Complete tumor necrosis after neoadjuvant chemotherapy defines good responders in patients with Ewing sarcoma.

BACKGROUND: Survival in patients who have Ewing sarcoma is correlated with postchemotherapy response (tumor necrosis). This treatment response has been categorized as the response rate, similar to what has been used in osteosarcoma. There is controversy regarding whether this is appropriate or whether it should be a dichotomy of complete versus incomplete response, given how important a complete response is for in overall survival of patients with Ewing sarcoma. The purpose of this study was to evaluate the impact that the amount of chemotherapy-induced necrosis has on (1) overall survival, (2) local recurrence-free survival, (3) metastasis-free survival, and (4) event-free survival in patients with Ewing sarcoma. METHODS: In total, 427 patients who had Ewing sarcoma or tumors in the Ewing sarcoma family and received treatment with preoperative chemotherapy and surgery at 10 international institutions were included. Multivariate Cox proportional-hazards analyses were used to assess the associations between tumor necrosis and all four outcomes while controlling for clinical factors identified in bivariate analysis, including age, tumor volume, location, surgical margins, metastatic disease at presentation, and preoperative radiotherapy. RESULTS: Patients who had a complete (100%) tumor response to chemotherapy had increased overall survival (hazard ratio [HR], 0.26; 95% CI, 0.14-0.48; p < .01), recurrence-free survival (HR, 0.40; 95% CI, 0.20-0.82; p = .01), metastasis-free survival (HR, 0.27; 95% CI, 0.15-0.46; p ≤ .01), and event-free survival (HR, 0.26; 95% CI, 0.16-0.41; p ≤ .01) compared with patients who had a partial (0%-99%) response. CONCLUSIONS: Complete tumor necrosis should be the index parameter to grade response to treatment as satisfactory in patients with Ewing sarcoma. Any viable tumor in these patients after neoadjuvant treatment should be of oncologic concern. These findings can affect the design of new clinical trials and the risk-stratified application of conventional or novel treatments.

Clinical and Molecular Analysis of Pathologic Fracture-associated Osteosarcoma: MicroRNA profile Is Different and Correlates with Prognosis.

BACKGROUND: MicroRNAs are small, noncoding RNAs that regulate the expression of posttranslational genes. The presence of some specific microRNAs has been associated with increased risk of both local recurrence and metastasis and worse survival in patients with osteosarcoma. Pathologic fractures in osteosarcoma are considered to be more the manifestation of a neoplasm with a more aggressive biological behavior than the cause itself of worse prognosis. However, this has not been proved at the biological or molecular level. Currently, there has not been a microRNA profiling study of patients who have osteosarcoma with and without pathologic fractures that has described differences in terms of microRNA profiling between these two groups and their correlation with biologic behavior. QUESTIONS/PURPOSES: (1) In patients with osteosarcoma of the extremities, how do the microRNA profiles of those with and without pathologic fractures compare? (2) What relationship do microRNAs have with local recurrence, risk of metastasis, disease-specific survival, and overall survival in osteosarcoma patients with pathologic fractures? METHODS: Between 1994 and 2013, 217 patients were diagnosed and treated at our institution for osteosarcoma of the extremities. Patients were excluded if (1) they underwent oncologic resection of the osteosarcoma at an outside institution (two patients) or (2) they were diagnosed with an extraskeletal osteosarcoma (29 patients) or (3) they had less than 1 year of clinical follow-up and no oncologic outcome (local recurrence, metastasis, or death) (four patients). A total of 182 patients were eligible. Of those, 143 were high-grade osteosarcomas. After evaluation of tumor samples before chemotherapy treatment, a total of 80 consecutive samples were selected for sequencing. Demographic and clinical comparison between the sequenced and non-sequenced patients did not demonstrate any differences, confirming that both groups were comparable. Diagnostic samples from the extremities of 80 patients with high-grade extremity osteosarcomas who had not yet received chemotherapy underwent microRNA sequencing for an ongoing large-scale osteosarcoma genome profiling project at our institution. Six samples were removed after a second look by a musculoskeletal pathologist who verified cellularity and quality of samples to be sequenced, leaving a total of 74 patients. Of these, two samples were removed as they were confirmed to be pelvic tumors in a second check after sequencing. The final study sample was 72 patients (11 patients with pathologic fractures and 61 without). Sequencing data were correlated with fractures and local recurrence, risk of metastasis, disease-specific survival, and overall survival through Kaplan-Meier analyses. RESULTS: Several microRNAs were expressed differently between the two groups. Among the markers with the highest differential expression (edgeR and DESeq algorithms), Hsa-mIR 656-3p, hsa-miR 493-5p, and hsa-miR 381-3p were upregulated in patients with pathologic fractures, whereas hsa-miR 363, hsa-miR 885-5p, and has-miR 20b-5p were downregulated. The highest differential expression fracture and nonfracture-associated microRNA markers also distinguished groups of patients with different metastasis risk, a well as different disease-specific and overall survival. Furthermore, the profile of pathologic fractures demonstrated a higher differential expression for microRNA markers that were previously associated with a higher risk of metastasis and lower survival rates in patients with osteosarcoma. CONCLUSIONS: In patients who have osteosarcoma, the microRNA profiles of those with pathologic fractures are different than of patients without pathologic fractures. The highest differential expression mircroRNA molecules in patients with pathologic fractures predict also higher risk of metastatic disease as well as worse disease-specific survival and overall survival. Furthermore, we found higher differential expression of microRNAs in the pathologic fracture group previously associated with poor prognosis. The higher risk of metastasis and poorer overall survival in patients with pathologic fractures is inherent to tumor aggressive biologic behavior. It is plausible that the fracture itself is not the direct cause of worse prognosis but another manifestation of tumor biologic aggressiveness. Identification of these molecules through liquid biopsies may help to determine which patients may benefit from surgery before fractures occur. The same technology can be applied to identify patterns of response to conventional chemotherapy, assisting in more specific and accurate systemic therapy. LEVEL OF EVIDENCE LEVEL: III, prognostic study.

A network model for angiogenesis in ovarian cancer.

BACKGROUND: We recently identified two robust ovarian cancer subtypes, defined by the expression of genes involved in angiogenesis, with significant differences in clinical outcome. To identify potential regulatory mechanisms that distinguish the subtypes we applied PANDA, a method that uses an integrative approach to model information flow in gene regulatory networks. RESULTS: We find distinct differences between networks that are active in the angiogenic and non-angiogenic subtypes, largely defined by a set of key transcription factors that, although previously reported to play a role in angiogenesis, are not strongly differentially-expressed between the subtypes. Our network analysis indicates that these factors are involved in the activation (or repression) of different genes in the two subtypes, resulting in differential expression of their network targets. Mechanisms mediating differences between subtypes include a previously unrecognized pro-angiogenic role for increased genome-wide DNA methylation and complex patterns of combinatorial regulation. CONCLUSIONS: The models we develop require a shift in our interpretation of the driving factors in biological networks away from the genes themselves and toward their interactions. The observed regulatory changes between subtypes suggest therapeutic interventions that may help in the treatment of ovarian cancer.

Next-generation sequencing and microarray-based interrogation of microRNAs from formalin-fixed, paraffin-embedded tissue: preliminary assessment of cross-platform concordance.

Next-generation sequencing is increasingly employed in biomedical investigations. Strong concordance between microarray and mRNA-seq levels has been reported in high quality specimens but information is lacking on formalin-fixed, paraffin-embedded (FFPE) tissues, and particularly for microRNA (miRNA) analysis. We conducted a preliminary examination of the concordance between miRNA-seq and cDNA-mediated annealing, selection, extension, and ligation (DASL) miRNA assays. Quantitative agreement between platforms is moderate (Spearman correlation 0.514-0.596) and there is discordance of detection calls on a subset of miRNAs. Quantitative PCR (q-RT-PCR) performed for several discordant miRNAs confirmed the presence of most sequences detected by miRNA-seq but not by DASL but also that miRNA-seq did not detect some sequences, which DASL confidently detected. Our results suggest that miRNA-seq is specific, with few false positive calls, but it may not detect certain abundant miRNAs in FFPE tissue. Further work is necessary to fully address these issues that are pertinent for translational research.

A dynamic microRNA profile that tracks a chemotherapy resistance phenotype in osteosarcoma. Implications for novel therapeutics.

Osteosarcoma is a rare primary bone tumor for which no significant therapeutic advancement has been made since the late 1980s despite ongoing efforts. Overall, the five-year survival rate remains about 65%, and is much lower in patients with tumors unresponsive to methotrexate, doxorubicin, and cisplatin therapy. Genetic studies have not revealed actionable drug targets, but our group, and others, have reported that epigenomic biomarkers, including regulatory RNAs, may be useful prognostic tools for osteosarcoma. We tested if microRNA (miRNA) transcriptional patterns mark the transition from a chemotherapy sensitive to resistant tumor phenotype. Small RNA sequencing was performed using 14 patient matched pre-chemotherapy biopsy and post-chemotherapy resection high-grade osteosarcoma frozen tumor samples. Independently, small RNA sequencing was performed using 14 patient matched biopsy and resection samples from untreated tumors. Separately, miRNA specific Illumina DASL arrays were used to assay an independent cohort of 65 pre-chemotherapy biopsy and 26 patient matched post-chemotherapy resection formalin fixed paraffin embedded (FFPE) tumor samples. mRNA specific Illumina DASL arrays were used to profile 37 pre-chemotherapy biopsy and five post-chemotherapy resection FFPE samples, all of which were also used for Illumina DASL miRNA profiling. The National Cancer Institute Therapeutically Applicable Research to Generate Effective Treatments dataset, including PCR based miRNA profiling and RNA-seq data for 86 and 93 pre-chemotherapy tumor samples, respectively, was also used. Paired differential expression testing revealed a profile of 17 miRNAs with significantly different transcriptional levels following chemotherapy. Genes targeted by the miRNAs were differentially expressed following chemotherapy, suggesting the miRNAs may regulate transcriptional networks. Finally, an in vitro pharmacogenomic screen using miRNAs and their target transcripts predicted response to a set of candidate small molecule therapeutics which potentially reverse the chemotherapy resistance phenotype and synergize with chemotherapy in otherwise treatment resistant tumors. Importantly, these novel therapeutic targets are distinct from targets identified by a similar pharmacogenomic analysis of previously published prognostic miRNA profiles from pre chemotherapy biopsy specimens.

A microRNA activity map of human mesenchymal tumors: connections to oncogenic pathways; an integrative transcriptomic study.

BACKGROUND: MicroRNAs (miRNAs) are nucleic acid regulators of many human mRNAs, and are associated with many tumorigenic processes. miRNA expression levels have been used in profiling studies, but some evidence suggests that expression levels do not fully capture miRNA regulatory activity. In this study we integrate multiple gene expression datasets to determine miRNA activity patterns associated with cancer phenotypes and oncogenic pathways in mesenchymal tumors - a very heterogeneous class of malignancies. RESULTS: Using a computational method, we identified differentially activated miRNAs between 77 normal tissue specimens and 135 sarcomas and we validated many of these findings with microarray interrogation of an independent, paraffin-based cohort of 18 tumors. We also showed that miRNA activity is imperfectly correlated with miRNA expression levels. Using next-generation miRNA sequencing we identified potential base sequence alterations which may explain differential activity. We then analyzed miRNA activity changes related to the RAS-pathway and found 21 miRNAs that switch from silenced to activated status in parallel with RAS activation. Importantly, nearly half of these 21 miRNAs were predicted to regulate integral parts of the miRNA processing machinery, and our gene expression analysis revealed significant reductions of these transcripts in RAS-active tumors. These results suggest an association between RAS signaling and miRNA processing in which miRNAs may attenuate their own biogenesis. CONCLUSIONS: Our study represents the first gene expression-based investigation of miRNA regulatory activity in human sarcomas, and our findings indicate that miRNA activity patterns derived from integrated transcriptomic data are reproducible and biologically informative in cancer. We identified an association between RAS signaling and miRNA processing, and demonstrated sequence alterations as plausible causes for differential miRNA activity. Finally, our study highlights the value of systems level integrative miRNA/mRNA assessment with high-throughput genomic data, and the applicability of paraffin-tissue-derived RNA for validation of novel findings.

Genome-wide DNA methylation patterns reveal clinically relevant predictive and prognostic subtypes in human osteosarcoma.

Aberrant methylation of genomic DNA has been reported in many cancers. Specific DNA methylation patterns have been shown to provide clinically useful prognostic information and define molecular disease subtypes with different response to therapy and long-term outcome. Osteosarcoma is an aggressive malignancy for which approximately half of tumors recur following standard combined surgical resection and chemotherapy. No accepted prognostic factor save tumor necrosis in response to adjuvant therapy currently exists, and traditional genomic studies have thus far failed to identify meaningful clinical associations. We studied the genome-wide methylation state of primary tumors and tested how they predict patient outcomes. We discovered relative genomic hypomethylation to be strongly predictive of response to standard chemotherapy. Recurrence and survival were also associated with genomic methylation, but through more site-specific patterns. Furthermore, the methylation patterns were reproducible in three small independent clinical datasets. Downstream transcriptional, in vitro, and pharmacogenomic analysis provides insight into the clinical translation of the methylation patterns. Our findings suggest the assessment of genomic methylation may represent a strategy for stratifying patients for the application of alternative therapies.

Single-cell analysis and functional characterization uncover the stem cell hierarchies and developmental origins of rhabdomyosarcoma.

Rhabdomyosarcoma (RMS) is a common childhood cancer that shares features with developing skeletal muscle. Yet, the conservation of cellular hierarchy with human muscle development and the identification of molecularly defined tumor-propagating cells has not been reported. Using single-cell RNA-sequencing, DNA-barcode cell fate mapping and functional stem cell assays, we uncovered shared tumor cell hierarchies in RMS and human muscle development. We also identified common developmental stages at which tumor cells become arrested. Fusion-negative RMS cells resemble early myogenic cells found in embryonic and fetal development, while fusion-positive RMS cells express a highly specific gene program found in muscle cells transiting from embryonic to fetal development at 7-7.75 weeks of age. Fusion-positive RMS cells also have neural pathway-enriched states, suggesting less-rigid adherence to muscle-lineage hierarchies. Finally, we identified a molecularly defined tumor-propagating subpopulation in fusion-negative RMS that shares remarkable similarity to bi-potent, muscle mesenchyme progenitors that can make both muscle and osteogenic cells.

EWSR1-ATF1 dependent 3D connectivity regulates oncogenic and differentiation programs in Clear Cell Sarcoma.

Oncogenic fusion proteins generated by chromosomal translocations play major roles in cancer. Among them, fusions between EWSR1 and transcription factors generate oncogenes with powerful chromatin regulatory activities, capable of establishing complex gene expression programs in permissive precursor cells. Here we define the epigenetic and 3D connectivity landscape of Clear Cell Sarcoma, an aggressive cancer driven by the EWSR1-ATF1 fusion gene. We find that EWSR1-ATF1 displays a distinct DNA binding pattern that requires the EWSR1 domain and promotes ATF1 retargeting to new distal sites, leading to chromatin activation and the establishment of a 3D network that controls oncogenic and differentiation signatures observed in primary CCS tumors. Conversely, EWSR1-ATF1 depletion results in a marked reconfiguration of 3D connectivity, including the emergence of regulatory circuits that promote neural crest-related developmental programs. Taken together, our study elucidates the epigenetic mechanisms utilized by EWSR1-ATF1 to establish regulatory networks in CCS, and points to precursor cells in the neural crest lineage as candidate cells of origin for these tumors.

Myc is a prognostic biomarker and potential therapeutic target in osteosarcoma.

BACKGROUND: Over the past four decades, outcomes for osteosarcoma patients have plateaued as there have been few emerging therapies showing clinical results. Thus, the identification of novel biomarkers and therapeutic strategies are urgently needed to address these primary obstacles in patient care. Although the Myc-oncogene has known roles in oncogenesis and cancer cell growth, its expression and function in osteosarcoma are largely unknown. METHODS: Expression of Myc was determined by Western blotting of osteosarcoma cell lines and patient tissues, and by immunohistochemistry of a unique osteosarcoma tissue microarray (TMA) constructed from 70 patient samples with extensive follow-up data. Myc specific siRNA and inhibitor 10058-F4 were applied to examine the effect of Myc inhibition on osteosarcoma cell proliferation. The clonogenicity and migration activity was determined by clonogenic and wound-healing assays. A mimic in vivo assay, three-dimensional (3D) cell culture model, was performed to further validate the effect of Myc inhibition on osteosarcoma cell tumorigenic markers. RESULTS: Myc was significantly overexpressed in human osteosarcoma cell lines compared with normal human osteoblasts, and also highly expressed in fresh osteosarcoma tissues. Higher Myc expression correlated significantly with metastasis and poor prognosis. Through the addition of Myc specific siRNA and inhibitor, we significantly reduced Myc protein expression, resulting in decreased osteosarcoma cell proliferation. Inhibition of Myc also suppressed the migration, clonogenicity, and spheroid growth of osteosarcoma cells. CONCLUSION: Our results support Myc as an emerging prognostic biomarker and therapeutic target in osteosarcoma therapy.

MicroRNA-mRNA networks define translatable molecular outcome phenotypes in osteosarcoma.

There is a lack of well validated prognostic biomarkers in osteosarcoma, a rare, recalcitrant disease for which treatment standards have not changed in over 20 years. We performed microRNA sequencing in 74 frozen osteosarcoma biopsy samples, constituting the largest single center translationally analyzed osteosarcoma cohort to date, and we separately analyzed a multi-omic dataset from a large NCI supported national cooperative group cohort. We validated the prognostic value of candidate microRNA signatures and contextualized them in relevant transcriptomic and epigenomic networks. Our results reveal the existence of molecularly defined phenotypes associated with outcome independent of clinicopathologic features. Through machine learning based integrative pharmacogenomic analysis, the microRNA biomarkers identify novel therapeutics for stratified application in osteosarcoma. The previously unrecognized osteosarcoma subtypes with distinct clinical courses and response to therapy could be translatable for discerning patients appropriate for more intensified, less intensified, or alternate therapeutic regimens.

Author Correction: Intragenic antagonistic roles of protein and circRNA in tumorigenesis.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Serum proteomics and biomarkers in hepatocellular carcinoma and chronic liver disease.

PURPOSE: Proteomic profiling using surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF MS) enables the identification of biomarkers for cancer. We evaluated the sensitivity and specificity of SELDI-TOF MS for detection of established hepatocellular cancer (HCC) and compared it against alpha-fetoprotein (AFP), Lens culinaris agglutinin-reactive AFP (AFP-L3), and prothrombin induced by vitamin K absence-II (PIVKA-II). EXPERIMENTAL DESIGN: Forty-one patients with HCC and 51 patients with hepatitis C cirrhosis were enrolled. Serum was analyzed by SELDI-TOF MS using three Ciphergen protein array types. RESULTS: An 11-peak algorithm for HCC detection was identified. Using the AFP cutoff of 20 ng/mL, the sensitivity was 73% and the specificity was 71%. Using the AFP-L3 cutoff of 10% yielded a sensitivity of 63% and a specificity of 94%. Using the PIVKA-II cutoff of 125 milliabsorbance units (mAU), the sensitivity was 84% and the specificity was 69%. Overall, the sensitivity and specificity of SELDI-TOF MS for HCC were 79% and 86%, respectively. In multivariate analysis, the 11-peak SELDI profile was predictive of HCC independent of AFP, PIVKA, and AFP-L3. Among eight patients with the largest tumor size of <2 cm, SELDI-TOF MS correctly identified seven whereas AFP, AFP-L3, and PIVKA-II identified only three, one, and one, respectively. One of the 11 peaks in the SELDI-TOF MS 11-peak predictor from SELDI-TOF MS was identified as cystatin C. CONCLUSIONS: SELDI-TOF MS accurately distinguished patients with HCC from those with hepatitis C virus cirrhosis, was more accurate than traditional biomarkers in identifying small tumors, and should be further evaluated.

Gene-expression profiling in epithelial ovarian cancer.

DNA-microarray technology has made it possible to simultaneously analyze the expression of thousands of genes in a small sample of tumor tissue. In epithelial ovarian cancer, gene-expression profiling has been used to provide prognostic information, to predict response to first-line platinum-based chemotherapy, and to discriminate between different histologic subtypes. Furthermore, DNA-microarray technology might permit identification of novel markers for early detection of disease and provide insights into the mechanisms of cancer growth and chemotherapy resistance. In this Review, we summarize the contributions of gene-expression profiling to the diagnosis and management of epithelial ovarian cancer and discuss ways in which this technique could become a useful tool in clinical management.

Reproducibility of proteomic profiles over 3 years in postmenopausal women not taking postmenopausal hormones.

Most proteomics studies examine one blood specimen per participant; however, it is unknown how well measures at one time point reflect an individual's long-term proteome pattern. Therefore, we examined the stability of the proteome over 3 years in postmenopausal women not taking hormones for at least 3 months using surface-enhanced laser desorption and ionization time-of-flight mass spectrometry. Using the Nurses' Health Study blood cohort, we randomly selected 60 women from a subset providing 2 to 3 blood samples over 3 years. Four different protein chip surfaces/plasma fractions were examined: unfractionated plasma on a CM10 and H50 chip, pH >/= 9, plasma fraction on a CM10 chip, and the organic fraction on the H50 chip, all with a low- and high-energy transfer protocol. Participant and quality control samples were aligned to a reference sample and then peak intensity was assessed for all peaks identified in the reference sample. The average coefficient of variation (CV) of the peak intensity within conditions ranged from 16% (H50, organic, low protocol) to 63% (CM10, pH > or = 9, high protocol). Generally, the CV and mean peak intensity of the quality control samples were inversely correlated (median -0.48). The mean intraclass correlation (ICC) within conditions ranged from 0.37 (H50, unfractionated, low protocol) to 0.68 (CM10, unfractionated, high protocol). For a signal-to-noise cutoff of 2.0, we observed 334 peaks, of which 241 (72%) had an ICC of > or =0.40. Although we observed a large range of CVs and ICCs, sufficient numbers of peaks had reasonable ICCs to suggest that protein peak reproducibility over 3 years was reasonable among postmenopausal women not taking hormones.

Proteomic identification of interleukin-2 therapy response in metastatic renal cell cancer.

PURPOSE: To detect a predictive protein profile that distinguishes interleukin-2 therapy responders and nonresponders among patients with metastatic renal cell carcinoma we used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. MATERIALS AND METHODS: Protein extracts from 56 patients with metastatic clear cell patients renal cell carcinoma obtained from radical nephrectomy specimens before interleukin-2 therapy were applied to protein chip arrays of different chromatographic properties and analyzed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. A class prediction algorithm was applied to identify a subset of protein peaks with expression values associated with interleukin-2 response status. Multivariate analysis was performed to assess the association between the proteomic profile and interleukin-2 response status, controlling for the effect of lymphadenopathy. RESULTS: From 513 protein peaks we discovered a predictor set of 11 that performed optimally for predicting interleukin-2 response status with 86% accuracy (Fisher's p <0.004, permutation p <0.01). Results were validated in an independent data set with 72% overall accuracy (p <0.05, permutation p <0.01). On multivariate analysis the proteomic profile was significantly associated with the interleukin-2 response when corrected for lymph node status (p <0.04). CONCLUSIONS: We identified and validated a proteomic pattern that is an independent predictor of the interleukin-2 response. The ability to predict the probability of the interleukin-2 response could permit targeted selection of the patients most likely to respond to interleukin-2, while avoiding unwanted toxicity in patients less likely to respond. This proteomic predictor has the potential to significantly aid clinicians in the decision making of appropriate therapy for patients with metastatic renal cell carcinoma.

IGF axis gene expression patterns are prognostic of survival in epithelial ovarian cancer.

The IGF axis has documented growth-promoting effects in various malignancies, but its role in epithelial ovarian cancer (EOC) has not been adequately examined. We studied the expression of the IGF axis genes in relation to outcome in EOC. Microarray expression profiles from 64 patients with advanced-stage EOC were used. Two multi-gene subsets were chosen, one upstream of the IGF receptor ('IGF family') and the other downstream of the IGF receptor ('IGF signaling pathway'), and analyzed in relation to survival. In addition, expression patterns of the two gene subsets were analyzed in relation to favorable and unfavorable prognosis categories identified in a previous study by whole-genome expression profiling. In a gene-by-gene analysis, IGF binding protein 4 and IGF-II receptor gene expression was inversely associated with survival. Using hierarchical clustering, the two multi-gene subsets separated the patient cohort into two groups with different median survival (IGF family: 33 vs 63 months, P=0.02 and IGF signaling pathway: 41 vs 63 months, P=0.05). Furthermore, the two multi-gene subsets were differentially expressed between the previously defined favorable and unfavorable prognosis tumors (Kolmogorov-Smirnov permutation: P=0.0005 and 0.003 for the IGF family and signaling pathway respectively), and individual genes (including IGF-I, IGF-I receptor, and several genes downstream of the receptor) were overexpressed in unfavorable prognosis tumors (permutation P<0.05). The expression patterns of several genes in the IGF axis are associated with survival in EOC, and expression changes of these genes may be underlying previously proposed microarray-derived clinical prognostic models. Future studies are needed to more precisely determine the diagnostic and potential therapeutic significance of these findings.

Age-related transcription levels of KU70, MGST1 and BIK in CD34+ hematopoietic stem and progenitor cells.

Despite the known longevity of human hematopoietic stem and progenitor cells (HSC), numerous functional impairments of these cells can be observed in an age-dependent manner. However, the molecular alterations associated with aging of HSC are largely unknown. Therefore, we scrutinized gene expression patterns of HSC from newborn, young and old healthy donors. CD34+ HSC were isolated via immuno-magnetic separation and evaluated by FACS analysis. We performed cDNA macroarray analyses on a first set of CD34+ samples (n=13). We found the genes encoding KU-antigen 70 kD (KU70), microsomal glutathione S-transferase 1 (MGST1) and BCL2-interacting killer (BIK) to possess age-related mRNA expression levels. KU70 is a DNA repair gene and part of the DNA-dependent protein kinase (DNA-PK) complex. Its expression was negatively correlated with donor age showing highest expression levels in newborn, 2.6-fold lower levels in young and 6.3-fold lower levels in old donors. The transcription levels of MGST1, a gene protecting against oxidative stress, progressively increased with age. Expression was lowest in newborn, 2.6-fold higher in young and 4.3-fold higher in old donors. BIK is a proapoptotic gene and its expression was positively correlated with donor age: lowest in newborn, 1.8-fold higher in young and 4.1-fold higher in old donors. These findings were confirmed with an independent, second set of CD34+ samples (n=16) by means of quantitative real-time RT-PCR. Elucidation of age-dependent molecular alterations in healthy HSC facilitate a better understanding of functional impairments in hematopoiesis and may become valuable for anti-aging drug development and the emerging field of regenerative medicine.

A Collision Tumor Involving a Primary Leiomyosarcoma of the Lower Extremity and a Metastatic Medullary Thyroid Carcinoma: A Case Report.

CASE: A 49-year-old man presented with a rapidly growing thigh mass. Histologic analyses demonstrated separate regions that were consistent with a collision tumor composed of a primary leiomyosarcoma and a metastatic medullary thyroid carcinoma. After responding to chemotherapy, the patient underwent resection of the tumor and a total thyroidectomy; he was disease-free 9 years after the diagnosis. CONCLUSION: A wide diagnostic differential and thorough histologic analysis are necessary in patients presenting with neoplasms of the extremities. A leiomyosarcoma may be a hospitable location for metastatic disease, and the presence of a collision tumor should be considered when pathology findings are equivocal.

Expression and Therapeutic Potential of SOX9 in Chordoma.

Purpose: Conventional chemotherapeutic agents are ineffective in the treatment of chordoma. We investigated the functional roles and therapeutic relevance of the sex-determining region Y (SRY)-box 9 (SOX9) in chordoma.Experimental Design: SOX9 expression was examined by immunohistochemistry (IHC) using 50 chordoma tissue samples. SOX9 expression in chordoma cell lines was examined by Western blot and immunofluorescent assays. We used synthetic human SOX9 siRNA to inhibit the expression of SOX9. Cell proliferation ability and cytotoxicity of inhibiting SOX9 were assessed by 3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide (MTT) and clonogenic assays. The effect of SOX9 knockdown on chordoma cell motility was evaluated by a wound-healing assay and a Transwell invasion chamber assay. Knockdown of SOX9 induced apoptosis, cell-cycle arrest, as well as decreased expression of cancer stem cell markers were determined by Western blot and flow cytometric assays. The effect of the combination of SOX9 siRNA and the chemotherapeutic drug doxorubicin/cisplatin on chordoma cells was assessed by an MTT assay.Results: Tissue microarray and IHC analysis showed that SOX9 is broadly expressed in chordomas and that higher expression levels of SOX9 correlated with a poor prognosis. RNA interference (RNAi)-mediated knockdown of SOX9 inhibited chordoma cell growth, decreased cell motility, and induced apoptosis as well as cell-cycle arrest. Moreover, the combination of SOX9 inhibition and chemotherapeutic drugs had an enhanced anti-cancer effect on chordoma cells.Conclusions: Our results demonstrate that SOX9 plays a crucial role in chordoma. Targeting SOX9 provides a new rationale for treatment of chordoma. Clin Cancer Res; 23(17); 5176-86. ©2017 AACR.