Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction.

Breast cancer (BC) is a complex disease comprising multiple distinct subtypes with different genetic features and pathological characteristics. Although a large number of antineoplastic compounds have been approved for clinical use, patient-to-patient variability in drug response is frequently observed, highlighting the need for efficient treatment prediction for individualized therapy. Several patient-derived models have been established lately for the prediction of drug response. However, each of these models has its limitations that impede their clinical application. Here, we report that the whole-tumor cell culture (WTC) ex vivo model could be stably established from all breast tumors with a high success rate (98 out of 116), and it could reassemble the parental tumors with the endogenous microenvironment. We observed strong clinical associations and predictive values from the investigation of a broad range of BC therapies with WTCs derived from a patient cohort. The accuracy was further supported by the correlation between WTC-based test results and patients' clinical responses in a separate validation study, where the neoadjuvant treatment regimens of 15 BC patients were mimicked. Collectively, the WTC model allows us to accomplish personalized drug testing within 10 d, even for small-sized tumors, highlighting its potential for individualized BC therapy. Furthermore, coupled with genomic and transcriptomic analyses, WTC-based testing can also help to stratify specific patient groups for assignment into appropriate clinical trials, as well as validate potential biomarkers during drug development.

A minority-group of renal cell cancer patients with high infiltration of CD20+B-cells is associated with poor prognosis.

BACKGROUND: The role of B-lymphocytes in solid tumours is unclear. Tumour biology studies have implied both anti- and pro-tumoural effects and prognostic studies have mainly linked B-cells to increased survival. This study aimed to analyse the clinical relevance of B-lymphocytes in renal cell cancer (RCC), where information on the prognostic impact is lacking. METHODS: Following immunohistochemistry (IHC) stainings with a CD20 antibody, density of CD20+ B-cells was quantified in an RCC discovery- and validation cohort. Associations of B-cell infiltration, determined by CD20 expression or a B-cell gene-signature, and survival was also analysed in 14 publicly available gene expression datasets of cancer, including the kidney clear cell carcinoma (KIRC) dataset. RESULTS: IHC analyses of the discovery cohort identified a previously unrecognised subgroup of RCC patients with high infiltration of CD20+ B-cells. The B-cell-high subgroup displayed significantly shorter survival according to uni- and multi-variable analyses. The association between poor prognosis and high density of CD20+ B-cells was confirmed in the validation cohort. Analyses of the KIRC gene expression dataset using the B-cell signature confirmed findings from IHC analyses. Analyses of other gene expression datasets, representing 13 different tumour types, indicated that the poor survival-association of B-cells occurred selectively in RCC. CONCLUSION: This exploratory study identifies a previously unrecognised poor-prognosis subset of RCC with high density of CD20-defined B-cells.

Immune gene expression and response to chemotherapy in advanced breast cancer.

BACKGROUND: Transcriptomic profiles have shown promise as predictors of response to neoadjuvant chemotherapy in breast cancer (BC). This study aimed to explore their predictive value in the advanced BC (ABC) setting. METHODS: In a Phase 3 trial of first-line chemotherapy in ABC, a fine needle aspiration biopsy (FNAB) was obtained at baseline. Intrinsic molecular subtypes and gene modules related to immune response, proliferation, oestrogen receptor (ER) signalling and recurring genetic alterations were analysed for association with objective response to chemotherapy. Gene-set enrichment analysis (GSEA) of responders vs non-responders was performed independently. Lymphocytes were enumerated in FNAB smears and the absolute abundance of immune cell types was calculated using the Microenvironment Cell Populations counter method. RESULTS: Gene expression data were available for 109 patients. Objective response to chemotherapy was statistically significantly associated with an immune module score (odds ratio (OR)=1.62; 95% confidence interval (CI), 1.03-2.64; P=0.04). Subgroup analysis showed that this association was restricted to patients with ER-positive or luminal tumours (OR=3.54; 95%, 1.43-10.86; P=0.012 and P for interaction=0.04). Gene-set enrichment analysis confirmed that in these subgroups, immune-related gene sets were enriched in responders. CONCLUSIONS: Immune-related transcriptional signatures may predict response to chemotherapy in ER-positive and luminal ABC.

Intra-tumor heterogeneity in breast cancer has limited impact on transcriptomic-based molecular profiling.

BACKGROUND: Transcriptomic profiling of breast tumors provides opportunity for subtyping and molecular-based patient stratification. In diagnostic applications the specimen profiled should be representative of the expression profile of the whole tumor and ideally capture properties of the most aggressive part of the tumor. However, breast cancers commonly exhibit intra-tumor heterogeneity at molecular, genomic and in phenotypic level, which can arise during tumor evolution. Currently it is not established to what extent a random sampling approach may influence molecular breast cancer diagnostics. METHODS: In this study we applied RNA-sequencing to quantify gene expression in 43 pieces (2-5 pieces per tumor) from 12 breast tumors (Cohort 1). We determined molecular subtype and transcriptomic grade for all tumor pieces and analysed to what extent pieces originating from the same tumors are concordant or discordant with each other. Additionally, we validated our finding in an independent cohort consisting of 19 pieces (2-6 pieces per tumor) from 6 breast tumors (Cohort 2) profiled using microarray technique. Exome sequencing was also performed on this cohort, to investigate the extent of intra-tumor genomic heterogeneity versus the intra-tumor molecular subtype classifications. RESULTS: Molecular subtyping was consistent in 11 out of 12 tumors and transcriptomic grade assignments were consistent in 11 out of 12 tumors as well. Molecular subtype predictions revealed consistent subtypes in four out of six patients in this cohort 2. Interestingly, we observed extensive intra-tumor genomic heterogeneity in these tumor pieces but not in their molecular subtype classifications. CONCLUSIONS: Our results suggest that macroscopic intra-tumoral transcriptomic heterogeneity is limited and unlikely to have an impact on molecular diagnostics for most patients.

PD-1 protein and gene expression as prognostic factors in early breast cancer.

BACKGROUND: There is a paucity of data on the prognostic value of programmed cell death protein 1 (PD-1) protein and gene expression in early breast cancer (BC) and the present study's aim was to comprehensively investigate it. METHODS: The study consisted of three parts: a correlative analysis of PD-1 protein and gene expression from an original patient cohort of 564 patients with early BC; a systematic review and trial-level meta-analysis on the association between PD-1 protein expression and disease-free survival/overall survival (OS) in early BC; and a pooled gene expression analysis from publicly available transcriptomic datasets regarding PDCD1 expression. RESULTS: In the study cohort, PD-1 protein, but not gene expression, was associated with improved OS (HRadj=0.73, 95% CI 0.55 to 0.97, p=0.027 and HRadj=0.88, 95% CI 0.68 to 1.13, p=0.312, respectively). In the trial-level meta-analysis, PD-1 protein expression was not found to be statistically significantly associated with outcomes in the overall population. Finally, in the pooled gene expression analysis, higher PDCD1 expression was associated with better OS in multivariable analysis in the entire population (HRadj=0.89, 95% CI 0.80 to 0.99, p=0.025) and in basal-like tumours. CONCLUSIONS: PD-1 protein and gene expression seem to be promising prognostic factors in early BC. Standardisation of detection and assessment methods is of utmost importance.

Prognostic Implications of PD-L1 Expression in Breast Cancer: Systematic Review and Meta-analysis of Immunohistochemistry and Pooled Analysis of Transcriptomic Data.

PURPOSE: Conflicting data have been reported on the prognostic value of PD-L1 protein and gene expression in breast cancer.Experimental Design: Medline, Embase, Cochrane Library, and Web of Science Core Collection were searched, and data were extracted independently by two researchers. Outcomes included pooled PD-L1 protein positivity in tumor cells, immune cells, or both, per subtype and per antibody used, and its prognostic value for disease-free and overall survival. A pooled gene expression analysis of 39 publicly available transcriptomic datasets was also performed. RESULTS: Of the initial 4,184 entries, 38 retrospective studies fulfilled the predefined inclusion criteria. The overall pooled PD-L1 protein positivity rate was 24% (95% CI, 15%-33%) in tumor cells and 33% (95% CI, 14%- 56%) in immune cells. PD-L1 protein expression in tumor cells was prognostic for shorter overall survival (HR, 1.63; 95% CI, 1.07-2.46; P = 0.02); there was significant heterogeneity (I2 = 80%, P heterogeneity < 0.001). In addition, higher PD-L1 gene expression predicted better survival in multivariate analysis in the entire population (HR, 0.82; 95% CI, 0.74-0.90; P < 0.001 for OS) and in basal-like tumors (HR, 0.64; 95% CI, 0.52-0.80; P < 0.001 for OS; P interaction 0.005). CONCLUSIONS: The largest to our knowledge meta-analysis on the subject informs on PD-L1 protein positivity rates and its prognostic value in breast cancer. Standardization is needed prior to routine implementation. PD-L1 gene expression is a promising prognostic factor, especially in basal-like breast cancer. Discrepant prognostic information might be related to PD-L1 gene expression in the stroma.

A Novel ACKR2-Dependent Role of Fibroblast-Derived CXCL14 in Epithelial-to-Mesenchymal Transition and Metastasis of Breast Cancer.

PURPOSE: Fibroblasts expressing the orphan chemokine CXCL14 have been previously shown to associate with poor breast cancer prognosis and promote cancer growth. This study explores the mechanism underlying the poor survival associations of stromal CXCL14. EXPERIMENTAL DESIGN: Tumor cell epithelial-to-mesenchymal transition (EMT), invasion, and metastasis were studied in in vitro and in vivo models together with fibroblasts overexpressing CXCL14. An approach for CXCL14 receptor identification included loss-of-function studies followed by molecular and functional endpoints. The clinical relevance was further explored in publicly available gene expression datasets. RESULTS: CXCL14 fibroblasts stimulated breast cancer EMT, migration, and invasion in breast cancer cells and in a xenograft model. Furthermore, tumor cells primed by CXCL14 fibroblasts displayed enhanced lung colonization after tail-vein injection. By loss-of function experiments, the atypical G-protein-coupled receptor ACKR2 was identified to mediate CXCL14-stimulated responses. Downregulation of ACKR2, or CXCL14-induced NOS1, attenuated the pro-EMT and migratory capacity. CXCL14/ACKR2 expression correlated with EMT and survival in gene expression datasets. CONCLUSIONS: Collectively, the findings imply an autocrine fibroblast CXCL14/ACKR2 pathway as a clinically relevant stimulator of EMT, tumor cell invasion, and metastasis. The study also identifies ACKR2 as a novel mediator for CXCL14 function and thereby defines a pathway with drug target potential.See related commentary by Zhang et al., p. 3476.

Effect of CYP2C19 and CYP2D6 genotype on tamoxifen treatment outcome indicates endogenous and exogenous interplay.

AIM: We investigated the interaction of CYP2C19 and CYP2D6 genotype on clinical outcome in tamoxifen-treated breast cancer patients. MATERIALS & METHODS: A cohort of 306 patients on tamoxifen treatment for a minimum of 1 year were employed to analyze the effect of genotype-predicted phenotype on relapse-free survival. RESULTS & CONCLUSION: We show that the group with worst outcome and highest risk of relapse is that of 2C19↑-2D6↓ (hazard ratio: 2.94), when adjusting for age, Nottingham prognostic index and adjuvant chemotherapy. Furthermore, the effect of 2C19↑-2D6↓genotype-predicted phenotype is greatly enhanced in premenopausal patients (hazard ratio: 21.08). We hypothesize that poor bioactivation of tamoxifen in patients with low CYP2D6 activity and high CYP2C19 metabolism represents a tamoxifen-treated patient group that has the worst clinical outcome.

Dynamic evaluation of the immune infiltrate and immune function genes as predictive markers for neoadjuvant chemotherapy in hormone receptor positive, HER2 negative breast cancer.

Gene expression (GE) signatures and Tumor Infiltrating Lymphocytes (TIL) enumeration are predictive for response to neoadjuvant chemotherapy in HR- and in HER2+ breast cancer, but data are conflicting in HR+/HER2- disease. This study aimed to explore their predictive value in this subset, measured both at baseline and after short exposure to chemotherapy. Specifically, the PROMIX phase 2 trial enrolled patients with locally advanced HER2- BC to receive six cycles of epirubicin and docetaxel, plus bevacizumab during cycles 3-6. Patients underwent tumor biopsies at baseline and after cycle 2 for GE profiling and enumeration of TIL, FOXP3+ T-cells and CD163+ macrophages. An immune related gene module and the quantification of the immune infiltrate were analyzed for association with pathologic complete response (pCR), decrease in tumor size and disease-free survival (DFS). Of the 150 patients enrolled in PROMIX, 113 were HR+/HER2-. Baseline GE and immune cell enumeration data were available from 71 patients, while data after 2 cycles of chemotherapy were available from 41. At baseline, only GE was statistically significantly associated with higher pCR rates (OR 2.29, 95% CI 1.05 - 5.38, p = 0.037) and decrease in tumor size (r = 0.25, p = 0.047). In contrast, longitudinal data indicate that both GE (r = 0.54, p<0.001) and TIL abundance (p = 0.009) are stronger predictors for the reduction of tumor size, while low FOXP3+ was statistically significantly associated with an improved DFS (p = 0.027). In conclusion, GE analysis, TIL and FOXP3+ enumeration after short-term exposure to chemotherapy carry important predictive information in HR+/HER2- breast cancer at the neoadjuvant setting.

Spatially and functionally distinct subclasses of breast cancer-associated fibroblasts revealed by single cell RNA sequencing.

Cancer-associated fibroblasts (CAFs) are a major constituent of the tumor microenvironment, although their origin and roles in shaping disease initiation, progression and treatment response remain unclear due to significant heterogeneity. Here, following a negative selection strategy combined with single-cell RNA sequencing of 768 transcriptomes of mesenchymal cells from a genetically engineered mouse model of breast cancer, we define three distinct subpopulations of CAFs. Validation at the transcriptional and protein level in several experimental models of cancer and human tumors reveal spatial separation of the CAF subclasses attributable to different origins, including the peri-vascular niche, the mammary fat pad and the transformed epithelium. Gene profiles for each CAF subtype correlate to distinctive functional programs and hold independent prognostic capability in clinical cohorts by association to metastatic disease. In conclusion, the improved resolution of the widely defined CAF population opens the possibility for biomarker-driven development of drugs for precision targeting of CAFs.

Evolutionary history of metastatic breast cancer reveals minimal seeding from axillary lymph nodes.

Metastatic breast cancers are still incurable. Characterizing the evolutionary landscape of these cancers, including the role of metastatic axillary lymph nodes (ALNs) in seeding distant organ metastasis, can provide a rational basis for effective treatments. Here, we have described the genomic analyses of the primary tumors and metastatic lesions from 99 samples obtained from 20 patients with breast cancer. Our evolutionary analyses revealed diverse spreading and seeding patterns that govern tumor progression. Although linear evolution to successive metastatic sites was common, parallel evolution from the primary tumor to multiple distant sites was also evident. Metastatic spreading was frequently coupled with polyclonal seeding, in which multiple metastatic subclones originated from the primary tumor and/or other distant metastases. Synchronous ALN metastasis, a well-established prognosticator of breast cancer, was not involved in seeding the distant metastasis, suggesting a hematogenous route for cancer dissemination. Clonal evolution coincided frequently with emerging driver alterations and evolving mutational processes, notably an increase in apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like-associated (APOBEC-associated) mutagenesis. Our data provide genomic evidence for a role of ALN metastasis in seeding distant organ metastasis and elucidate the evolving mutational landscape during cancer progression.

Estrogen Receptor ß as a Therapeutic Target in Breast Cancer Stem Cells.

Background: Breast cancer cells with tumor-initiating capabilities (BSCs) are considered to maintain tumor growth and govern metastasis. Hence, targeting BSCs will be crucial to achieve successful treatment of breast cancer. Methods: We characterized mammospheres derived from more than 40 cancer patients and two breast cancer cell lines for the expression of estrogen receptors (ERs) and stem cell markers. Mammosphere formation and proliferation assays were performed on cells from 19 cancer patients and five healthy individuals after incubation with ER-subtype selective ligands. Transcriptional analysis was performed to identify pathways activated in ERß-stimulated mammospheres and verified using in vitro experiments. Xenograft models (n = 4 or 5 per group) were used to study the role of ERs during tumorigenesis. Results: We identified an absence of ERα but upregulation of ERß in BSCs associated with phenotypic stem cell markers and responsible for the proliferative role of estrogens. Knockdown of ERß caused a reduction of mammosphere formation in cell lines and in patient-derived cancer cells (40.7%, 26.8%, and 39.1%, respectively). Gene set enrichment analysis identified glycolysis-related pathways (false discovery rate < 0.001) upregulated in ERß-activated mammospheres. We observed that tamoxifen or fulvestrant alone was insufficient to block proliferation of patient-derived BSCs while this could be accomplished by a selective inhibitor of ERß (PHTPP; 53.7% in luminal and 45.5% in triple-negative breast cancers). Furthermore, PHTPP reduced tumor initiation in two patient-derived xenografts (75.9% and 59.1% reduction in tumor volume, respectively) and potentiated tamoxifen-mediated inhibition of tumor growth in MCF7 xenografts. Conclusion: We identify ERß as a mediator of estrogen action in BSCs and a novel target for endocrine therapy.

An HIF-1α/VEGF-A Axis in Cytotoxic T Cells Regulates Tumor Progression.

Cytotoxic T cells infiltrating tumors are thought to utilize HIF transcription factors during adaptation to the hypoxic tumor microenvironment. Deletion analyses of the two key HIF isoforms found that HIF-1α, but not HIF-2α, was essential for the effector state in CD8+ T cells. Furthermore, loss of HIF-1α in CD8+ T cells reduced tumor infiltration and tumor cell killing, and altered tumor vascularization. Deletion of VEGF-A, an HIF target gene, in CD8+ T cells accelerated tumorigenesis while also altering vascularization. Analyses of human breast cancer showed inverse correlations between VEGF-A expression and CD8+ T cell infiltration, and a link between T cell infiltration and vascularization. These data demonstrate that the HIF-1α/VEGF-A axis is an essential aspect of tumor immunity.

Gene expression profiling of sequential metastatic biopsies for biomarker discovery in breast cancer.

The feasibility of longitudinal metastatic biopsies for gene expression profiling in breast cancer is unexplored. Dynamic changes in gene expression can potentially predict efficacy of targeted cancer drugs. Patients enrolled in a phase III trial of metastatic breast cancer with docetaxel monotherapy versus combination of docetaxel + sunitinib were offered to participate in a translational substudy comprising longitudinal fine needle aspiration biopsies and Positron Emission Tomography imaging before (T1) and two weeks after start of treatment (T2). Aspirated tumor material was used for microarray analysis, and treatment-induced changes (T2 versus T1) in gene expression and standardized uptake values (SUV) were investigated and correlated to clinical outcome measures. Gene expression profiling yielded high-quality data at both time points in 14/18 patients. Unsupervised clustering revealed specific patterns of changes caused by monotherapy vs. combination therapy (p = 0.021, Fisher's exact test). A therapy-induced reduction of known proliferation and hypoxia metagene scores was prominent in the combination arm. Changes in a previously reported hypoxia metagene score were strongly correlated to the objective responses seen by conventional radiology assessments after 6 weeks in the combination arm, Spearman's ρ = 1 (p = 0.017) but not in monotherapy, ρ = -0.029 (p = 1). Similarly, the Predictor Analysis of Microarrays 50 (PAM50) proliferation metagene correlated to tumor changes merely in the combination arm at 6 and 12 weeks (ρ = 0.900, p = 0.083 and ρ = 1, p = 0.017 respectively). Reductions in mean SUV were a reliable early predictor of objective response in monotherapy, ρ = 0.833 (p = 0.008), but not in the combination arm ρ = -0.029 (p = 1). Gene expression profiling of longitudinal metastatic aspiration biopsies was feasible, demonstrated biological validity and provided predictive information.

mTOR inhibitors counteract tamoxifen-induced activation of breast cancer stem cells.

Breast cancer cells with stem cell characteristics (CSC) are a distinct cell population with phenotypic similarities to mammary stem cells. CSCs are important drivers of tumorigenesis and the metastatic process. Tamoxifen is the most widely used hormonal therapy for estrogen receptor (ER) positive cancers. In our study, tamoxifen was effective in reducing proliferation of ER + adherent cancer cells, but not their CSC population. We isolated, expanded and incubated CSC from seven breast cancers with or without tamoxifen. By genome-wide transcriptional analysis we identified tamoxifen-induced transcriptional pathways associated with ribosomal biogenesis and mRNA translation, both regulated by the mTOR-pathway. We observed induction of the key mTOR downstream targets S6K1, S6RP and 4E-BP1 in-patient derived CSCs by tamoxifen on protein level. Using the mTOR inhibitors rapamycin, everolimus and PF-04691502 (a dual PI3K/mTOR inhibitor) and in combination with tamoxifen, significant reduction in mammosphere formation was observed. Hence, we suggest that the CSC population play a significant role during endocrine resistance through activity of the mTOR pathway. In addition, tamoxifen further stimulates the mTOR-pathway but can be antagonized using mTOR-inhibitors.

Endothelial ALK1 Is a Therapeutic Target to Block Metastatic Dissemination of Breast Cancer.

Exploration of new strategies for the prevention of breast cancer metastasis is justifiably at the center of clinical attention. In this study, we combined a computational biology approach with mechanism-based preclinical trials to identify inhibitors of activin-like receptor kinase (ALK) 1 as effective agents for blocking angiogenesis and metastasis in breast cancer. Pharmacologic targeting of ALK1 provided long-term therapeutic benefit in mouse models of mammary carcinoma, accompanied by strikingly reduced metastatic colonization as a monotherapy or part of combinations with chemotherapy. Gene-expression analysis of breast cancer specimens from a population-based nested case-control study encompassing 768 subjects defined endothelial expression of ALK1 as an independent and highly specific prognostic factor for metastatic manifestation, a finding that was corroborated in an independent clinical cohort. Overall, our results suggest that pharmacologic inhibition of endothelial ALK1 constitutes a tractable strategy for interfering with metastatic dissemination of breast cancer.