Background

Distant recurrences after antineoplastic treatment remain a serious problem for breast cancer clinical management, which threats patients’ life. Systemic therapy is administered to eradicate cancer cells from the organism, both at the site of the primary tumor and at any other potential location. Despite this intervention, a significant proportion of breast cancer patients relapse even many years after their primary tumor has been successfully treated according to current clinical standards, evidencing the existence of a chemoresistant cell subpopulation originating from the primary tumor.

Methods/Findings

To identify key molecules and signaling pathways which drive breast cancer chemoresistance we performed gene expression analysis before and after anthracycline and taxane-based chemotherapy and compared the results between different histopathological response groups (good-, mid- and bad-response), established according to the Miller & Payne grading system. Two cohorts of 33 and 73 breast cancer patients receiving neoadjuvant chemotherapy were recruited for whole-genome expression analysis and validation assay, respectively. Identified genes were subjected to a bioinformatic analysis in order to ascertain the molecular function of the proteins they encode and the signaling in which they participate. High throughput technologies identified 65 gene sequences which were over-expressed in all groups (P ≤ 0·05 Bonferroni test). Notably we found that, after chemotherapy, a significant proportion of these genes were over-expressed in the good responders group, making their tumors indistinguishable from those of the bad responders in their expression profile (P ≤ 0.05 Benjamini-Hochgerg`s method).

Conclusions

These data identify a set of key molecular pathways selectively up-regulated in post-chemotherapy cancer cells, which may become appropriate targets for the development of future directed therapies against breast cancer.

Because of the high risk of recurrence in high-grade serous ovarian carcinoma (HGS-OvCa), the development of outcome predictors could be valuable for patient stratification. Using the catalog of The Cancer Genome Atlas (TCGA), we developed subtype and survival gene expression signatures, which, when combined, provide a prognostic model of HGS-OvCa classification, named “Classification of Ovarian Cancer” (CLOVAR). We validated CLOVAR on an independent dataset consisting of 879 HGS-OvCa expression profiles. The worst outcome group, accounting for 23% of all cases, was associated with a median survival of 23 months and a platinum resistance rate of 63%, versus a median survival of 46 months and platinum resistance rate of 23% in other cases. Associating the outcome prediction model with BRCA1/BRCA2 mutation status, residual disease after surgery, and disease stage further optimized outcome classification. Ovarian cancer is a disease in urgent need of more effective therapies. The spectrum of outcomes observed here and their association with CLOVAR signatures suggests variations in underlying tumor biology. Prospective validation of the CLOVAR model in the context of additional prognostic variables may provide a rationale for optimal combination of patient and treatment regimens.

The microRNA-200 family restricts epithelial-mesenchymal transition (EMT) and metastasis in tumor cell lines derived from mice that develop metastatic lung adenocarcinoma. To determine the mechanisms responsible for EMT and metastasis regulated by this microRNA, we conducted a global LC-MS/MS analysis to compare metastatic and non-metastatic murine lung adenocarcinoma cells which had undergone EMT due to loss of miR-200. An analysis of syngeneic tumors generated by these cells identified multiple novel proteins linked to metastasis. In particular, the analysis of conditioned media, cell surface proteins, and whole cell lysates from metastatic and non-metastatic cells revealed large scale modifications in the tumor microenvironment. Specific increases were documented in extracellular matrix proteins, peptidases, and changes in distribution of cell adhesion proteins in the metastatic cell lines. Integrating proteomic data from three sub-proteomes, we defined constituents of a multilayer protein network that both regulated and mediated the effects of transforming growth factor TGFβ. Lastly, we identified extracellular matrix proteins and peptidases that were directly regulated by miR-200. Taken together, our results reveal how expression of miR-200 alters the tumor microenvironment to inhibit the processes of EMT and metastasis.

In breast carcinomas, increased levels of insulin-like growth factor 1 (IGF-1) can act as a mitogen to augment tumorigenesis through the regulation of MAPK and AKT signaling pathways. Signaling through these two pathways allows IGF-1 to employ mechanisms that favor proliferation and cellular survival. Here we demonstrate a subset of previously described tumor suppressor and oncogenic microRNAs (miRNAs) that are under the direct regulation of IGF-1 signaling. Additionally, we show that the selective inhibition of either the MAPK or AKT pathways prior to IGF-1 stimulation prevents the expression of previously described tumor suppressor miRNAs that are family and cluster specific. Here we have defined, for the first time, specific miRNAs under the direct regulation of IGF-1 signaling in the estrogen receptor positive MCF-7 breast cancer cell line and demonstrate kinase signaling as a modulator of expression for a small subset of microRNAs. Taken together, these data give new insights into mechanisms governing IGF-1 signaling in breast cancer.

BACKGROUND

Chronic myeloid leukemia (CML) is a clonal stem cell malignancy whose pathogenesis is driven by constitutive activation of the breakpoint cluster region–v-abl Abelson murine leukemia viral oncogene homolog 1 (BCR-ABL1) kinase. Although BCR-ABL1 activation is present in all patients with CML, patients can present in 3 different phases characterized by an increasingly worse prognosis and diminished responsiveness to tyrosine kinase inhibitors: chronic phase, accelerated phase, or blastic phase. The biologic basis for progression from chronic phase to blastic phase and for regulating the homeostasis of tyrosine kinase inhibitor-resistant CML stem cells is not entirely understood.

METHODS

To shed some light into these aspects of CML biology, the authors used reverse phase protein arrays probed with 112 individual monoclonal antibodies to compare protein expression patterns in 40 samples of leukemia-enriched fractions from patients with CML (25 in chronic phase, 5 in accelerated phase, and 10 in phase).

RESULTS

An analysis of variance (significance cutoff, P < .01) unveiled a set of proteins that were overexpressed in blastic phase, including heat-shock protein 90 (hsp90); retinoblastoma (Rb); apoptosis-inducing factor (AIF); serine/threonine-protein phosphatase 2A (PP2A); B-cell leukemia 2 (Bcl-2); X-linked inhibitor of apoptosis protein (Xiap); human homolog of Drosophila Mad (mothers against decapenta-plegic) and related Caenorhabditis elegans gene Sma, family member 1 (Smad1); single-stranded DNA binding protein 2 alpha (SSBP2α); poly(adenosine diphosphate-ribose) polymerase (PARP); GRB2-associated binding protein 2 (Gab2); and tripartite motif containing 24 (Trim24). It is noteworthy that several of these proteins also were overexpressed in the CD34-positive compartment, which putatively contains the CML stem cell population.

CONCLUSIONS

The results from this study indicated that reverse phase protein array analysis can unveil differentially expressed proteins in advanced phase CML that can be exploited therapeutically with targeted approaches.

Prediction of prostate cancer prognosis is challenging and predictive biomarkers of recurrence remain elusive. Although prostate specific antigen (PSA) has high sensitivity (90%) at a PSA level of 4.0 ng/mL, its low specificity leads to many false positive results and considerable overtreatment of patients and its performance at lower ranges is poor. Given the histopathological and molecular heterogeneity of prostate cancer, we propose that a panel of markers will be a better tool than a single marker. We tested a panel of markers composed of the anti-apoptotic protein FLIP and its transcriptional regulators Sp1 and Sp3 using prostate tissues from 64 patients with recurrent and non-recurrent cancer who underwent radical prostatectomy as primary treatment for prostate cancer and were followed with PSA measurements for at least 5 years. Immunohistochemical staining for Sp1, Sp3, and FLIP was performed on these tissues and scored based on the proportion and intensity of staining. The predictive value of the FLIP/Sp1/Sp3 signature for clinical outcome (recurrence vs. non-recurrence) was explored with logistic regression, and combinations of FLIP/Sp1/Sp3 and Gleason score were analyzed with a stepwise (backward and forward) logistic model. The discrimination of the markers was identified by sensitivity-specificity analysis and the diagnostic value of FLIP/Sp1/Sp3 was determined using area under the curve (AUC) for receiver operator characteristic curves. The AUCs for FLIP, Sp1, Sp3, and Gleason score for predicting PSA failure and non-failure were 0.71, 0.66, 0.68, and 0.76, respectively. However, this increased to 0.93 when combined. Thus, the “biomarker signature” of FLIP/Sp1/Sp3 combined with Gleason score predicted disease recurrence and stratified patients who are likely to benefit from more aggressive treatment.

Molecular profiling studies have found that estrogen receptor-positive (ER+) human breast cancers are comprised of at least two distinct diseases with differing biologies. With the advent of DNA microarrays, global gene expression patterns were used to define the luminal A and luminal B subtypes of ER+ breast cancer, with luminal B cancers showing a more aggressive phenotype including substantially worse outcomes in patients. The luminal B subtype designation could be considered a surrogate for those ER+ tumors having low progesterone receptors, high proliferation, high grade, and predicted poor response to hormone therapy. While they express estrogen receptors, luminal B cancers do not show a corresponding expression of estrogen-regulated genes, and may therefore rely upon alternative pathways for growth. At the molecular level, luminal B cancers appear dramatically distinct from luminal A cancers, at the levels of gene expression, gene copy, somatic mutation, and DNA methylation; luminal B cancers are also genetically and genomically altered to a greater extent than luminal A cancers. While, in the clinical setting, luminal B is typically regarded as an ER+, hormone-sensitive disease, more research is needed into how to better treat it. Comprehensive profiling initiatives, such as The Cancer Genome Atlas, have recently provided us a catalog of mutated or copy altered genes, from which new therapeutic targets could potentially be mined. Candidate pathways that might be targeted in luminal B include those involving growth factor receptors, including HER2 and EGFR, as well as PI3K/Akt/mTor.

Next generation sequencing has now enabled a cost-effective enumeration of the full mutational complement of a tumor genome—in particular single nucleotide variants (SNVs). Most current computational and statistical models for analyzing next generation sequencing data, however, do not account for cancer-specific biological properties, including somatic segmental copy number alterations (CNAs)—which require special treatment of the data. Here we present CoNAn-SNV (Copy Number Annotated SNV): a novel algorithm for the inference of single nucleotide variants (SNVs) that overlap copy number alterations. The method is based on modelling the notion that genomic regions of segmental duplication and amplification induce an extended genotype space where a subset of genotypes will exhibit heavily skewed allelic distributions in SNVs (and therefore render them undetectable by methods that assume diploidy). We introduce the concept of modelling allelic counts from sequencing data using a panel of Binomial mixture models where the number of mixtures for a given locus in the genome is informed by a discrete copy number state given as input. We applied CoNAn-SNV to a previously published whole genome shotgun data set obtained from a lobular breast cancer and show that it is able to discover 21 experimentally revalidated somatic non-synonymous mutations in a lobular breast cancer genome that were not detected using copy number insensitive SNV detection algorithms. Importantly, ROC analysis shows that the increased sensitivity of CoNAn-SNV does not result in disproportionate loss of specificity. This was also supported by analysis of a recently published lymphoma genome with a relatively quiescent karyotype, where CoNAn-SNV showed similar results to other callers except in regions of copy number gain where increased sensitivity was conferred. Our results indicate that in genomically unstable tumors, copy number annotation for SNV detection will be critical to fully characterize the mutational landscape of cancer genomes.

Background

Long noncoding RNAs (lncRNAs) are an important class of pervasive genes involved in a variety of biological functions. They are aberrantly expressed in many types of cancers. In this study, we described lncRNAs profiles in 6 pairs of human renal clear cell carcinoma (RCCC) and the corresponding adjacent nontumorous tissues (NT) by microarray.

Methodology/Principal Findings

With abundant and varied probes accounting 33,045 LncRNAs in our microarray, the number of lncRNAs that expressed at a certain level could be detected is 17157. From the data we found there were thousands of lncRNAs that differentially expressed (≥2 fold-change) in RCCC tissues compared with NT and 916 lncRNAs differentially expressed in five or more of six RCCC samples. Compared with NT, many lncRNAs were significantly up-regulated or down-regulated in RCCC. Our data showed that down-regulated lncRNAs were more common than up-regulated ones. ENST00000456816, X91348, BC029135, NR_024418 were evaluated by qPCR in sixty-three pairs of RCCC and NT samples. The four lncRNAs were aberrantly expressed in RCCC compared with matched histologically normal renal tissues.

Conclusions/Significance

Our study is the first one to determine genome-wide lncRNAs expression patterns in RCCC by microarray. The results displayed that clusters of lncRNAs were aberrantly expressed in RCCC compared with NT samples, which revealed that lncRNAs differentially expressed in tumor tissues and normal tissues may exert a partial or key role in tumor development. Taken together, this study may provide potential targets for future treatment of RCCC and novel insights into cancer biology.

Biomarkers are needed to address overtreatment that occurs for the majority of prostate cancer patients that would not die of the disease but receive radical treatment. A possible barrier to biomarker discovery may be the polyclonal/multifocal nature of prostate tumors as well as cell-type heterogeneity between patient samples. Tumor-adjacent stroma (tumor microenvironment) is less affected by genetic alteration and might therefore yield more consistent biomarkers in response to tumor aggressiveness. To this end we compared Affymetrix gene expression profiles in stroma near tumor and identified a set of 115 probe sets for which the expression levels were significantly correlated with time-to-relapse. We also compared patients that chemically relapsed shortly after prostatectomy (<1 year), and patients that did not relapse in the first four years after prostatectomy. We identified 131 differentially expressed microarray probe sets between these two categories. 19 probe sets (15 genes overlapped between the two gene lists with p<0.0001). We developed a PAM-based classifier by training on samples containing stroma near tumor: 9 rapid relapse patient samples and 9 indolent patient samples. We then tested the classifier on 47 different samples, containing 90% or more stroma. The classifier predicted the risk status of patients with an average accuracy of 87%. This is the first general tumor microenvironment-based prognostic classifier. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for predicting outcomes for patients.

Metastatic cancer is extremely difficult to treat, and the presence of metastases greatly reduces a cancer patient’s likelihood of long-term survival. The ZEB1 transcriptional repressor promotes metastasis through downregulation of microRNAs (miRs) that are strong inducers of epithelial differentiation and inhibitors of stem cell factors. Given that each miR can target multiple genes with diverse functions, we posited that the prometastatic network controlled by ZEB1 extends beyond these processes. We tested this hypothesis using a mouse model of human lung adenocarcinoma metastasis driven by ZEB1, human lung carcinoma cells, and human breast carcinoma cells. Transcriptional profiling studies revealed that ZEB1 controls the expression of numerous oncogenic and tumor-suppressive miRs, including miR-34a. Ectopic expression of miR-34a decreased tumor cell invasion and metastasis, inhibited the formation of promigratory cytoskeletal structures, suppressed activation of the RHO GTPase family, and regulated a gene expression signature enriched in cytoskeletal functions and predictive of outcome in human lung adenocarcinomas. We identified several miR-34a target genes, including Arhgap1, which encodes a RHO GTPase activating protein that was required for tumor cell invasion. These findings demonstrate that ZEB1 drives prometastatic actin cytoskeletal remodeling by downregulating miR-34a expression and provide a compelling rationale to develop miR-34a as a therapeutic agent in lung cancer patients.

Pregnancy-induced noncoding RNA (PINC) and retinoblastoma-associated protein 46 (RbAp46) are upregulated in alveolar cells of the mammary gland during pregnancy and persist in alveolar cells that remain in the regressed lobules following involution. The cells that survive involution are thought to function as alveolar progenitor cells that rapidly differentiate into milk-producing cells in subsequent pregnancies, but it is unknown whether PINC and RbAp46 are involved in maintaining this progenitor population. Here, we show that, in the post-pubertal mouse mammary gland, mPINC is enriched in luminal and alveolar progenitors. mPINC levels increase throughout pregnancy and then decline in early lactation, when alveolar cells undergo terminal differentiation. Accordingly, mPINC expression is significantly decreased when HC11 mammary epithelial cells are induced to differentiate and produce milk proteins. This reduction in mPINC levels may be necessary for lactation, as overexpression of mPINC in HC11 cells blocks lactogenic differentiation, while knockdown of mPINC enhances differentiation. Finally, we demonstrate that mPINC interacts with RbAp46, as well as other members of the polycomb repressive complex 2 (PRC2), and identify potential targets of mPINC that are differentially expressed following modulation of mPINC expression levels. Taken together, our data suggest that mPINC inhibits terminal differentiation of alveolar cells during pregnancy to prevent abundant milk production and secretion until parturition. Additionally, a PRC2 complex that includes mPINC and RbAp46 may confer epigenetic modifications that maintain a population of mammary epithelial cells committed to the alveolar fate in the involuted gland.

Author Summary

During pregnancy, epithelial cells of the mammary gland begin to undergo differentiation into functional alveolar cells that, during lactation, will produce and secrete milk proteins, thereby providing nourishment to offspring. Following lactation, the majority of alveolar cells die and the mammary gland remodels to a pre-pregnancy-like state in a process called involution. However, some alveolar cells survive involution, and these cells are thought to serve as alveolar progenitors that are able to rapidly proliferate and differentiate into milk-producing cells in subsequent pregnancies. Keeping alveolar cells from undergoing terminal differentiation during pregnancy and involution is vital for the preservation of an alveolar progenitor population. Here, we show that the long noncoding RNA, PINC, is downregulated in the mammary gland between late pregnancy and early lactation, when alveolar cells begin to terminally differentiate. This reduction of PINC levels may be necessary for lactation, as overexpression of PINC inhibits differentiation, while knockdown of PINC enhances differentiation of mammary epithelial cells. Finally, we find that PINC interacts with the chromatin-modifying complex PRC2, suggesting epigenetic regulation may be involved in maintaining alveolar progenitors in the pregnant and involuting mammary gland. These results emphasize the potential importance of lncRNA-PRC2 involvement in regulating cell fate during development.

Background

To improve the quality of life of colorectal cancer patients, it is important to establish new screening methods for early diagnosis of colorectal cancer.

Methodology/Principal Findings

We performed serum metabolome analysis using gas-chromatography/mass-spectrometry (GC/MS). First, the accuracy of our GC/MS-based serum metabolomic analytical method was evaluated by calculating the RSD% values of serum levels of various metabolites. Second, the intra-day (morning, daytime, and night) and inter-day (among 3 days) variances of serum metabolite levels were examined. Then, serum metabolite levels were compared between colorectal cancer patients (N = 60; N = 12 for each stage from 0 to 4) and age- and sex-matched healthy volunteers (N = 60) as a training set. The metabolites whose levels displayed significant changes were subjected to multiple logistic regression analysis using the stepwise variable selection method, and a colorectal cancer prediction model was established. The prediction model was composed of 2-hydroxybutyrate, aspartic acid, kynurenine, and cystamine, and its AUC, sensitivity, specificity, and accuracy were 0.9097, 85.0%, 85.0%, and 85.0%, respectively, according to the training set data. In contrast, the sensitivity, specificity, and accuracy of CEA were 35.0%, 96.7%, and 65.8%, respectively, and those of CA19-9 were 16.7%, 100%, and 58.3%, respectively. The validity of the prediction model was confirmed using colorectal cancer patients (N = 59) and healthy volunteers (N = 63) as a validation set. At the validation set, the sensitivity, specificity, and accuracy of the prediction model were 83.1%, 81.0%, and 82.0%, respectively, and these values were almost the same as those obtained with the training set. In addition, the model displayed high sensitivity for detecting stage 0–2 colorectal cancer (82.8%).

Conclusions/Significance

Our prediction model established via GC/MS-based serum metabolomic analysis is valuable for early detection of colorectal cancer and has the potential to become a novel screening test for colorectal cancer.

Purpose

Increased expression of FGFR-4 and its ligands have been linked to lethal prostate cancer (PCa). Furthermore, a germline polymorphism in the FGFR-4 gene, resulting in arginine at codon 388 (Arg388) instead of glycine (Gly388), is associated with aggressive disease. The FGFR-4 Arg388 variant results in increased receptor stability, sustained receptor activation and increased motility and invasion compared to Gly388. However, the impact of sustained signaling on cellular signal transduction pathways is unknown.

Experimental Design

Expression microarray analysis of immortalized prostatic epithelial cells lines expressing FGFR-4 Arg388 or Gly388 was used to establish a gene signature associated with FGFR-4 Arg388 expression. Transient transfection of reporters and inhibitors were used to establish the pathways activated by FGFR-4 Arg388 expression. The impact of pathway knockdown in vitro and in an orthotopic model was assessed using inhibitors and/or shRNA.

Results

Expression of the FGFR-4 Arg388 protein leads to increased activity of the extracellular signal-related kinase (ERK) pathway, increased activity of serum response factor (SRF) and AP1 and transcription of multiple genes which are correlated with aggressive clinical behavior in PCa. Increased expression of SRF is associated with biochemical recurrence in men undergoing radical prostatectomy. Consistent with these observations, knockdown of FGFR-4 Arg388 in PCa cells decreases proliferation and invasion in vitro and primary tumor growth and metastasis in vivo.

Conclusions

These studies define a signal transduction pathway downstream of FGFR-4 Arg388 that acts via ERK and SRF to promote prostate cancer progression.

MicroRNAs (miRNAs), non-coding RNAs regulating gene expression, are frequently aberrantly expressed in human cancers. Next-generation deep sequencing technology enables genome-wide expression profiling of known miRNAs and discovery of novel miRNAs at unprecedented quantitative and qualitative accuracy. Deep sequencing was performed on 11 fresh frozen clear cell renal cell carcinoma (ccRCC) and adjacent non-tumoral renal cortex (NRC) pairs, 11 additional frozen ccRCC tissues, and 2 ccRCC cell lines (n = 35). The 22 ccRCCs patients belonged to 3 prognostic sub-groups, i.e. those without disease recurrence, with recurrence and with metastatic disease at diagnosis. Thirty-two consecutive samples (16 ccRCC/NRC pairs) were used for stem-loop PCR validation. Novel miRNAs were predicted using 2 distinct bioinformatic pipelines. In total, 463 known miRNAs (expression frequency 1–150,000/million) were identified. We found that 100 miRNA were significantly differentially expressed between ccRCC and NRC. Differential expression of 5 miRNAs was confirmed by stem-loop PCR in the 32 ccRCC/NRC samples. With respect to RCC subgroups, 5 miRNAs discriminated between non-recurrent versus recurrent and metastatic disease, whereas 12 uniquely distinguished non-recurrent versus metastatic disease. Blocking overexpressed miR-210 or miR-27a in cell line SKCR-7 by transfecting specific antagomirs did not result in significant changes in proliferation or apoptosis. Twenty-three previously unknown miRNAs were predicted in silico. Quantitative genome-wide miRNA profiling accurately separated ccRCC from (benign) NRC. Individual differentially expressed miRNAs may potentially serve as diagnostic or prognostic markers or future therapeutic targets in ccRCC. The biological relevance of candidate novel miRNAs is unknown at present.

Background

To investigate the frequency and relationship of the KRAS, BRAF and PIK3CA mutations and the loss of PTEN expression in Chinese patients with colorectal cancer (CRC).

Methodology/Principal Findings

Genomic DNA was extracted from the formalin-fixed paraffin-embedded (FFPE) tissues of 69 patients with histologically confirmed CRC. Automated sequencing analysis was conducted to detect mutations in the KRAS (codons 12, 13, and 14), BRAF (codon 600) and PIK3CA (codons 542, 545 and 1047). PTEN protein expression was evaluated by immunohistochemistry on 3 mm FFPE tissue sections. Statistical analysis was carried out using SPSS 16.0 software. The frequency of KRAS, BRAF and PIK3CA mutations and loss of PTEN expression was 43.9% (25/57), 25.4% (15/59), 8.2% (5/61) and 47.8% (33/69), respectively. The most frequent mutation in KRAS, BRAF and PIK3CA was V14G (26.7% of all mutations), V600E (40.0% of all mutations) and V600L (40.0% of all mutations), and H1047L (80.0% of all mutations), respectivly. Six KRAS mutatant patients (24.0%) harbored BRAF mutations. BRAF and PIK3CA mutations were mutually exclusive. No significant correlation was observed between the four biomarkers and patients' characteristics.

Conclusions/Significance

BRAF mutation rate is much higher in this study than in other studies, and overlap a lot with KRAS mutations. Besides, the specific types of KRAS and PIK3CA mutations in Chinese patients could be quite different from that of patients in other countries. Further studies are warranted to examine their impact on prognosis and response to targeted treatment.

MAP2K4 encodes a dual-specificity kinase (mitogen-activated protein kinase kinase 4, or MKK4) that is mutated in a variety of human malignancies, but the biochemical properties of the mutant kinases and their roles in tumorigenesis have not been fully elucidated. Here we showed that 8 out of 11 cancer-associated MAP2K4 mutations reduce MKK4 protein stability or impair its kinase activity. On the basis of findings from bioinformatic studies on human cancer cell lines with homozygous MAP2K4 loss, we posited that MKK4 functions as a tumor suppressor in lung adenocarcinomas that develop in mice owing to expression of mutant Kras and Tp53. Conditional Map2k4 inactivation in the bronchial epithelium of mice had no discernible effect alone but increased the multiplicity and accelerated the growth of incipient lung neoplasias induced by oncogenic Kras. MKK4 suppressed the invasion and metastasis of Kras-Tp53-mutant lung adenocarcinoma cells. MKK4 deficiency increased peroxisomal proliferator-activated receptor γ2 (PPARγ2) expression through noncanonical MKK4 substrates, and PPARγ2 enhanced tumor cell invasion. We conclude that Map2k4 functions as a tumor suppressor in lung adenocarcinoma and inhibits tumor cell invasion by decreasing PPARγ2 levels.

Progenitor cells are thought to be an important cell of origin of human malignancies. However, there has not been any single gene that can define mammary bipotential progenitor cells, and as such it has not been possible to use genetic methods to introduce oncogenic alterations into these cells in vivo to study tumorigenesis from them. Keratin 6a is expressed in a subset of mammary luminal epithelial cells and body cells of terminal end buds. By generating transgenic mice using the Keratin 6a (K6a) gene promoter to express tva, which encodes the receptor for avian leukosis virus subgroup A (ALV/A), we provide direct evidence that K6a+ cells are bipotential progenitor cells. These K6a+ cells were readily induced to form mammary tumors by intraductal injection of RCAS (an ALV/A-derived vector) carrying the gene encoding the polyoma middle T antigen. Tumors in this K6a-tva line were unique in that they resemble the normal breast-like subtype of human breast cancer, providing a model for preclinical testing of targeted therapy for patients with normal-like breast cancers. These observations also provide direct in vivo evidence for the hypothesis that the cell of origin affects mammary tumor phenotypes.

Purpose

We previously reported an IGF gene expression signature, based upon genes induced or repressed by IGF-I, which correlated with poor prognosis in breast cancer. We tested if the IGF signature was affected by anti-IGF-IR inhibitors, and if the IGF signature correlated with response to a dual anti-IGF-IR/InsR inhibitor BMS-754807.

Experimental Design

An IGF gene expression signature was examined in human breast tumors and cell lines, and changes noted following treatment of cell lines or xenografts with anti-IGF-IR antibodies or tyrosine kinase inhibitors. Sensitivity of cells to BMS-754807 was correlated with levels of the IGF signature. Human primary tumorgrafts were analyzed for the IGF signature and IGF-IR levels and activity, and MC1 tumorgrafts treated with BMS-754807 and chemotherapy.

Results

The IGF gene expression signature was reversed in three different models (cancer cell lines or xenografts) treated with three different anti-IGF-IR therapies. The IGF signature was present in triple-negative breast cancers (TNBC) and TNBC cell lines. TNBC cell lines were especially sensitive to BMS-754807, and sensitivity was significantly correlated to expression of the IGF gene signature. The TNBC primary human tumorgraft MC1 showed high levels of both IGF-IR expression and activity, and IGF gene signature score. Treatment of MC1 with BMS-754807 showed growth inhibition and in combination with docetaxel tumor regression occurred until no tumor was palpable. Regression was associated with reduced proliferation, increased apoptosis, and mitotic catastrophe.

Conclusion

These studies provide a clear biological rationale to test anti-IGF-IR/InsR therapy in combination with chemotherapy in patients with TNBC.

Background

The Cancer Genome Atlas (TCGA) Network recently comprehensively catalogued the molecular aberrations in 487 high-grade serous ovarian cancers, with much remaining to be elucidated regarding the microRNAs (miRNAs). Here, using TCGA ovarian data, we surveyed the miRNAs, in the context of their predicted gene targets.

Methods and Results

Integration of miRNA and gene patterns yielded evidence that proximal pairs of miRNAs are processed from polycistronic primary transcripts, and that intronic miRNAs and their host gene mRNAs derive from common transcripts. Patterns of miRNA expression revealed multiple tumor subtypes and a set of 34 miRNAs predictive of overall patient survival. In a global analysis, miRNA:mRNA pairs anti-correlated in expression across tumors showed a higher frequency of in silico predicted target sites in the mRNA 3′-untranslated region (with less frequency observed for coding sequence and 5′-untranslated regions). The miR-29 family and predicted target genes were among the most strongly anti-correlated miRNA:mRNA pairs; over-expression of miR-29a in vitro repressed several anti-correlated genes (including DNMT3A and DNMT3B) and substantially decreased ovarian cancer cell viability.

Conclusions

This study establishes miRNAs as having a widespread impact on gene expression programs in ovarian cancer, further strengthening our understanding of miRNA biology as it applies to human cancer. As with gene transcripts, miRNAs exhibit high diversity reflecting the genomic heterogeneity within a clinically homogeneous disease population. Putative miRNA:mRNA interactions, as identified using integrative analysis, can be validated. TCGA data are a valuable resource for the identification of novel tumor suppressive miRNAs in ovarian as well as other cancers.

Here we presented that the expression of RUNX3 was significantly decreased in 75 cases of clear cell renal cell carcinoma (CCRCC) tissues (p<0.05). Enforced RUNX3 expression mediated 786-O cells to exhibit inhibition of growth, G1 cell-cycle arrest and metastasis in vitro, and to lost tumorigenicity in nude mouse model in vivo. RUNX3-induced growth suppression was found partially to regulate various proteins, including inhibition of cyclinD1, cyclinE, cdk2, cdk4 and p-Rb, but increase of p27Kip1, Rb and TIMP-1. Therefore, RUNX3 had the function of inhibiting the proliferative and metastatic abilities of CCRCC cells by regulating cyclins and TIMP1.

Objective

Trastuzumab has been used for the treatment of HER2-positive breast cancer (BC). However, a subset of BC patients exhibited resistance to trastuzumab therapy. Thus, clarifying the molecular mechanism of trastuzumab treatment will be beneficial to improve the treatment of HER2-positive BC patients. In this study, we identified trastuzumab-responsive microRNAs that are involved in the therapeutic effects of trastuzumab.

Methods and Results

RNA samples were obtained from HER2-positive (SKBR3 and BT474) and HER2-negetive (MCF7 and MDA-MB-231) cells with and without trastuzumab treatment for 6 days. Next, we conducted a microRNA profiling analysis using these samples to screen those microRNAs that were up- or down-regulated only in HER2-positive cells. This analysis identified miR-26a and miR-30b as trastuzumab-inducible microRNAs. Transfecting miR-26a and miR-30b induced cell growth suppression in the BC cells by 40% and 32%, respectively. A cell cycle analysis showed that these microRNAs induced G1 arrest in HER2-positive BC cells as trastuzumab did. An Annexin-V assay revealed that miR-26a but not miR-30b induced apoptosis in HER2-positive BC cells. Using the prediction algorithms for microRNA targets, we identified cyclin E2 (CCNE2) as a target gene of miR-30b. A luciferase-based reporter assay demonstrated that miR-30b post-transcriptionally reduced 27% (p = 0.005) of the gene expression by interacting with two binding sites in the 3′-UTR of CCNE2.

Conclusion

In BC cells, trastuzumab modulated the expression of a subset of microRNAs, including miR-26a and miR-30b. The upregulation of miR-30b by trastuzumab may play a biological role in trastuzumab-induced cell growth inhibition by targeting CCNE2.

The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. Meta-analyses of several established prognostic breast cancer gene expression profiles in large patient cohorts have demonstrated that despite sharing few genes, their delineation of patients into “good prognosis” or “poor prognosis” are frequently very highly correlated, and combining prognostic profiles does not increase prognostic power. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Microarray gene expression data from an initial training cohort of 72 breast cancer patients for which CTC status had been determined in a previous study using a multimarker QPCR-based assay was used to develop a CTC-predictive profile. The generated profile was validated in two independent datasets of 49 and 123 patients and confirmed to be both predictive of CTC status, and independently prognostic. Importantly, the “CTC profile” also provided prognostic information independent of the well-established and powerful ‘70-gene’ prognostic breast cancer signature. This profile therefore has the potential to not only add prognostic information to currently-available microarray tests but in some circumstances even replace blood-based prognostic CTC tests at time of diagnosis for those patients already undergoing testing by multigene assays.

Ovarian cancer is the fifth leading cause of cancer death for women in the U.S. and the seventh most fatal worldwide. Although ovarian cancer is notable for its initial sensitivity to platinum-based therapies, the vast majority of patients eventually develop recurrent cancer and succumb to increasingly platinum-resistant disease. Modern, targeted cancer drugs intervene in cell signaling, and identifying key disease mechanisms and pathways would greatly advance our treatment abilities. In order to shed light on the molecular diversity of ovarian cancer, we performed comprehensive transcriptional profiling on 129 advanced stage, high grade serous ovarian cancers. We implemented a, re-sampling based version of the ISIS class discovery algorithm (rISIS: robust ISIS) and applied it to the entire set of ovarian cancer transcriptional profiles. rISIS identified a previously undescribed patient stratification, further supported by micro-RNA expression profiles, and gene set enrichment analysis found strong biological support for the stratification by extracellular matrix, cell adhesion, and angiogenesis genes. The corresponding “angiogenesis signature” was validated in ten published independent ovarian cancer gene expression datasets and is significantly associated with overall survival. The subtypes we have defined are of potential translational interest as they may be relevant for identifying patients who may benefit from the addition of anti-angiogenic therapies that are now being tested in clinical trials.

Ovarian cancer is a complex and deadly disease that remains difficult to detect at an early curable stage. Furthermore, although some oncogenic (Kras, Pten/PI3K and Trp53) pathways that are frequently mutated, deleted or amplified in ovarian cancer are known, how these pathways initiate and drive specific morphological phenotypes and tumor outcomes remain unclear. We recently generated Pten fl/fl; KrasG12D;Amhr2-Cre mice to disrupt the Pten gene and express a stable mutant form of KrasG12D in ovarian surface epithelial (OSE) cells. Based on histopathologic criteria, the mutant mice developed low-grade ovarian serous papillary adenocarcinomas at an early age and with 100% penetrance. This highly reproducible phenotype provides the first mouse model in which to study this ovarian cancer subtype. OSE cells isolated from ovaries of mutant mice at 5 and 10 weeks of age exhibit temporal changes in the expression of specific Mullerian epithelial marker genes, grow in soft agar and develop ectopic invasive tumors in recipient mice, indicating that the cells are transformed. Gene profiling identified specific mRNAs and microRNAs differentially expressed in purified OSE cells derived from tumors of the mutant mice compared to WT OSE cells. Mapping of transcripts or genes between the mouse OSE mutant datasets, the Kras signature from human cancer cell lines and the human ovarian tumor array datasets, documented significant overlap, indicating that KRAS is a key driver of OSE transformation in this context. Two key hallmarks of the mutant OSE cells in these mice are the elevated expression of the tumor suppressorsTrp53 (p53) and its microRNA target, miR-34a-c. We propose that elevated TRP53 and miR-34a-c may exert negatively regulatory effects that reduce the proliferative potential of OSE cells leading to the low-grade serous adenocarcinoma phenotype.