Phospholipase C Isozymes Are Deregulated in Colorectal Cancer – Insights Gained from Gene Set Enrichment Analysis of the Transcriptome

Colorectal cancer (CRC) is one of the most common cancer types in developed countries. To identify molecular networks and biological processes that are deregulated in CRC compared to normal colonic mucosa, we applied Gene Set Enrichment Analysis to two independent transcriptome datasets, including a total of 137 CRC and ten normal colonic mucosa samples. Eighty-two gene sets as described by the Kyoto Encyclopedia of Genes and Genomes database had significantly altered gene expression in both datasets. These included networks associated with cell division, DNA maintenance, and metabolism. Among signaling pathways with known changes in key genes, the “Phosphatidylinositol signaling network”, comprising part of the PI3K pathway, was found deregulated. The downregulated genes in this pathway included several members of the Phospholipase C protein family, and the reduced expression of two of these, PLCD1 and PLCE1, were successfully validated in CRC biopsies (n = 70) and cell lines (n = 19) by quantitative analyses. The repression of both genes was found associated with KRAS mutations (P = 0.005 and 0.006, respectively), and we observed that microsatellite stable carcinomas with reduced PLCD1 expression more frequently had TP53 mutations (P = 0.002). Promoter methylation analyses of PLCD1 and PLCE1 performed in cell lines and tumor biopsies revealed that methylation of PLCD1 can contribute to reduced expression in 40% of the microsatellite instable carcinomas. In conclusion, we have identified significantly deregulated pathways in CRC, and validated repression of PLCD1 and PLCE1 expression. This illustrates that the GSEA approach may guide discovery of novel biomarkers in cancer

Induction of Immune Mediators in Glioma and Prostate Cancer Cells by Non-Lethal Photodynamic Therapy

BACKGROUND: Photodynamic therapy (PDT) uses the combination of photosensitizing drugs and harmless light to cause selective damage to tumor cells. PDT is therefore an option for focal therapy of localized disease or for otherwise unresectable tumors. In addition, there is increasing evidence that PDT can induce systemic anti-tumor immunity, supporting control of tumor cells, which were not eliminated by the primary treatment. However, the effect of non-lethal PDT on the behavior and malignant potential of tumor cells surviving PDT is molecularly not well defined. METHODOLOGY/PRINCIPAL FINDINGS: Here we have evaluated changes in the transcriptome of human glioblastoma (U87, U373) and human (PC-3, DU145) and murine prostate cancer cells (TRAMP-C1, TRAMP-C2) after non-lethal PDT in vitro and in vivo using oligonucleotide microarray analyses. We found that the overall response was similar between the different cell lines and photosensitizers both in vitro and in vivo. The most prominently upregulated genes encoded proteins that belong to pathways activated by cellular stress or are involved in cell cycle arrest. This response was similar to the rescue response of tumor cells following high-dose PDT. In contrast, tumor cells dealing with non-lethal PDT were found to significantly upregulate a number of immune genes, which included the chemokine genes CXCL2, CXCL3 and IL8/CXCL8 as well as the genes for IL6 and its receptor IL6R, which can stimulate proinflammatory reactions, while IL6 and IL6R can also enhance tumor growth. CONCLUSIONS: Our results indicate that PDT can support anti-tumor immune responses and is, therefore, a rational therapy even if tumor cells cannot be completely eliminated by primary phototoxic mechanisms alone. However, non-lethal PDT can also stimulate tumor growth-promoting autocrine loops, as seen by the upregulation of IL6 and its receptor. Thus the efficacy of PDT to treat tumors may be improved by controlling unwanted and potentially deleterious growth-stimulatory pathways

Vowel reduction in word-final position by early and late Spanish-English bilinguals

Vowel reduction is a prominent feature of American English, as well as other stress-timed languages. As a phonological process, vowel reduction neutralizes multiple vowel quality contrasts in unstressed syllables. For bilinguals whose native language is not characterized by large spectral and durational differences between tonic and atonic vowels, systematically reducing unstressed vowels to the central vowel space can be problematic. Failure to maintain this pattern of stressed-unstressed syllables in American English is one key element that contributes to a ?foreign accent? in second language speakers. Reduced vowels, or ?schwas,? have also been identified as particularly vulnerable to the co-articulatory effects of adjacent consonants. The current study examined the effects of adjacent sounds on the spectral and temporal qualities of schwa in word-final position. Three groups of English-speaking adults were tested: Miami-based monolingual English speakers, early Spanish-English bilinguals, and late Spanish-English bilinguals. Subjects performed a reading task to examine their schwa productions in fluent speech when schwas were preceded by consonants from various points of articulation. Results indicated that monolingual English and late Spanish-English bilingual groups produced targeted vowel qualities for schwa, whereas early Spanish-English bilinguals lacked homogeneity in their vowel productions. This extends prior claims that schwa is targetless for F2 position for native speakers to highly-proficient bilingual speakers. Though spectral qualities lacked homogeneity for early Spanish-English bilinguals, early bilinguals produced schwas with near native-like vowel duration. In contrast, late bilinguals produced schwas with significantly longer durations than English monolinguals or early Spanish-English bilinguals. Our results suggest that the temporal properties of a language are better integrated into second language phonologies than spectral qualities. Finally, we examined the role of nonstructural variables (e.g. linguistic history measures) in predicting native-like vowel duration. These factors included: Age of L2 learning, amount of L1 use, and self-reported bilingual dominance. Our results suggested that different sociolinguistic factors predicted native-like reduced vowel duration than predicted native-like vowel qualities across multiple phonetic environments

Improved prognostication of glioblastoma beyond molecular subtyping by transcriptional profiling of the tumor microenvironment

Glioblastoma (GBM), the most aggressive form of brain cancer, is characterized by a high level of molecular heterogeneity, and infiltration by various immune and stromal cell populations. Important advances have been made in deciphering the microenvironment of GBMs, but its association with existing molecular subtypes and its potential prognostic role remain elusive. We have investigated the abundance of infiltrating immune and stromal cells in silico, from gene expression profiles. Two cohorts, including in-house normal brain and glioma samples (n = 70) and a large sample set from TCGA (n = 393), were combined into a single exploratory dataset. A third independent cohort (n = 124) was used for validation. Tumors were clustered based on their microenvironment infiltration profiles, and associations with known GBM molecular subtypes and patient outcome were tested a posteriori in a multivariable setting. We identified a subset of GBM samples with significantly higher abundances of most immune and stromal cell populations. This subset showed increased expression of both immune suppressor and immune effector genes compared to other GBMs and was enriched for the mesenchymal molecular subtype. Survival analyses suggested that tumor microenvironment infiltration pattern was an independent prognostic factor for GBM patients. Among all, patients with the mesenchymal subtype with low immune and stromal infiltration had the poorest survival. By combining molecular subtyping with gene expression measures of tumor infiltration, the present work contributes with improving prognostic models in GBM