Preclinical Development of PNT6555, a Boronic Acid-Based, Fibroblast Activation Protein-α (FAP)-Targeted Radiotheranostic for Imaging and Treatment of FAP-Positive Tumors.

The overexpression of fibroblast activation protein-α (FAP) in solid cancers relative to levels in normal tissues has led to its recognition as a target for delivering agents directly to tumors. Radiolabeled quinoline-based FAP ligands have established clinical feasibility for tumor imaging, but their therapeutic potential is limited due to suboptimal tumor retention, which has prompted the search for alternative pharmacophores. One such pharmacophore is the boronic acid derivative N-(pyridine-4-carbonyl)-d-Ala-boroPro, a potent and selective FAP inhibitor (FAPI). In this study, the diagnostic and therapeutic (theranostic) potential of N-(pyridine-4-carbonyl)-d-Ala-boroPro-based metal-chelating DOTA-FAPIs was evaluated. Methods: Three DOTA-FAPIs, PNT6555, PNT6952, and PNT6522, were synthesized and characterized with respect to potency and selectivity toward soluble and cell membrane FAP; cellular uptake of the Lu-chelated analogs; biodistribution and pharmacokinetics in mice xenografted with human embryonic kidney cell-derived tumors expressing mouse FAP; the diagnostic potential of 68Ga-chelated DOTA-FAPIs by direct organ assay and small-animal PET; the antitumor activity of 177Lu-, 225Ac-, or 161Tb-chelated analogs using human embryonic kidney cell-derived tumors expressing mouse FAP; and the tumor-selective delivery of 177Lu-chelated DOTA-FAPIs via direct organ assay and SPECT. Results: DOTA-FAPIs and their natGa and natLu chelates exhibited potent inhibition of human and mouse sources of FAP and greatly reduced activity toward closely related prolyl endopeptidase and dipeptidyl peptidase 4. 68Ga-PNT6555 and 68Ga-PNT6952 showed rapid renal clearance and continuous accumulation in tumors, resulting in tumor-selective exposure at 60 min after administration. 177Lu-PNT6555 was distinguished from 177Lu-PNT6952 and 177Lu-PNT6522 by significantly higher tumor accumulation over 168 h. In therapeutic studies, all 3 177Lu-DOTA-FAPIs exhibited significant antitumor activity at well-tolerated doses, with 177Lu-PNT6555 producing the greatest tumor growth delay and animal survival. 225Ac-PNT6555 and 161Tb-PNT6555 were similarly efficacious, producing 80% and 100% survival at optimal doses, respectively. Conclusion: PNT6555 has potential for clinical translation as a theranostic agent in FAP-positive cancer.

Therapeutic Targeting of LIF Overcomes Macrophage-mediated Immunosuppression of the Local Tumor Microenvironment.

PURPOSE: Leukemia inhibitory factor (LIF) is a multifunctional cytokine with numerous reported roles in cancer and is thought to drive tumor development and progression. Characterization of LIF and clinical-stage LIF inhibitors would increase our understanding of LIF as a therapeutic target. EXPERIMENTAL DESIGN: We first tested the association of LIF expression with transcript signatures representing multiple processes regulating tumor development and progression. Next, we developed MSC-1, a high-affinity therapeutic antibody that potently inhibits LIF signaling and tested it in immune competent animal models of cancer. RESULTS: LIF was associated with signatures of tumor-associated macrophages (TAM) across 7,769 tumor samples spanning 22 solid tumor indications. In human tumors, LIF receptor was highly expressed within the macrophage compartment and LIF treatment drove macrophages to acquire immunosuppressive capacity. MSC-1 potently inhibited LIF signaling by binding an epitope that overlaps with the gp130 receptor binding site on LIF. MSC-1 showed monotherapy efficacy in vivo and drove TAMs to acquire antitumor and proinflammatory function in syngeneic colon cancer mouse models. Combining MSC-1 with anti-PD1 leads to strong antitumor response and a long-term tumor-free survival in a significant proportion of treated mice. CONCLUSIONS: Overall, our findings highlight LIF as a therapeutic target for cancer immunotherapy.

Monoamine oxidase-A activity is required for clonal tumorsphere formation by human breast tumor cells.

BACKGROUND: Breast tumor growth and recurrence are driven by an infrequent population of breast tumor-initiating cells (BTIC). We and others have reported that the frequency of BTIC is orders of magnitude higher when breast tumor cells are propagated in vitro as clonal spheres, termed tumorspheres, by comparison to adherent cells. We exploited the latter to screen > 35,000 small molecules to identify agents capable of targeting BTIC. We unexpectedly discovered that selective antagonists of serotonin signaling were among the hit compounds. To better understand the relationship between serotonin and BTIC we expanded our analysis to include monoamine oxidase-A (MAO-A), an enzyme that metabolizes serotonin. METHODS: We used the Nanostring technology and Western blotting to determine whether MAO-A is expressed in human breast tumor cell lines cultured as tumorspheres by comparison to those grown as adherent cells. We then determined whether MAO-A activity is required for tumorsphere formation, a surrogate in vitro assay for BTIC, by assessing whether selective MAO-A inhibitors affect the frequency of tumorsphere-forming cells. To learn whether MAO-A expression in breast tumor cells is associated with other reported properties of BTIC such as anticancer drug resistance or breast tumor recurrence, we performed differential gene expression analyses using publicly available transcriptomic datasets. RESULTS: Tumorspheres derived from human breast tumor cell lines representative of every breast cancer clinical subtype displayed increased expression of MAO-A transcripts and protein by comparison to adherent cells. Surprisingly, inhibition of MAO-A activity with selective inhibitors reduced the frequency of tumorsphere-forming cells. We also found that increased MAO-A expression is a common feature of human breast tumor cell lines that have acquired anticancer drug resistance and is associated with poor recurrence-free survival (RFS) in patients that experienced high-grade, ER-negative (ER-) breast tumors. CONCLUSIONS: Our data suggests that MAO-A activity is required for tumorsphere formation and that its expression in breast tumor cells is associated with BTIC-related properties. The discovery that a selective MAO-A inhibitor targets tumorsphere-forming cells with potencies in the nanomolar range provides the first evidence of this agent's anticancer property. These data warrant further investigation of the link between MAO-A and BTIC.

A novel method for quantifying axon degeneration.

Axons normally degenerate during development of the mammalian nervous system, but dysregulation of the same genetically-encoded destructive cellular machinery can destroy crucial structures during adult neurodegenerative diseases. Nerve growth factor (NGF) withdrawal from dorsal root ganglia (DRG) axons is a well-established in vitro experimental model for biochemical and cell biological studies of developmental degeneration. Definitive methods for measuring axon degeneration have been lacking and here we report a novel method of axon degeneration quantification from bulk cultures of DRG that enables objective and automated measurement of axonal density over the entire field of radial axon outgrowth from the ganglion. As proof of principal, this new method, written as an R script called Axoquant 2.0, was used to examine the role of extracellular Ca2+ in the execution of cytoskeletal disassembly during degeneration of NGF-deprived DRG axons. This method can be easily applied to examine degenerative or neuroprotective effects of gene manipulations and pharmacological interventions.

Serotonergic system antagonists target breast tumor initiating cells and synergize with chemotherapy to shrink human breast tumor xenografts.

Breast tumors comprise an infrequent tumor cell population, termed breast tumor initiating cells (BTIC), which sustain tumor growth, seed metastases and resist cytotoxic therapies. Hence therapies are needed to target BTIC to provide more durable breast cancer remissions than are currently achieved. We previously reported that serotonergic system antagonists abrogated the activity of mouse BTIC resident in the mammary tumors of a HER2-overexpressing model of breast cancer. Here we report that antagonists of serotonin (5-hydroxytryptamine; 5-HT) biosynthesis and activity, including US Federal Food and Drug Administration (FDA)-approved antidepressants, targeted BTIC resident in numerous breast tumor cell lines regardless of their clinical or molecular subtype. Notably, inhibitors of tryptophan hydroxylase 1 (TPH1), required for 5-HT biosynthesis in select non-neuronal cells, the serotonin reuptake transporter (SERT) and several 5-HT receptors compromised BTIC activity as assessed by functional sphere-forming assays. Consistent with these findings, human breast tumor cells express TPH1, 5-HT and SERT independent of their molecular or clinical subtype. Exposure of breast tumor cells ex vivo to sertraline (Zoloft), a selective serotonin reuptake inhibitor (SSRI), reduced BTIC frequency as determined by transplanting drug-treated tumor cells into immune-compromised mice. Moreover, another SSRI (vilazodone; Viibryd) synergized with chemotherapy to shrink breast tumor xenografts in immune-compromised mice by inhibiting tumor cell proliferation and inducing their apoptosis. Collectively our data suggest that antidepressants in combination with cytotoxic anticancer therapies may be an appropriate treatment regimen for testing in clinical trials.

Claudin-Low Breast Cancer; Clinical & Pathological Characteristics.

Claudin-low breast cancer is a molecular type of breast cancer originally identified by gene expression profiling and reportedly associated with poor survival. Claudin-low tumors have been recognised to preferentially display a triple-negative phenotype, however only a minority of triple-negative breast cancers are claudin-low. We sought to identify an immunohistochemical profile for claudin-low tumors that could facilitate their identification in formalin fixed paraffin embedded tumor material. First, an in silico collection of ~1600 human breast cancer expression profiles was assembled and all claudin-low tumors identified. Second, genes differentially expressed between claudin-low tumors and all other molecular subtypes of breast cancer were identified. Third, a number of these top differentially expressed genes were tested using immunohistochemistry for expression in a diverse panel of breast cancer cell lines to determine their specificity for claudin-low tumors. Finally, the immunohistochemical panel found to be most characteristic of claudin-low tumors was examined in a cohort of 942 formalin fixed paraffin embedded human breast cancers with >10 years clinical follow-up to evaluate the clinico-pathologic and survival characteristics of this tumor subtype. Using this approach we determined that claudin-low breast cancer is typically negative for ER, PR, HER2, claudin 3, claudin 4, claudin 7 and E-cadherin. Claudin-low tumors identified with this immunohistochemical panel, were associated with young age of onset, higher tumor grade, larger tumor size, extensive lymphocytic infiltrate and a circumscribed tumor margin. Patients with claudin-low tumors had a worse overall survival when compared to patients with luminal A type breast cancer. Interestingly, claudin-low tumors were associated with a low local recurrence rate following breast conserving therapy. In conclusion, a limited panel of antibodies can facilitate the identification of claudin-low tumors. Furthermore, claudin-low tumors identified in this manner display similar clinical, pathologic and survival characteristics to claudin-low tumors identified from fresh frozen tumor material using gene expression profiling.

Transcript signatures that predict outcome and identify targetable pathways in MYCN-amplified neuroblastoma.

BACKGROUND: In the pediatric cancer neuroblastoma (NB), patients are stratified into low, intermediate or high-risk subsets based in part on MYCN amplification status. While MYCN amplification in general predicts unfavorable outcome, no clinical or genomic factors have been identified that predict outcome within these cohorts of high-risk patients. In particular, it is currently not possible at diagnosis to determine which high-risk neuroblastoma patients will ultimately fail upfront therapy. EXPERIMENTAL DESIGN: We analyzed the prognostic potential of most published gene expression signatures for NB and developed a new prognostic signature to predict outcome for patients with MYCN amplification. Network and pathway analyses identified candidate therapeutic targets for this MYCN-amplified patient subset with poor outcome. RESULTS: Most signatures have a high capacity to predict outcome of unselected NB patients. However, the majority of published signatures, as well as most randomly generated signatures, are highly confounded by MYCN amplification, and fail to predict outcome in subpopulations of high-risk patients with MYCN-amplified NB. We identify a MYCN module signature that predicts patient outcome for those with MYCN-amplified tumors, that also predicts potential tractable therapeutic signaling pathways and targets including the DNA repair enzyme Poly [ADP-ribose] polymerase 1 (PARP1). CONCLUSION: Many prognostic signatures for NB are confounded by MYCN amplification and fail to predict outcome for the subset of high-risk patients with MYCN amplification. We report a MYCN module signature that is associated with distinct patient outcomes, and predicts candidate therapeutic targets in DNA repair pathways, including PARP1 in MYCN-amplified NB.

Serotonin transporter antagonists target tumor-initiating cells in a transgenic mouse model of breast cancer.

Accumulating data suggests that the initiation and progression of human breast tumors is fueled by a rare subpopulation of tumor cells, termed breast tumor-initiating cells (BTIC), which resist radiotherapy and chemotherapy. Consequently, therapies that abrogate BTIC activity are needed to achieve durable cures for breast cancer patients. To identify such therapies we used a sensitive assay to complete a high-throughput screen of small molecules, including approved drugs, with BTIC-rich mouse mammary tumor cell populations. We found that inhibitors of the serotonin reuptake transporter (SERT) and serotonin receptors, which include approved drugs used to treat mood disorders, were potent inhibitors of mouse BTIC activity as determined by functional sphere-forming assays and the initiation of tumor formation by transplant of drug-exposed tumor cells into syngeneic mice. Moreover, sertraline (Zoloft), a selective serotonin reuptake inhibitor (SSRI), synergized with docetaxel (Taxotere) to shrink mouse breast tumors in vivo. Hence drugs targeting the serotonergic system might be repurposed to treat breast cancer patients to afford more durable breast cancer remissions.

The effects of lymph node status on predicting outcome in ER+ /HER2- tamoxifen treated breast cancer patients using gene signatures.

BACKGROUND: Lymph node (LN) status is the most important prognostic variable used to guide ER positive (+) breast cancer treatment. While a positive nodal status is traditionally associated with a poor prognosis, a subset of these patients respond well to treatment and achieve long-term survival. Several gene signatures have been established as a means of predicting outcome of breast cancer patients, but the development and indication for use of these assays varies. Here we compare the capacity of two approved gene signatures and a third novel signature to predict outcome in distinct LN negative (-) and LN+ populations. We also examine biological differences between tumours associated with LN- and LN+ disease. METHODS: Gene expression data from publically available data sets was used to compare the ability of Oncotype DX and Prosigna to predict Distant Metastasis Free Survival (DMFS) using an in silico platform. A novel gene signature (Ellen) was developed by including patients with both LN- and LN+ disease and using Prediction Analysis of Microarrays (PAM) software. Gene Set Enrichment Analysis (GSEA) was used to determine biological pathways associated with patient outcome in both LN- and LN+ tumors. RESULTS: The Oncotype DX gene signature, which only used LN- patients during development, significantly predicted outcome in LN- patients, but not LN+ patients. The Prosigna gene signature, which included both LN- and LN+ patients during development, predicted outcome in both LN- and LN+ patient groups. Ellen was also able to predict outcome in both LN- and LN+ patient groups. GSEA suggested that epigenetic modification may be related to poor outcome in LN- disease, whereas immune response may be related to good outcome in LN+ disease. CONCLUSIONS: We demonstrate the importance of incorporating lymph node status during the development of prognostic gene signatures. Ellen may be a useful tool to predict outcome of patients regardless of lymph node status, or for those with unknown lymph node status. Finally we present candidate biological processes, unique to LN- and LN+ disease, that may indicate risk of relapse.

A novel stem cell culture model of recurrent glioblastoma.

Glioblastoma (GBM) is the most common and aggressive primary brain tumor in adults with average disease relapse at 9 months and median survival rarely extending beyond 15 months. Brain tumor stem cells (BTSCs) have been implicated in not only initiating GBM but also conferring resistance to therapy. However, it is not clear whether the BTSC population that initiates tumor growth is also responsible for GBM recurrence. In this study, we have developed a novel in vitro treatment model to profile the evolution of primary treatment-naïve GBM BTSCs through chemoradiotherapy. We report that our in vitro model enriched for a CD15+/CD133- BTSC population, mirroring the phenotype of BTSCs in recurrent GBM. We also show that in vitro treatment increased stem cell gene expression as well as self-renewal capacity of primary GBMs. In addition, the chemoradiotherapy-refractory gene signature obtained from gene expression profiling identified a hyper-aggressive subtype of glioma. The delivery of in vitro chemoradiotherapy to primary GBM BTSCs models several aspects of recurrent GBM biology, and could be used as a discovery and drug-screening platform to uncover new biological drivers and therapeutic targets in GBM.

Methylation-dependent regulation of hypoxia inducible factor-1 alpha gene expression by the transcription factor Kaiso.

Low oxygen tension (hypoxia) is a common characteristic of solid tumors and strongly correlates with poor prognosis and resistance to treatment. In response to hypoxia, cells initiate a cascade of transcriptional events regulated by the hypoxia inducible factor-1 (HIF-1) heterodimer. Since the oxygen-sensitive HIF-1α subunit is stabilized during hypoxia, it functions as the regulatory subunit of the protein. To date, while the mechanisms governing HIF-1α protein stabilization and function have been well studied, those governing HIF1A gene expression are not fully understood. However, recent studies have suggested that methylation of a HIF-1 binding site in the HIF1A promoter prevents its autoregulation. Here we report that the POZ-ZF transcription factor Kaiso modulates HIF1A gene expression by binding to the methylated HIF1A promoter in a region proximal to the autoregulatory HIF-1 binding site. Interestingly, Kaiso's regulation of HIF1A occurs primarily during hypoxia, which is consistent with the finding that Kaiso protein levels peak after 4 h of hypoxic incubation and return to normoxic levels after 24 h. Our data thus support a role for Kaiso in fine-tuning HIF1A gene expression after extended periods of hypoxia.

Identification and evaluation of network modules for the prognosis of basal-like breast cancer.

PURPOSE: Basal-like breast cancer (BLBC) is a molecular subtype of breast cancer associated with poor clinical outcome, although some patients with BLBC experience long-term survival. Apart from nodal status, current clinical/histopathological variables show little capacity to identify BLBC patients at either high- or low-risk of disease recurrence. Accordingly, we sought to develop a network based genomic predictor for predicting the outcome of patients with BLBC. EXPERIMENTAL DESIGN: We performed network analysis on global gene expression profiling data of BLBCs, and identified BLBC network modules associated with AP-1 transcription, G-protein coupled receptors, and T-, B-, and NK-cells that are significant predictors of BLBC patient survival. RESULTS: In gene expression and tissue microarray (TMA) validation cohorts of 210 and 102 BLBC patients, respectively, the identified network modules were robustly associated with patient outcome. In the gene expression validation cohort, the Kaplan-Meier estimate for 10-year survival in the low-risk group was 90%, whereas in the high-risk group it was a 56%. In the TMA cohort, the Kaplan-Meier estimate for 10-year survival in the low-risk group was 98%, whereas in the high-risk group it was 71%. CONCLUSIONS: The capacity to distinguish between patients with BLBC at high- or low-risk of recurrence at the time of diagnosis could permit timely intervention with more aggressive therapeutic regimens in those patients predicted to be high-risk, and to avoid such therapy in low-risk patients.

Treatment-induced cell cycle kinetics dictate tumor response to chemotherapy.

Chemotherapy fails to provide durable cure for the majority of cancer patients. To identify mechanisms associated with chemotherapy resistance, we identified genes differentially expressed before and after chemotherapeutic treatment of breast cancer patients. Treatment response resulted in either increased or decreased cell cycle gene expression. Tumors in which cell cycle gene expression was increased by chemotherapy were likely to be chemotherapy sensitive, whereas tumors in which cell cycle gene transcripts were decreased by chemotherapy were resistant to these agents. A gene expression signature that predicted these changes proved to be a robust and novel index that predicted the response of patients with breast, ovarian, and colon tumors to chemotherapy. Investigations in tumor cell lines supported these findings, and linked treatment induced cell cycle changes with p53 signaling and G1/G0 arrest. Hence, chemotherapy resistance, which can be predicted based on dynamics in cell cycle gene expression, is associated with TP53 integrity.

Immune cell transcript modules reveal leukocyte heterogeneity in synovial biopsies of seronegative spondylarthropathy patients.

BACKGROUND: The objective of this study was to identify leukocyte cell types found within the synovia of patients with seronegative spondylarthropathies (SpA), such as ankylosing spondylitis (AS), using transcription based analyses. METHODS: Leukocyte transcriptional profiles obtained from the NCBI's gene expression omnibus and prediction analysis of microarrays (PAM) was used to identify 25-gene leukocyte metagenes. Subsequently, transcriptional profiles from murine and clinical models of AS and SpA were interrogated to characterize the local infiltration of leukocytes in SpA synovia. RESULTS: Analysis of a proteoglycan-induced murine model of AS reveals infiltration of dendritic cells, CD4+ T cells, monocytes, and natural killer cells to the spine. In human SpA and AS patients, transcriptional analysis of synovial biopsies revealed local infiltration of dendritic cells and CD4+ T cells. CONCLUSIONS: We identified leukocyte cell types that infiltrated the synovial of SpA patients. Our results imply a role for dendritic cells and CD4+ T cells in the local inflammation that underlies pathogenesis in patients with SpA.

Estrogen independent gene expression defines clinically relevant subgroups of estrogen receptor positive breast cancer.

BACKGROUND: Human breast cancer represents a significantly heterogeneous disease. Global gene expression profiling measurements have been used to classify tumors into multiple molecular subtypes. The capacity to define subtypes of breast tumors provides a framework to enable improved understanding of the mechanisms of breast oncogenesis, as well as to provide opportunities for improved therapeutic intervention in patients. METHODS: We used publicly available gene expression profiling data to identify 'estrogen independent' genes in estrogen receptor alpha (ER+) breast tumors, and subsequently identified 6 subgroups of ER+breast tumors. RESULTS: Each of the 6 identified subgroups exhibited distinct clinical behaviors and biology. Patients whose tumors comprised subgroups 2,5&6 experienced excellent long-term survival, whereas those patients whose tumors belonged to subgroups 1&4 experienced much poorer survival. Breast tumor cell lines representative of the different subgroups responded to therapeutic compounds in accordance with their subgroup classification. CONCLUSIONS: These data support the existence of 6 distinct subgroups of ER+breast cancer and suggest that knowledge of the ER+subgroup status of patient samples have the potential to guide therapy choice.

A program to identify prognostic and predictive gene signatures.

BACKGROUND: The advent of high-throughput technologies to profile human tumors has generated unprecedented insight into our molecular understanding of cancer. However, analysis of such high dimensional data is challenging and requires significant expertise which is not routinely available to many cancer researchers. RESULTS: To overcome this limitation, we developed a freely accessible and user friendly Program to Identify Molecular Signatures (PIMS). Importantly, such signatures allow important insight into cancer biology, as well as provide clinical tools to identify potential biomarkers that might provide means to accurately stratify patients into different risk or treatment groups. We evaluated the performance of PIMS by identifying and testing predictive and prognostic gene signatures for breast cancer, using multiple breast tumor microarray cohorts representing hundreds of patients. Importantly, PIMS identified signatures classified patients into high and low risk groups with at least similar performance to other commonly used gene signature selection techniques. CONCLUSIONS: Our program is contained entirely within a Microsoft Excel file and therefore requires no installation of any additional programs or training. Hence, PIMS provides an accessible tool for cancer researchers to identify predictive and prognostic gene signatures to advance their research.

Single unpurified breast tumor-initiating cells from multiple mouse models efficiently elicit tumors in immune-competent hosts.

The tumor-initiating cell (TIC) frequency of bulk tumor cell populations is one of the criteria used to distinguish malignancies that follow the cancer stem cell model from those that do not. However, tumor-initiating cell frequencies may be influenced by experimental conditions and the extent to which tumors have progressed, parameters that are not always addressed in studies of these cells. We employed limiting dilution cell transplantation of minimally manipulated tumor cells from mammary tumors of several transgenic mouse models to determine their tumor-initiating cell frequency. We determined whether the tumors that formed following tumor cell transplantation phenocopied the primary tumors from which they were isolated and whether they could be serially transplanted. Finally we investigated whether propagating primary tumor cells in different tissue culture conditions affected their resident tumor-initiating cell frequency. We found that tumor-initiating cells comprised between 15% and 50% of the bulk tumor cell population in multiple independent mammary tumors from three different transgenic mouse models of breast cancer. Culture of primary mammary tumor cells in chemically-defined, serum-free medium as non-adherent tumorspheres preserved TIC frequency to levels similar to that of the primary tumors from which they were established. By contrast, propagating the primary tumor cells in serum-containing medium as adherent populations resulted in a several thousand-fold reduction in their tumor-initiating cell fraction. Our findings suggest that experimental conditions, including the sensitivity of the transplantation assay, can dramatically affect estimates of tumor initiating cell frequency. Moreover, conditional on cell culture conditions, the tumor-initiating cell fraction of bulk mouse mammary tumor cell preparations can either be maintained at high or low frequency in vitro thus permitting comparative studies of tumorigenic and non-tumorigenic cancer cells.

FoxG1 interacts with Bmi1 to regulate self-renewal and tumorigenicity of medulloblastoma stem cells.

Brain tumors represent the leading cause of childhood cancer mortality, of which medulloblastoma (MB) is the most frequent malignant tumor. Recent studies have demonstrated the presence of several MB molecular subgroups, each distinct in terms of prognosis and predicted therapeutic response. Groups 1 and 2 are characterized by relatively good clinical outcomes and activation of the Wnt and Shh pathways, respectively. In contrast, groups 3 and 4 ("non-Shh/Wnt MBs") are distinguished by metastatic disease, poor patient outcome, and lack a molecular pathway phenotype. Current gene expression platforms have not detected brain tumor-initiating cell (BTIC) self-renewal genes in groups 3 and 4 MBs as BTICs typically comprise a minority of tumor cells and may therefore go undetected on bulk tumor analyses. Since increasing BTIC frequency has been associated with increasing tumor aggressiveness and poor patient outcome, we investigated the subgroup-specific gene expression profile of candidate stem cell genes within 251 primary human MBs from four nonoverlapping MB transcriptional databases (Amsterdam, Memphis, Toronto, Boston) and 74 NanoString-subgrouped MBs (Vancouver). We assessed the functional relevance of two genes, FoxG1 and Bmi1, which were significantly enriched in non-Shh/Wnt MBs and showed these genes to mediate MB stem cell self-renewal and tumor initiation in mice. We also identified their transcriptional regulation through reciprocal promoter occupancy in CD15+ MB stem cells. Our work demonstrates the application of stem cell data gathered from genomic platforms to guide functional BTIC assays, which may then be used to develop novel BTIC self-renewal mechanisms amenable to therapeutic targeting.

A cancer stem cell model for studying brain metastases from primary lung cancer.

BACKGROUND: Brain metastases are most common in adults with lung cancer, predicting uniformly poor patient outcome, with a median survival of only months. Despite their frequency and severity, very little is known about tumorigenesis in brain metastases. METHODS: We applied previously developed primary solid tumor-initiating cell models to the study of brain metastases from the lung to evaluate the presence of a cancer stem cell population. Patient-derived brain metastases (n = 20) and the NCI-H1915 cell line were cultured as stem-enriching tumorspheres. We used in vitro limiting-dilution and sphere-forming assays, as well as intracranial human-mouse xenograft models. To determine genes overexpressed in brain metastasis tumorspheres, we performed comparative transcriptome analysis. All statistical analyses were two-sided. RESULTS: Patient-derived brain metastasis tumorspheres had a mean sphere-forming capacity of 33 spheres/2000 cells (SD = 33.40) and median stem-cell frequency of 1/60 (range = 0-1/141), comparable to that of primary brain tumorspheres (P = .53 and P = .20, respectively). Brain metastases also expressed CD15 and CD133, markers suggestive of a stemlike population. Through intracranial xenotransplantation, brain metastasis tumorspheres were found to recapitulate the original patient tumor heterogeneity. We also identified several genes overexpressed in brain metastasis tumorspheres as statistically significant predictors of poor survival in primary lung cancer. CONCLUSIONS: For the first time, we demonstrate the presence of a stemlike population in brain metastases from the lung. We also show that NCI-H1915 tumorspheres could be useful in studying self-renewal and tumor initiation in brain metastases. Our candidate genes may be essential to metastatic stem cell populations, where pathway interference may be able to transform a uniformly fatal disease into a more localized and treatable one.

A target based approach identifies genomic predictors of breast cancer patient response to chemotherapy.

BACKGROUND: The efficacy of chemotherapy regimens in breast cancer patients is variable and unpredictable. Whether individual patients either achieve long-term remission or suffer recurrence after therapy may be dictated by intrinsic properties of their breast tumors including genetic lesions and consequent aberrant transcriptional programs. Global gene expression profiling provides a powerful tool to identify such tumor-intrinsic transcriptional programs, whose analyses provide insight into the underlying biology of individual patient tumors. For example, multi-gene expression signatures have been identified that can predict the likelihood of disease reccurrence, and thus guide patient prognosis. Whereas such prognostic signatures are being introduced in the clinical setting, similar signatures that predict sensitivity or resistance to chemotherapy are not currently clinically available. METHODS: We used gene expression profiling to identify genes that were co-expressed with genes whose transcripts encode the protein targets of commonly used chemotherapeutic agents. RESULTS: Here, we present target based expression indices that predict breast tumor response to anthracycline and taxane based chemotherapy. Indeed, these signatures were independently predictive of chemotherapy response after adjusting for standard clinic-pathological variables such as age, grade, and estrogen receptor status in a cohort of 488 breast cancer patients treated with adriamycin and taxotere/taxol. CONCLUSIONS: Importantly, our findings suggest the practicality of developing target based indices that predict response to therapeutics, as well as highlight the possibility of using gene signatures to guide the use of chemotherapy during treatment of breast cancer patients.