Serial analysis of circulating tumor cells in metastatic breast cancer receiving first-line chemotherapy

Background: We examined the prognostic significance of circulating tumor cell (CTC) dynamics during treatment in metastatic breast cancer (MBC) patients receiving first-line chemotherapy. Methods: Serial CTC data from 469 patients (2,202 samples) were used to build a novel latent mixture model to identify groups with similar CTC trajectory (tCTC) patterns during the course of treatment. Cox regression was used to estimate hazard ratios for progression-free survival (PFS) and overall survival (OS) in groups based on baseline CTCs (bCTC), combined CTC status at baseline to the end of cycle 1 (cCTC), and tCTC. Akaike Information Criterion (AIC) was used to select the model that best predicted PFS and OS. Results: Latent mixture modeling revealed 4 distinct tCTC patterns: undetectable CTCs (tCTCneg, 56.9% ), low (tCTClo, 23.7%), intermediate (tCTCmid, 14.5%), or high (tCTChi, 4.9%). Patients with tCTClo, tCTCmid and tCTChi patterns had statistically significant inferior PFS and OS compared to those with tCTCneg (P<.001). AIC indicated that the tCTC model best predicted PFS and OS when compared to bCTC and cCTC models. Validation studies in an independent cohort of 1,856 MBC patients confirmed these findings. Further validation using only a single pretreatment CTC measurement confirmed prognostic performance of the tCTC model. Conclusions: We identified four novel prognostic groups in MBC based on similarities in CTC trajectory patterns during chemotherapy. Prognostic groups included patients with very poor outcome (tCTCmid+tCTChi, 19.4%) who could benefit from more effective treatment. Our novel prognostic classification approach may be utilized for fine-tuning of CTC-based risk-stratification strategies to guide future prospective clinical trials in MBC

Serial Analysis of Circulating Tumor Cells in Metastatic Breast Cancer Receiving First-Line Chemotherapy

BACKGROUND: We examined the prognostic significance of circulating tumor cell (CTC) dynamics during treatment in metastatic breast cancer (MBC) patients receiving first-line chemotherapy. METHODS: Serial CTC data from 469 patients (2202 samples) were used to build a novel latent mixture model to identify groups with similar CTC trajectory (tCTC) patterns during the course of treatment. Cox regression was used to estimate hazard ratios for progression-free survival (PFS) and overall survival (OS) in groups based on baseline CTCs, combined CTC status at baseline to the end of cycle 1, and tCTC. Akaike information criterion was used to select the model that best predicted PFS and OS. RESULTS: Latent mixture modeling revealed 4 distinct tCTC patterns: undetectable CTCs (56.9% ), low (23.7%), intermediate (14.5%), or high (4.9%). Patients with low, intermediate, and high tCTC patterns had statistically significant inferior PFS and OS compared with those with undetectable CTCs (P < .001). Akaike Information Criterion indicated that the tCTC model best predicted PFS and OS compared with baseline CTCs and combined CTC status at baseline to the end of cycle 1 models. Validation studies in an independent cohort of 1856 MBC patients confirmed these findings. Further validation using only a single pretreatment CTC measurement confirmed prognostic performance of the tCTC model. CONCLUSIONS: We identified 4 novel prognostic groups in MBC based on similarities in tCTC patterns during chemotherapy. Prognostic groups included patients with very poor outcome (intermediate + high CTCs, 19.4%) who could benefit from more effective treatment. Our novel prognostic classification approach may be used for fine-tuning of CTC-based risk stratification strategies to guide future prospective clinical trials in MBC

Polymorphic variants in TSC1 and TSC2 and their association with breast cancer phenotypes

TSC1 acts coordinately with TSC2 in a complex to inhibit mTOR, an emerging therapeutic target and known promoter of cell growth and cell cycle progression. Perturbation of the mTOR pathway, through abnormal expression or function of pathway genes, could lead to tumorigenesis. TSC1 and TSC2 expression is reduced in invasive breast cancer as compared with normal mammary epithelium. Because single nucleotide polymorphisms (SNPs) in regulatory genes have been implicated in risk and age at diagnosis of breast cancers, systematic SNP association studies were performed on TSC1 and TSC2 SNPs for their associations with clinical features of breast cancer. TSC1 and TSC2 haplotypes were constructed from genotyping of multiple loci in both genes in healthy volunteers. SNPs were selected for further study using a bioinformatics approach based on SNP associations with drug response in NCI-60 cell lines and evidence of selection bias based on haplotype frequencies. Genotyping for five TSC1 and one TSC2 loci were performed on genomic DNA from 1,137 women with breast cancer. This study found that for TSC1 rs7874234, TT variant carriers had a 9-year later age at diagnosis of estrogen receptor positive (ER+), but not ER-, ductal carcinomas (P = 0.0049). No other SNP locus showed an association with age at diagnosis, nor any other breast cancer phenotype. TSC1 rs7874234 is hypothesized to be functional in ER+ breast cancer because the T allele, but not the C allele, may create an estrogen receptor element (ERE) site, resulting in increased TSC1 transcription and subsequent inhibition of mTOR. © 2010 Springer Science+Business Media, LLC

Pembrolizumab monotherapy for previously untreated, PD-L1-positive, metastatic triple-negative breast cancer: Cohort B of the phase II KEYNOTE-086 study

Background Standard first-line treatment of metastatic triple-negative breast cancer (mTNBC) is chemotherapy. However, outcomes are poor, and new treatment options are needed. In cohort B of the phase II KEYNOTE-086 study, we evaluated pembrolizumab as first-line therapy for patients with PD-L1-positive mTNBC. Patients and methods Eligible patients had centrally confirmed mTNBC, no prior systemic anticancer therapy for metastatic disease, measurable disease at baseline per RECIST v1.1 by central review, no radiographic evidence of central nervous system metastases, and a tumor PD-L1 combined positive score ≥1. Patients received pembrolizumab 200 mg intravenously every 3 weeks for up to 2 years. The primary end point was safety. Secondary end points included objective response rate, disease control rate (percentage of patients with complete or partial response or stable disease for ≥24 weeks), duration of response, progression-free survival and overall survival. Results All 84 patients enrolled were women, and 73 (86.9%) received prior (neo)adjuvant therapy. Fifty-three (63.1%) patients had treatment-related adverse events (AEs), including 8 patients (9.5%) with grade 3 severity; no patients experienced grade 4 AEs or died because of treatment-related AEs. Four patients had a complete response and 14 had a partial response, for an objective response rate of 21.4% (95% CI 13.9-31.4). Of the 13 patients with stable disease, 2 had stable disease lasting ≥24 weeks, for a disease control rate of 23.8% (95% CI 15.9-34.0). At data cut-off, 8 of 18 (44.4%) responses were ongoing, and median duration of response was 10.4 months (range 4.2 to 19.2+). Median progression-free survival was 2.1 months (95% CI 2.0-2.2), and median overall survival was 18.0 months (95% CI 12.9-23.0). Conclusions Pembrolizumab monotherapy had a manageable safety profile and showed durable antitumor activity as first-line therapy for patients with PD-L1-positive mTNBC. Clinical trial registration ClinicalTrials.gov, NCT02447003

Metabotropic glutamate receptor 1 expression and its polymorphic variants associate with breast cancer phenotypes.

Several epidemiological studies have suggested a link between melanoma and breast cancer. Metabotropic glutamate receptor 1 (GRM1), which is involved in many cellular processes including proliferation and differentiation, has been implicated in melanomagenesis, with ectopic expression of GRM1 causing malignant transformation of melanocytes. This study was undertaken to evaluate GRM1 expression and polymorphic variants in GRM1 for associations with breast cancer phenotypes. Three single nucleotide polymorphisms (SNPs) in GRM1 were evaluated for associations with breast cancer clinicopathologic variables. GRM1 expression was evaluated in human normal and cancerous breast tissue and for in vitro response to hormonal manipulation. Genotyping was performed on genomic DNA from over 1,000 breast cancer patients. Rs6923492 and rs362962 genotypes associated with age at diagnosis that was highly dependent upon the breast cancer molecular phenotype. The rs362962 TT genotype also associated with risk of estrogen receptor or progesterone receptor positive breast cancer. In vitro analysis showed increased GRM1 expression in breast cancer cells treated with estrogen or the combination of estrogen and progesterone, but reduced GRM1 expression with tamoxifen treatment. Evaluation of GRM1 expression in human breast tumor specimens demonstrated significant correlations between GRM1 staining with tissue type and molecular features. Furthermore, analysis of gene expression data from primary breast tumors showed that high GRM1 expression correlated with a shorter distant metastasis-free survival as compared to low GRM1 expression in tamoxifen-treated patients. Additionally, induced knockdown of GRM1 in an estrogen receptor positive breast cancer cell line correlated with reduced cell proliferation. Taken together, these findings suggest a functional role for GRM1 in breast cancer

Serial Analysis of Circulating Tumor Cells in Metastatic Breast Cancer Receiving First-Line Chemotherapy

32siBackground: We examined the prognostic significance of circulating tumor cell (CTC) dynamics during treatment in metastatic breast cancer (MBC) patients receiving first-line chemotherapy. Methods: Serial CTC data from 469 patients (2202 samples) were used to build a novel latent mixture model to identify groups with similar CTC trajectory (tCTC) patterns during the course of treatment. Cox regression was used to estimate hazard ratios for progression-free survival (PFS) and overall survival (OS) in groups based on baseline CTCs, combined CTC status at baseline to the end of cycle 1, and tCTC. Akaike information criterion was used to select the model that best predicted PFS and OS. Results: Latent mixture modeling revealed 4 distinct tCTC patterns: undetectable CTCs (56.9%), low (23.7%), intermediate (14.5%), or high (4.9%). Patients with low, intermediate, and high tCTC patterns had statistically significant inferior PFS and OS compared with those with undetectable CTCs (P <. 001). Akaike Information Criterion indicated that the tCTC model best predicted PFS and OS compared with baseline CTCs and combined CTC status at baseline to the end of cycle 1 models. Validation studies in an independent cohort of 1856 MBC patients confirmed these findings. Further validation using only a single pretreatment CTC measurement confirmed prognostic performance of the tCTC model. Conclusions: We identified 4 novel prognostic groups in MBC based on similarities in tCTC patterns during chemotherapy. Prognostic groups included patients with very poor outcome (intermediate + high CTCs, 19.4%) who could benefit from more effective treatment. Our novel prognostic classification approach may be used for fine-tuning of CTC-based risk stratification strategies to guide future prospective clinical trials in MBC.reservedmixedMagbanua M.J.M.; Hendrix L.H.; Hyslop T.; Barry W.T.; Winer E.P.; Hudis C.; Toppmeyer D.; Carey L.A.; Partridge A.H.; Pierga J.-Y.; Fehm T.; Vidal-Martinez J.; Mavroudis D.; Garcia-Saenz J.A.; Stebbing J.; Gazzaniga P.; Manso L.; Zamarchi R.; Antelo M.L.; Mattos-Arruda L.D.; Generali D.; Caldas C.; Munzone E.; Dirix L.; Delson A.L.; Burstein H.J.; Qadir M.; Ma C.; Scott J.H.; Bidard F.-C.; Park J.W.; Rugo H.S.Magbanua, M. J. M.; Hendrix, L. H.; Hyslop, T.; Barry, W. T.; Winer, E. P.; Hudis, C.; Toppmeyer, D.; Carey, L. A.; Partridge, A. H.; Pierga, J. -Y.; Fehm, T.; Vidal-Martinez, J.; Mavroudis, D.; Garcia-Saenz, J. A.; Stebbing, J.; Gazzaniga, P.; Manso, L.; Zamarchi, R.; Antelo, M. L.; Mattos-Arruda, L. D.; Generali, D.; Caldas, C.; Munzone, E.; Dirix, L.; Delson, A. L.; Burstein, H. J.; Qadir, M.; Ma, C.; Scott, J. H.; Bidard, F. -C.; Park, J. W.; Rugo, H. S

Cumulative incidence of breast cancer as a function of age of diagnosis for rs362962 genotypes.

<p>Fraction of individuals diagnosed with breast cancer as a function of age, in a cohort of Caucasian women diagnosed with (A) ER+/PR+ ductal breast cancer and (B) ER−/PR- ductal breast cancer as a function of rs362962 genotype. Data were analyzed as CC (grey) versus T allele (black).</p

Immunohistochemical staining for GRM1 on tissue microarrays of human breast tissue.

<p>Representative examples of the IHC scoring system using breast cancer tissues are shown. Melanoma (left panel) was utilized as a positive control and for antibody optimization. Scoring was based on intensity of membrane staining: 0; 1+; 2+; 3+.</p