A functionalized nanohydrogel siRNA delivery system and a mouse model of serous ovarian cancer were used to test predictions from previous cell line studies that knockdown of EGFR (epidermal growth factor receptor) may be of clinical significance in the treatment of epithelial tumors especially with respect to the enhancement of platinum based therapies. Our results support these predictions and suggest that targeted delivery of EGFR siRNA may be an effective strategy for the treatment of ovarian and other epithelial tumors associated with elevated levels of EGFR and especially those demonstrating resistance to platinum-based therapies.
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 5 years ago
Cushing disease (CD) is a life-threatening disorder attributed to excess pituitary tumor-derived adrenocorticotrophic hormone (ACTH) and adrenal steroid secretion caused by pituitary tumors. Whereas CD was first described in 1932, the underlying genetic basis driving tumor growth and ACTH secretion remains unsolved. Here, we show that testicular orphan nuclear receptor 4 (TR4, nuclear receptor subfamily 2, group C, member 2) is overexpressed in human corticotroph tumors as well as in human and mouse corticotroph tumor cell lines. Forced overexpression of TR4 in both human and murine tumor cells increased proopiomelanocortin transcription, ACTH secretion, cellular proliferation, and tumor invasion rates in vitro. Conversely, knockdown of TR4 expression reversed all phenotypes. Mechanistically, we show that TR4 transcriptionally activates proopiomelanocortin through binding of a direct repeat 1 response element in the promoter, and that this is enhanced by MAPK-mediated TR4 phosphorylation. In vivo, TR4 overexpression promotes murine corticotroph tumor growth as well as enhances ACTH and corticosterone production, whereas TR4 knockdown decreases circulating ACTH and corticosterone levels in mice harboring ACTH-secreting tumors. Our findings directly link TR4 to the etiology of corticotroph tumors, hormone secretion, and cell growth as well as identify it as a potential target in the treatment of CD.
Acquired resistance is one of the major barriers to successful cancer therapy. The development of resistance is commonly attributed to genetic heterogeneity. However, heterogeneity of drug penetration of the tumor microenvironment both on the microscopic level within solid tumors as well as on the macroscopic level across metastases may also contribute to acquired drug resistance. Here we use mathematical models to investigate the effect of drug heterogeneity on the probability of escape from treatment and the time to resistance. Specifically we address scenarios with sufficiently potent therapies that suppress growth of all preexisting genetic variants in the compartment with the highest possible drug concentration. To study the joint effect of drug heterogeneity, growth rate, and evolution of resistance, we analyze a multi-type stochastic branching process describing growth of cancer cells in multiple compartments with different drug concentrations and limited migration between compartments. We show that resistance is likely to arise first in the sanctuary compartment with poor drug penetrations and from there populate non-sanctuary compartments with high drug concentrations. Moreover, we show that only below a threshold rate of cell migration does spatial heterogeneity accelerate resistance evolution, otherwise deterring drug resistance with excessively high migration rates. Our results provide new insights into understanding why cancers tend to quickly become resistant, and that cell migration and the presence of sanctuary sites with little drug exposure are essential to this end.
Differentiated mammary epithelium shows apicobasal polarity, and loss of tissue organization is an early hallmark of breast carcinogenesis. In BRCA1 mutation carriers, accumulation of stem and progenitor cells in normal breast tissue and increased risk of developing tumors of basal-like type suggest that BRCA1 regulates stem/progenitor cell proliferation and differentiation. However, the function of BRCA1 in this process and its link to carcinogenesis remain unknown. Here we depict a molecular mechanism involving BRCA1 and RHAMM that regulates apicobasal polarity and, when perturbed, may increase risk of breast cancer. Starting from complementary genetic analyses across families and populations, we identified common genetic variation at the low-penetrance susceptibility HMMR locus (encoding for RHAMM) that modifies breast cancer risk among BRCA1, but probably not BRCA2, mutation carriers: n = 7,584, weighted hazard ratio ((w)HR) = 1.09 (95% CI 1.02-1.16), p(trend) = 0.017; and n = 3,965, (w)HR = 1.04 (95% CI 0.94-1.16), p(trend) = 0.43; respectively. Subsequently, studies of MCF10A apicobasal polarization revealed a central role for BRCA1 and RHAMM, together with AURKA and TPX2, in essential reorganization of microtubules. Mechanistically, reorganization is facilitated by BRCA1 and impaired by AURKA, which is regulated by negative feedback involving RHAMM and TPX2. Taken together, our data provide fundamental insight into apicobasal polarization through BRCA1 function, which may explain the expanded cell subsets and characteristic tumor type accompanying BRCA1 mutation, while also linking this process to sporadic breast cancer through perturbation of HMMR/RHAMM.
Abnormal vascularization of solid tumours results in the development of microenvironments deprived of oxygen and nutrients that harbour slowly growing and metabolically stressed cells. Such cells display enhanced resistance to standard chemotherapeutic agents and repopulate tumours after therapy. Here we identify the small molecule VLX600 as a drug that is preferentially active against quiescent cells in colon cancer 3-D microtissues. The anticancer activity is associated with reduced mitochondrial respiration, leading to bioenergetic catastrophe and tumour cell death. VLX600 shows enhanced cytotoxic activity under conditions of nutrient starvation. Importantly, VLX600 displays tumour growth inhibition in vivo. Our findings suggest that tumour cells in metabolically compromised microenvironments have a limited ability to respond to decreased mitochondrial function, and suggest a strategy for targeting the quiescent populations of tumour cells for improved cancer treatment.
PURPOSE: Development of a heptamethine cyanine based tumor-targeting PET imaging probe for noninvasive detection and diagnosis of breast cancer. METHODS: Tumor-specific heptamethine-cyanine DOTA conjugate complexed with Cu-64 (PC-1001) was synthesized for breast cancer imaging. In vitro cellular uptake studies were performed in the breast cancer MCF-7 and noncancerous breast epithelial MCF-10A cell lines to establish tumor specificity. In vivo time-dependent fluorescence and PET imaging of breast tumor xenografts in mice were performed. Blood clearance, biodistribution, and tumor-specific uptake and plasma binding of PC-1001 were quantified. Tumor histology (H&E staining) and fluorescence imaging were examined. RESULTS: PC-1001 displayed similar fluorescence properties (ε=82,880cm(-1)M(-1), E(x)/E(m)=750/820nm) to the parental dye. Time-dependent cellular accumulation indicated significantly higher probe uptake (>2-fold, 30min) in MCF-7 than MCF-10A cells and the uptake was observed to be mediated by organic anion transport peptides (OATPs) system. In vivo studies revealed that PC-1001 has desirable accumulation profile in tumor tissues, with tumor versus muscle uptake of about 4.3 fold at 24h and 5.8 fold at 48h post probe injections. Blood half-life of PC-1001 was observed to be 4.3±0.2h. Microscopic fluorescence imaging of harvested tumor indicated that the uptake of PC-1001 was restricted to viable rather than necrotic tumor cells. CONCLUSIONS: A highly efficient tumor-targeting PET/fluorescence imaging probe PC-1001 is synthesized and validated in vitro in MCF-7 breast cancer cells and in vivo in mice breast cancer xenograft model.
BACKGROUND: Cancer outlier profile analysis (COPA) has proven to be an effective approach to analyzing cancer expression data, leading to the discovery of the TMPRSS2 and ETS family gene fusion events in prostate cancer. However, the original COPA algorithm did not identify down-regulated outliers, and the currently available R package implementing the method is similarly restricted to the analysis of over-expressed outliers. Here we present a modified outlier detection method, mCOPA, which contains refinements to the outlier-detection algorithm, identifies both over- and under-expressed outliers, is freely available, and can be applied to any expression dataset. RESULTS: We compare our method to other feature-selection approaches, and demonstrate that mCOPA frequently selects more-informative features than do differential expression or variance-based feature selection approaches, and is able to recover observed clinical subtypes more consistently. We demonstrate the application of mCOPA to prostate cancer expression data, and explore the use of outliers in clustering, pathway analysis, and the identification of tumour suppressors. We analyse the under-expressed outliers to identify known and novel prostate cancer tumour suppressor genes, validating these against data in Oncomine and the Cancer Gene Index. We also demonstrate how a combination of outlier analysis and pathway analysis can identify molecular mechanisms disrupted in individual tumours. CONCLUSIONS: We demonstrate that mCOPA offers advantages, compared to differential expression or variance, in selecting outlier features, and that the features so selected are better able to assign samples to clinically annotated subtypes. Further, we show that the biology explored by outlier analysis differs from that uncovered in differential expression or variance analysis. mCOPA is an important new tool for the exploration of cancer datasets and the discovery of new cancer subtypes, and can be combined with pathway and functional analysis approaches to discover mechanisms underpinning heterogeneity in cancers.
BACKGROUND: New therapies are urgently needed for patients with small cell lung cancer (SCLC). Chemotherapy and targeted therapies, including the Bcl-2 inhibitor ABT-737, may induce tumor cell autophagy. Autophagy can promote survival of cancer cells under stress and comprise a pathway of escape from cytotoxic therapies. METHODS: We explored the combination of ABT-737 and chloroquine, an inhibitor of autophagy, in preclinical models of SCLC. These included cell culture analyses of viability and of autophagic and apoptotic pathway induction, as well as in vivo analyses of efficacy in multiple xenograft models. RESULTS: Combination treatment of SCLC lines with ABT-737 and chloroquine decreased viability and increased caspase-3 activation over treatment with either single agent. ABT-737 induced several hallmarks of autophagy. However, knockdown of beclin-1, a key regulator of entry into autophagy, diminished the efficacy of ABT-737, suggesting either that the effects of chloroquine were nonspecific or that induction but not completion of autophagy is necessary for the combined effect of ABT-737 and chloroquine. ABT-737 and chloroquine in SCLC cell lines downregulated Mcl-1 and upregulated NOXA, both of which may promote apoptosis. Treatment of tumor-bearing mice demonstrated that chloroquine could enhance ABT-737-mediated tumor growth inhibition against NCI-H209 xenografts, but did not alter ABT-737 response in three primary patient-derived xenograft models. CONCLUSION: These data suggest that although ABT-737 can induce autophagy in SCLC, autophagic inhibition by choroquine does not markedly alter in vivo response to ABT-737 in relevant preclinical models, arguing against this as a treatment strategy for SCLC.
OBJECTIVE: To clearly define the proportions of benign vs malignant histologic findings in resected renal masses through an in-depth review of the contemporary medical data to assist in preoperative risk assessment. MATERIALS AND METHODS: PubMed and select oncology congresses were searched for publications that identify the histologic classification of resected renal masses in a representative sample from the contemporary data: [search] incidence AND (renal cell carcinoma AND benign); incidence AND (renal tumor AND benign); percentage AND (renal cell carcinoma AND benign); limit 2003-2011. RESULTS: We identified 26 representative studies meeting the inclusion criteria and incorporating 27,272 patients. The frequency of benign tumors ranged from 7% to 33%, with most studies within a few percentage points of the mean (14.5% ± 5.2%, median 13.9%). Clear cell renal cell carcinoma occurred in 46% to 83% of patients, with a mean of 68.3% (median 61.3; SD = 11.9%). An inverse relationship between tumor size and benign pathologic features was identified in 14 of 19 (74%) studies that examined an association between tumor size and pathologic characteristics. A statistically significant correlation between clear cell renal cell carcinoma and tumor size was identified in 13 of 19 studies (63%). The accuracy of preoperative cross-sectional imaging was low in the 2 studies examining computed tomography (17%). CONCLUSION: Benign renal tumors represent ∼15% of detected surgically resected renal masses and are more prevalent among small clinical T1a lesions. Noninvasive preoperative differentiation between more and less aggressive renal masses would be an important clinical advance that could allow clinicians greater diagnostic confidence and guide patient management through improved risk stratification.
In recent studies, both tumor morphology and vascularity played an important role in differentiating breast tumors. In this article, a computer-aided diagnosis (CAD) system was proposed to quantify the tumor morphology of vascularity on three-dimensional (3-D) power Doppler breast ultrasound (PDUS) images. We segmented the tumor margin by the level set method and skeletonized vessels by the 3-D thinning algorithm from 3-D PDUS data to capture the B-mode and vascularity features. The B-mode features including texture, shape and ellipsoid fitting and the vascularity features containing volume, complexity, length, radius and tortuosity were used to differentiate breast tumors. In the experiment, 82 biopsy-verified lesions including 41 benign and 41 malignant lesions were used to test the performance of the proposed system. The proposed method performed well, achieving accuracy, sensitivity, specificity and Az values of 85.37% (70/82), 85.37% (35/41), 85.37% (35/41) and 0.9104, respectively.