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes.

PURPOSE: To improve on current standards for breast cancer prognosis and prediction of chemotherapy benefit by developing a risk model that incorporates the gene expression-based "intrinsic" subtypes luminal A, luminal B, HER2-enriched, and basal-like. METHODS: A 50-gene subtype predictor was developed using microarray and quantitative reverse transcriptase polymerase chain reaction data from 189 prototype samples. Test sets from 761 patients (no systemic therapy) were evaluated for prognosis, and 133 patients were evaluated for prediction of pathologic complete response (pCR) to a taxane and anthracycline regimen. RESULTS: The intrinsic subtypes as discrete entities showed prognostic significance (P = 2.26E-12) and remained significant in multivariable analyses that incorporated standard parameters (estrogen receptor status, histologic grade, tumor size, and node status). A prognostic model for node-negative breast cancer was built using intrinsic subtype and clinical information. The C-index estimate for the combined model (subtype and tumor size) was a significant improvement on either the clinicopathologic model or subtype model alone. The intrinsic subtype model predicted neoadjuvant chemotherapy efficacy with a negative predictive value for pCR of 97%. CONCLUSION: Diagnosis by intrinsic subtype adds significant prognostic and predictive information to standard parameters for patients with breast cancer. The prognostic properties of the continuous risk score will be of value for the management of node-negative breast cancers. The subtypes and risk score can also be used to assess the likelihood of efficacy from neoadjuvant chemotherapy.

Agreement in risk prediction between the 21-gene recurrence score assay (Oncotype DX®) and the PAM50 breast cancer intrinsic Classifier™ in early-stage estrogen receptor-positive breast cancer.

PURPOSE: To compare risk assignment by PAM50 Breast Cancer Intrinsic Classifier™ and Oncotype DX_Recurrence Score (RS) in the same population. METHODS: RNA was extracted from 151 estrogen receptor (ER)+ stage I-II breast cancers and gene expression profiled using PAM50 "intrinsic" subtyping test. RESULTS: One hundred eight cases had complete molecular information; 103 (95%) were classified as luminal A (n = 76) or luminal B (n = 27). Ninety-two percent (n = 98) had a low (n = 59) or intermediate (n = 39) RS. Among luminal A cancers, 70% had low (n = 53) and the remainder (n = 23) had an intermediate RS. Among luminal B cancers, nine were high (33%) and 13 were intermediate (48%) by the RS. Almost all cancers with a high RS were classified as luminal B (90%, n = 9). One high RS cancer was identified as basal-like and had low ER/ESR1 and low human epidermal growth factor receptor 2 (HER2) expression by quantitative polymerase chain reaction in both assays. The majority of low RS cases were luminal A (83%, n = 53). Importantly, half of the intermediate RS cancers were re-categorized as low risk luminal A subtype by PAM50. CONCLUSION: There is good agreement between the two assays for high (i.e., luminal B or RS > 31) and low (i.e., luminal B or RS < 18) prognostic risk assignment but PAM50 assigns more patients to the low risk category. About half of the intermediate RS group was reclassified as luminal A by PAM50.

Multiparametric quantitative phase imaging for real-time, single cell, drug screening in breast cancer.

Quantitative phase imaging (QPI) measures the growth rate of individual cells by quantifying changes in mass versus time. Here, we use the breast cancer cell lines MCF-7, BT-474, and MDA-MB-231 to validate QPI as a multiparametric approach for determining response to single-agent therapies. Our method allows for rapid determination of drug sensitivity, cytotoxicity, heterogeneity, and time of response for up to 100,000 individual cells or small clusters in a single experiment. We find that QPI EC50 values are concordant with CellTiter-Glo (CTG), a gold standard metabolic endpoint assay. In addition, we apply multiparametric QPI to characterize cytostatic/cytotoxic and rapid/slow responses and track the emergence of resistant subpopulations. Thus, QPI reveals dynamic changes in response heterogeneity in addition to average population responses, a key advantage over endpoint viability or metabolic assays. Overall, multiparametric QPI reveals a rich picture of cell growth by capturing the dynamics of single-cell responses to candidate therapies.

Potential Utility of Pre-Emptive Germline Pharmacogenetics in Breast Cancer.

Patients with breast cancer often receive many drugs to manage the cancer, side effects associated with cancer treatment, and co-morbidities (i.e., polypharmacy). Drug-drug and drug-gene interactions contribute to the risk of adverse events (AEs), which could lead to non-adherence and reduced efficacy. Here we investigated several well-characterized inherited (germline) pharmacogenetic (PGx) targets in 225 patients with breast cancer. All relevant clinical, pharmaceutical, and PGx diplotype data were aggregated into a single unifying informatics platform to enable an exploratory analysis of the cohort and to evaluate pharmacy ordering patterns. Of the drugs recorded, there were 38 for which high levels of evidence for clinical actionability with PGx was available from the US FDA and/or the Clinical Pharmacogenetics Implementation Consortium (CPIC). These data were associated with 10 pharmacogenes: DPYD, CYP2C9, CYP2C19, CYP2D6, CYP3A5, CYP4F2, G6PD, MT-RNR1, SLCO1B1, and VKORC1. All patients were taking at least one of the 38 drugs and had inherited at least one actionable PGx variant that would have informed prescribing decisions if this information had been available pre-emptively. The non-cancer drugs with PGx implications that were common (prescribed to at least one-third of patients) included anti-depressants, anti-infectives, non-steroidal anti-inflammatory drugs, opioids, and proton pump inhibitors. Based on these results, we conclude that pre-emptive PGx testing may benefit patients with breast cancer by informing drug and dose selection to maximize efficacy and minimize AEs.

Family Study Designs Informed by Tumor Heterogeneity and Multi-Cancer Pleiotropies: The Power of the Utah Population Database.

BACKGROUND: Previously, family-based designs and high-risk pedigrees have illustrated value for the discovery of high- and intermediate-risk germline breast cancer susceptibility genes. However, genetic heterogeneity is a major obstacle hindering progress. New strategies and analytic approaches will be necessary to make further advances. One opportunity with the potential to address heterogeneity via improved characterization of disease is the growing availability of multisource databases. Specific to advances involving family-based designs are resources that include family structure, such as the Utah Population Database (UPDB). To illustrate the broad utility and potential power of multisource databases, we describe two different novel family-based approaches to reduce heterogeneity in the UPDB. METHODS: Our first approach focuses on using pedigree-informed breast tumor phenotypes in gene mapping. Our second approach focuses on the identification of families with similar pleiotropies. We use a novel network-inspired clustering technique to explore multi-cancer signatures for high-risk breast cancer families. RESULTS: Our first approach identifies a genome-wide significant breast cancer locus at 2q13 [P = 1.6 × 10-8, logarithm of the odds (LOD) equivalent 6.64]. In the region, IL1A and IL1B are of particular interest, key cytokine genes involved in inflammation. Our second approach identifies five multi-cancer risk patterns. These clusters include expected coaggregations (such as breast cancer with prostate cancer, ovarian cancer, and melanoma), and also identify novel patterns, including coaggregation with uterine, thyroid, and bladder cancers. CONCLUSIONS: Our results suggest pedigree-informed tumor phenotypes can map genes for breast cancer, and that various different cancer pleiotropies exist for high-risk breast cancer pedigrees. IMPACT: Both methods illustrate the potential for decreasing etiologic heterogeneity that large, population-based multisource databases can provide.See all articles in this CEBP Focus section, "Modernizing Population Science."