Distinguishing Tumor and Stromal Sources of MicroRNAs Linked to Metastasis in Cutaneous Melanoma

MicroRNA (miRNA) dysregulation in cancer causes changes in gene expression programs regulating tumor progression and metastasis. Candidate metastasis suppressor miRNA are often identified by differential expression in primary tumors compared to metastases. Here, we performed comprehensive analysis of miRNA expression in The Cancer Genome Atlas (TCGA) skin cutaneous melanoma (SKCM) tumors (97 primary, 350 metastatic), and identified candidate metastasis-suppressor miRNAs. Differential expression analysis revealed miRNA significantly downregulated in metastatic tumors, including miR-205, miR-203, miR-200a-c, and miR-141. Furthermore, sequential feature selection and classification analysis identified miR-205 and miR-203 as the miRNA best able to discriminate between primary and metastatic tumors. However, cell-type enrichment analysis revealed that gene expression signatures for epithelial cells, including keratinocytes and sebocytes, were present in primary tumors and significantly correlated with expression of the candidate metastasis-suppressor miRNA. Examination of miRNA expression in cell lines revealed that candidate metastasis-suppressor miRNA identified in the SKCM tumors, were largely absent in melanoma cells or melanocytes, and highly restricted to keratinocytes and other epithelial cell types. Indeed, the differences in stromal cell composition between primary and metastatic tumor tissues is the main basis for identification of differential miRNA that were previously classified as metastasis-suppressor miRNAs. We conclude that future studies must consider tumor-intrinsic and stromal sources of miRNA in their workflow to identify bone fide metastasis-suppressor miRNA in cutaneous melanoma and other cancers.     

Stem-like and non-stem human pancreatic cancer cells distinguished by morphology and metastatic behavior

We report here that XPA1 human pancreatic cancer cells are dimorphic. After injection in the spleen, XPA1 cells isolated from the primary tumor in the spleen were predominantly round; while cells isolated from the resulting liver metastasis and ascites were comprised of both round- and spindle-shaped cell types. Cancer cells previously grown in the spleen and re-implanted in the spleen developed large primary tumors in the spleen only. Cancer cells isolated from liver metastasis and re-transplanted to the spleen resulted in a primary tumor in the spleen and liver metastasis. Cancer cells derived from ascites and re-transplanted to the spleen developed primary tumors in the spleen and distant metastasis in the liver, lung, and diaphragm in addition to ascites formation. Spindle and round cells were differentially labeled with fluorescent proteins of different colors. After co-injection of the two cell types in the spleen, cells were isolated from the primary tumors, liver metastasis, and ascites and analyzed by color-coded fluorescence microscopy and fluorescence-activated cell sorting (FACS). No significant differences between the percentages of spindle-shaped and round cancer cells in the primary tumor and the liver metastasis were observed. However, spindle-shaped cancer cells were enriched in the ascites. One hundred percent of the spindle-shaped and round cancer cells expressed CD44, suggesting that morphology and metastatic behavior rather than CD44 expression can distinguish the stem-like cells of the XPA1 pancreatic cancer cell line. The spindle-shaped cancer cells had the greater capability for distant metastasis and ascites formation, suggesting they are stem-like cells, which can be readily targeted for therapy.     

Convergence of the proteomic pattern in cancer

MOTIVATION: On the histological level the differentiation of normal epithelial tissues is well known. The phenomenon of dedifferentiation, which occurs as cells develop towards malignancy is also well described. To identify an epithelial tumor-specific proteomic profile as well as to measure the proximities between we used data from tumor tissue and adjacent normal tissue microdissected from head and neck and colon cancer samples which were analyzed using ProteinChip technology and performed a bioinformatic meta-analysis on the resulting four complex datasets. RESULTS: All four groups could be identified based on their proteomic signatures and the tumor tissues were found to be more similar to one another than to the normal epithelial tissue from which they progressed. This study shows at the proteomic level that changes in the histological features of tumors as compared to the tissues from which they arise are reflected in the convergence of proteomic pattern during the development to cancer.     

Detection of bladder cancer using proteomic profiling of urine sediments

We used protein expression profiles to develop a classification rule for the detection and prognostic assessment of bladder cancer in voided urine samples. Using the Ciphergen PBS II ProteinChip Reader, we analyzed the protein profiles of 18 pairs of samples of bladder tumor and adjacent urothelium tissue, a training set of 85 voided urine samples (32 controls and 53 bladder cancer), and a blinded testing set of 68 voided urine samples (33 controls and 35 bladder cancer). Using t-tests, we identified 473 peaks showing significant differential expression across different categories of paired bladder tumor and adjacent urothelial samples compared to normal urothelium. Then the intensities of those 473 peaks were examined in a training set of voided urine samples. Using this approach, we identified 41 protein peaks that were differentially expressed in both sets of samples. The expression pattern of the 41 protein peaks was used to classify the voided urine samples as malignant or benign. This approach yielded a sensitivity and specificity of 59% and 90%, respectively, on the training set and 80% and 100%, respectively, on the testing set. The proteomic classification rule performed with similar accuracy in low- and high-grade bladder carcinomas. In addition, we used hierarchical clustering with all 473 protein peaks on 65 benign voided urine samples, 88 samples from patients with clinically evident bladder cancer, and 127 samples from patients with a history of bladder cancer to classify the samples into Cluster A or B. The tumors in Cluster B were characterized by clinically aggressive behavior with significantly shorter metastasis-free and disease-specific survival.     

High-throughput proteomic analysis of formalin-fixed paraffin-embedded tissue microarrays using MALDI imaging mass spectrometry

A novel method for high-throughput proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissue microarrays (TMA) is described using on-tissue tryptic digestion followed by MALDI imaging MS. A TMA section containing 112 needle core biopsies from lung-tumor patients was analyzed using MS and the data were correlated to a serial hematoxylin and eosin (H&E)-stained section having various histological regions marked, including cancer, non-cancer, and normal ones. By correlating each mass spectrum to a defined histological region, statistical classification models were generated that can sufficiently distinguish biopsies from adenocarcinoma from squamous cell carcinoma biopsies. These classification models were built using a training set of biopsies in the TMA and were then validated on the remaining biopsies. Peptide markers of interest were identified directly from the TMA section using MALDI MS/MS sequence analysis. The ability to detect and characterize tumor marker proteins for a large cohort of FFPE samples in a high-throughput approach will be of significant benefit not only to investigators studying tumor biology, but also to clinicians for diagnostic and prognostic purposes.     

Dissection of a metastatic gene expression signature into distinct components

Background

Metastasis, the process whereby cancer cells spread, is in part caused by an incompletely understood interplay between cancer cells and the surrounding stroma. Gene expression studies typically analyze samples containing tumor cells and stroma. Samples with less than 50% tumor cells are generally excluded, thereby reducing the number of patients that can benefit from clinically relevant signatures.

Results

For a head-neck squamous cell carcinoma (HNSCC) primary tumor expression signature that predicts the presence of lymph node metastasis, we first show that reduced proportions of tumor cells results in decreased predictive accuracy. To determine the influence of stroma on the predictive signature and to investigate the interaction between tumor cells and the surrounding microenvironment, we used laser capture microdissection to divide the metastatic signature into six distinct components based on tumor versus stroma expression and on association with the metastatic phenotype. A strikingly skewed distribution of metastasis associated genes is revealed.

Conclusion

Dissection of predictive signatures into different components has implications for design of expression signatures and for our understanding of the metastatic process. Compared to primary tumors that have not formed metastases, primary HNSCC tumors that have metastasized are characterized by predominant down-regulation of tumor cell specific genes and exclusive up-regulation of stromal cell specific genes. The skewed distribution agrees with poor signature performance on samples that contain less than 50% tumor cells. Methods for reducing tumor composition bias that lead to greater predictive accuracy and an increase in the types of samples that can be included are presented.     

Manganese superoxide dismutase (SOD2/MnSOD)/catalase and SOD2/GPx1 ratios as biomarkers for tumor progression and metastasis in prostate,colon, and lung cancer

The role of manganese-dependent superoxide dismutase (SOD2/MnSOD) during tumor progression has been studied for several decades with controversial results. While SOD2 downregulation was initially associated with tumor initiation and was proposed as a tumor suppressor gene, recent studies have reported that SOD2 might favor tumor progression and dissemination. To our knowledge this is the first time that changes in SOD2 expression in three different types of tumors, i.e., prostate, lung, and colon cancer, are studied by analyzing both SOD2 mRNA and protein levels in a total of 246 patients׳ samples. In prostate samples, SOD2 protein levels were also increased, especially in middle stage tumors. In the case of colon and lung tumors both mRNA and protein SOD2 levels were increased in malignant tissues compared to those in nontumor samples. More importantly, all metastases analyzed showed increased levels of SOD2 when compared to those of normal primary tissue and healthy adjacent tissue. Together, these results suggest that a common redox imbalance in these three types of tumor occurs at intermediate stages which then might favor migration and invasion, leading to a more aggressive cancer type. Consequently, the ratios SOD2/catalase and SOD2/Gpx1 could be considered as potential markers during progression from tumor growth to metastasis.     

Identification of a novel aspartic-like protease differentially expressed in human breast cancer cell lines

Four different human breast cancer cell lines were examined to search for genes associated with tumor growth and metastasis. Each of these cell lines, MDA-MB-453, MCF-7, MDA-MB-231 and MDA-MB-435, displays different phenotypic characteristics ranging from poorly to highly tumorigenic and metastatic. The differences in gene expression profiles of these cell lines generated by differential display technique should allow one to identify candidates as putative oncogenes or tumor/metastasis suppressor genes. A novel cDNA expressed in the highly tumorigenic and metastatic cell line, MDA-MB-435, was identified and isolated by this approach. The function for this gene, designated ALP56 (aspartic-like protease 56 kDa), in tumor progression is suggested by the homology of the encoded protein to aspartic proteases, such as cathepsin D. The amino acid residues in two catalytic domains of this family are highly conserved in those domains of ALP56. Northern hybridization indicated that the expression of ALP56 is associated with growth and metastasis of MDA-MB-435 tumors in immunodeficient mice. In situ hybridization of biopsies from breast cancer and colon cancer patients indicated that ALP56 is upregulated in human primary tumors and liver metastasis. These results suggest that this novel gene correlates with human tumor progression.     

Colon-Derived Liver Metastasis,Colorectal Carcinoma,and Hepatocellular Carcinoma Can Be Discriminated by the Ca2+-Binding Proteins S100A6 and S100A11

Background

It is unknown, on the proteomic level, whether the protein patterns of tumors change during metastasis or whether markers are present that allow metastases to be allocated to a specific tumor entity. The latter is of clinical interest if the primary tumor is not known.

Methodology/Principal Findings

In this study, tissue from colon-derived liver metastases (n = 17) were classified, laser-microdissected, and analysed by ProteinChip arrays (SELDI). The resulting spectra were compared with data for primary colorectal (CRC) and hepatocellular carcinomas (HCC) from our former studies. Of 49 signals differentially expressed in primary HCC, primary CRC, and liver metastases, two were identified by immunodepletion as S100A6 and S100A11. Both proteins were precisely localized immunohistochemically in cells. S100A6 and S100A11 can discriminate significantly between the two primary tumor entities, CRC and HCC, whereas S100A6 allows the discrimination of metastases and HCC.

Conclusions

Both identified proteins can be used to discriminate different tumor entities. Specific markers or proteomic patterns for the metastases of different primary cancers will allow us to determine the biological characteristics of metastasis in general. It is unknown how the protein patterns of tumors change during metastasis or whether markers are present that allow metastases to be allocated to a specific tumor entity. The latter is of clinical interest if the primary tumor is not known.     

MALDI imaging mass spectrometry reveals COX7A2, TAGLN2 and S100-A10 as novel prognostic markers in Barrett's adenocarcinoma

To characterize proteomic changes found in Barrett's adenocarcinoma and its premalignant stages, the proteomic profiles of histologically defined precursor and invasive carcinoma lesions were analyzed by MALDI imaging MS. For a primary proteomic screening, a discovery cohort of 38 fresh frozen Barrett's adenocarcinoma patient tissue samples was used. The goal was to find proteins that might be used as markers for monitoring cancer development as well as for predicting regional lymph node metastasis and disease outcome. Using mass spectrometry for protein identification and validating the results by immunohistochemistry on an independent validation set, we could identify two of 60 differentially expressed m/z species between Barrett's adenocarcinoma and the precursor lesion: COX7A2 and S100-A10. Furthermore, among 22 m/z species that are differentially expressed in Barrett's adenocarcinoma cases with and without regional lymph node metastasis, one was identified as TAGLN2. In the validation set, we found a correlation of the expression levels of COX7A2 and TAGLN2 with a poor prognosis while S100-A10 was confirmed by multivariate analysis as a novel independent prognostic factor in Barrett's adenocarcinoma. Our results underscore the high potential of MALDI imaging for revealing new biologically significant molecular details from cancer tissues which might have potential for clinical application. This article is part of a Special Issue entitled: Translational Proteomics.     

Assessment of a novel VEGF targeted agent using patient-derived tumor tissue xenograft models of colon carcinoma with lymphatic and hepatic metastases

The lack of appropriate tumor models of primary tumors and corresponding metastases that can reliably predict for response to anticancer agents remains a major deficiency in the clinical practice of cancer therapy. It was the aim of our study to establish patient-derived tumor tissue (PDTT) xenograft models of colon carcinoma with lymphatic and hepatic metastases useful for testing of novel molecularly targeted agents. PDTT of primary colon carcinoma, lymphatic and hepatic metastases were used to create xenograft models. Hematoxylin and eosin staining, immunohistochemical staining, genome-wide gene expression analysis, pyrosequencing, qRT-PCR, and western blotting were used to determine the biological stability of the xenografts during serial transplantation compared with the original tumor tissues. Early passages of the PDTT xenograft models of primary colon carcinoma, lymphatic and hepatic metastases revealed a high degree of similarity with the original clinical tumor samples with regard to histology, immunohistochemistry, genes expression, and mutation status as well as mRNA expression. After we have ascertained that these xenografts models retained similar histopathological features and molecular signatures as the original tumors, drug sensitivities of the xenografts to a novel VEGF targeted agent, FP3 was evaluated. In this study, PDTT xenograft models of colon carcinoma with lymphatic and hepatic metastasis have been successfully established. They provide appropriate models for testing of novel molecularly targeted agents.     

Preliminary evaluation of prostate cancer metastatic risk biomarkers

Prostate cancer patients at high risk of metastasis need to be identified as early as possible since metastasis is invariably fatal. Treatment could be tailored to risk. Recent array comparative genomic hybridization (aCGH) studies of primary and metastatic prostate tumors identified 39 BAC clones capable of detecting genomic signatures of metastasis. We termed these loci the genomic evaluators of metastatic CaP (GEMCaP). Risk assessments were made on a set of men who were managed with radical prostatectomy. We compared the utility of GEMCaP loci and the Kattan nomogram, a common risk assessment tool, in relation to biochemical outcome. This preliminary evaluation experiment suggests we can use aCGH to detect genomic signatures of metastasis in primary tumors with an accuracy of 78%. The classification accuracy for the Kattan nomogram was 75%. Therefore, validation of GEMCaP is warranted in a larger, appropriately designed cohort.     

Evaluation of hepatic-metastasis risk of colorectal cancer upon the protein signature of PI3K/AKT pathway

Liver is the most common organ of colorectal cancer (CRC) metastasis, and hepatic metastasis (HM) is regulated by complex protein network. Hence, we initiated a proteomic survey to seek interrelated multiplex markers related with HM. A total of 34 unique differential proteins were identified in the primary tumor tissues from 14 CRC patients with/without HM. A differential protein cluster, consisting of 17 proteins throughout PI3K/AKT pathway, was deduced and validated by Western blot. A three-protein signature elicited from the protein cluster, phosphorylated IkappaBalpha, TNFalpha and MFAP3L, was detected by immunohistochemistry on 105 pairs of CRC and normal samples. The positive protein signature was specifically correlated with HM (P < 0.001), and classified the HM risk of CRC patients with high sensitivity (92.85 +/- 4.87%) and specificity (94.94 +/- 2.5%). The high-risk group had significantly decreased overall survival (P < 0.001). Furthermore, RKO and HT29, two colon cancer cells with different expression status of the protein signature, were used to construct the nude mouse model of HM. And the HM occurrence of RKO cell (4/5) was dramatically higher than that of HT29 cell (1/5). Therefore, the protein signature derived from PI3K/AKT pathway is likely a promising multiplex biomarker for HM of CRC.     

Le traitement chirurgical des tumeurs endocrines digestives

Surgery is the only curative treatment for localized gastrointestinal endocrine tumors. It plays a major role in therapeutic strategy. It meets the oncological principles of treatment. It must take into consideration the site of the tumor, its extension and its secretory nature. In well-differentiated endocrine tumors according to WHO classification, surgery must be indicated, not only for the primary tumor but also for the metastasis, particularly liver metastasis. The primary gastrointestinal endocrine tumors (functional or non functional) are mainly pancreatic in origin but also can be situated in small bowel, appendix, colon, or rectum. Surgery is part of a comprehensive approach discussed in multidisciplinary meeting.     

Proteomic signature of human cancer cells

We assessed proteomic profiles as biomarkers for monitoring cell phenotypes. Protein expression profiles were obtained by fluorescence two-dimensional difference gel electrophoresis (2-D-DIGE), in which quantitative ability is improved by labeling proteins with fluorescent dyes prior to electrophoresis. Integrated protein spot intensities were analyzed by a statistical approach. The proteomic data of two groups of cell lines: (1) adenocarcinoma (AC) cell lines derived from lung, pancreas and colon tissues and (2) lung cancer cell lines with different histological backgrounds, including AC, squamous cell carcinoma and small cell carcinoma, were assessed on the basis of prior biological information. Hierarchical clustering analysis and principal component analysis were used to divide the cell lines into subgroups on the basis of similarities between their protein expression profiles. The majority of cell lines were grouped according to their organ of origin or histological background. A machine-learning algorithm selected 32 protein spots that were responsible for the classification. The results indicate that proteomic data generated by 2-D-DIGE can provide a signature of essential cell phenotypes, suggesting that it might be possible to apply this technique to developing tumor markers that could identify the organ of origin of metastatic tumors and contribute to the differential diagnosis of lung cancer.     

Integrative analysis identifies potential DNA methylation biomarkers for pan-cancer diagnosis and prognosis

DNA methylation status is closely associated with diverse diseases, and is generally more stable than gene expression, thus abnormal DNA methylation could be important biomarkers for tumor diagnosis, treatment and prognosis. However, the signatures regarding DNA methylation changes for pan-cancer diagnosis and prognosis are less explored. Here we systematically analyzed the genome-wide DNA methylation patterns in diverse TCGA cancers with machine learning. We identified seven CpG sites that could effectively discriminate tumor samples from adjacent normal tissue samples for 12 main cancers of TCGA (1216 samples, AUC > 0.99). Those seven potential diagnostic biomarkers were further validated in the other 9 different TCGA cancers and 4 independent datasets (AUC > 0.92). Three out of the seven CpG sites were correlated with cell division, DNA replication and cell cycle. We also identified 12 CpG sites that can effectively distinguish 26 different cancers (7605 samples), and the result was repeatable in independent datasets as well as two disparate tumors with metastases (micro-average AUC > 0.89). Furthermore, a series of potential signatures that could significantly predict the prognosis of tumor patients for 7 different cancer were identified via survival analysis (p-value < 1e-4). Collectively, DNA methylation patterns vary greatly between tumor and adjacent normal tissues, as well as among different types of cancers. Our identified signatures may aid the decision of clinical diagnosis and prognosis for pan-cancer and the potential cancer-specific biomarkers could be used to predict the primary site of metastatic breast and prostate cancers.     

Mutation of GDP-Mannose-4,6-Dehydratase in Colorectal Cancer Metastasis

Fucosylation is a crucial oligosaccharide modification in cancer. The known function of fucosylation in cancer is to mediate metastasis through selectin ligand-dependent processes. Previously, we found complete loss of fucosylation in the colon cancer cell line HCT116 due to a mutation in the GDP-fucose synthetic enzyme, GDP-mannose-4,6-dehydratase (GMDS). Loss of fucosylation led to escape of cancer cells from tumor immune surveillance followed by tumor progression and metastasis, suggesting a novel function of fucosylation in tumor progression pathway. In the present study, we investigated the frequency of GMDS mutation in a number of clinical colorectal cancer tissue samples: 81 samples of primary colorectal cancer tissue and 39 samples of metastatic lesion including liver and lymph node. Four types of deletion mutation in GMDS were identified in original cancer tissues as well as metastatic lesions. The frequency of GMDS mutation was slightly higher in metastatic lesions (12.8%, 5/39 samples) than in original cancer tissues (8.6%, 7/81 samples). No mutation of the GMDS gene was observed in normal colon tissues surrounding cancer tissues, suggesting that the mutation is somatic rather than in the germline. Immunohistochemical analysis revealed complete loss of fucosylation in three cases of cancer tissue. All three cases had GMDS mutation. In one of three cases, loss of fucosylation was observed in only metastatic lesion, but not its original colon cancer tissue. These data demonstrate involvement of GMDS mutation in the progression of colorectal cancer.     

DNA methylation data–based molecular subtype classification related to the prognosis of patients with cervical cancer

Cervical cancer is one of the leading female health-killers among all types of malignancies globally. Human papillomavirus infection combined with genetic and epigenetic alterations have been indicated to be closely associated with the pathogenesis, progression, and malignant transformation of cervical cancer. Notably, during the complex tumorigenesis process, a series of DNA methylations occurs early and is the most frequent molecular behavior. In this study, to exploit the specific DNA methylation sites influencing the prognosis of patients with cervical cancer, 275 samples were downloaded from The Cancer Genome Atlas database and further analyzed. As a result, 1253 CpGs were found to have a significant correlation with patient prognosis and were further selected for the consistent clustering of samples into six subgroups. Specifically, the samples in every subgroup were different regarding the following: race, age, tumor stage, receptor status, histological type, metastasis status, and patient prognosis. In addition, we calculated the levels of methylation sites in all subgroups, with 79 methylation sites (corresponding to 81 genes) screened as the intrasubgroup-specific methylation sites. Moreover, signaling pathway enrichment analysis was conducted on the genes of the corresponding promoter regions of the above-described specific methylation sites, revealing that these genes were enriched in biological pathways closely associated with tumors, such as the cyclic guanosine monophosphate–dependent protein kinase and focal adhesion signaling pathways. Finally, the least absolute shrinkage and selection operator algorithm was employed to establish a prognostic prediction model for cervical cancer patients, with training and test sets used for testing and validation, respectively. In summary, the specific DNA methylation site–based classification is able to reflect the heterogeneity of cervical cancer tissue, contributing to the development of personalized therapy and the accurate prediction of patient prognosis.