Purpose

The requirement of frozen tissues for microarray experiments limits the clinical usage of genome-wide expression profiling using microarray technology. The goal of this study is to test the feasibility of developing lung cancer prognosis gene signatures using genome-wide expression profiling of formalin-fixed paraffin-embedded (FFPE) samples, which are widely available and provide a valuable rich source for studying the association of molecular changes in cancer and associated clinical outcomes.

Experimental Design

We randomly selected 100 Non-Small-Cell lung cancer (NSCLC) FFPE samples with annotated clinical information from the UT-Lung SPORE Tissue Bank. We micro dissected tumor area from FFPE specimens, and used Affymetrix U133 plus 2.0 arrays to attain gene expression data. After strict quality control and analysis procedures, a supervised principal component analysis was used to develop a robust prognosis signature for NSCLC. Three independent published microarray data sets were used to validate the prognosis model.

Results

This study demonstrated that the robust gene signature derived from genome-wide expression profiling of FFPE samples is strongly associated with lung cancer clinical outcomes, can be used to refine the prognosis for stage I lung cancer patients and the prognostic signature is independent of clinical variables. This signature was validated in several independent studies and was refined to a 59-gene lung cancer prognosis signature.

Conclusions

We conclude that genome-wide profiling of FFPE lung cancer samples can identify a set of genes whose expression level provides prognostic information across different platforms and studies, which will allow its application in clinical settings.

Background

Esophageal squamous cell carcinoma (ESCC), the predominant histological subtype of esophageal cancer, is characterized by high mortality. Previous work identified important mRNA expression differences between normal and tumor cells; however, to date there are limited ex vivo studies examining expression changes occurring during normal esophageal squamous cell differentiation versus those associated with tumorigenesis. In this study, we used a unique tissue microdissection strategy and microarrays to measure gene expression profiles associated with cell differentiation versus tumorigenesis in twelve cases of patient-matched normal basal squamous epithelial cells (NB), normal differentiated squamous epithelium (ND), and squamous cell cancer. Class comparison and pathway analysis were used to compare NB versus tumor in a search for unique therapeutic targets.

Results

As a first step towards this goal, gene expression profiles and pathways were evaluated. Overall, ND expression patterns were markedly different from NB and tumor; whereas, tumor and NB were more closely related. Tumor showed a general decrease in differentially expressed genes relative to NB as opposed to ND that exhibited the opposite trend. FSH and IgG networks were most highly dysregulated in normal differentiation and tumorigenesis, respectively. DNA repair pathways were generally elevated in NB and tumor relative to ND indicating involvement in both normal and pathological growth. PDGF signaling pathway and 12 individual genes unique to the tumor/NB comparison were identified as therapeutic targets, and 10 associated ESCC gene-drug pairs were identified. We further examined the protein expression level and the distribution patterns of four genes: ODC1, POSTN, ASPA and IGF2BP3. Ultimately, three genes (ODC1, POSTN, ASPA) were verified to be dysregulated in the same pattern at both the mRNA and protein levels.

Conclusions

These data reveal insight into genes and molecular pathways mediating ESCC development and provide information potentially useful in designing novel therapeutic interventions for this tumor type.

Squamous cell carcinoma (SCC) is an epithelial malignancy involving many anatomical sites and is the most common cancer capable of metastatic spread. Development of early diagnosis methods and novel therapeutics are important for prevention and mortality reduction. In this effort, numerous molecular alterations have been described in SCCs. SCCs share many phenotypic and molecular characteristics, but they have not been extensively compared. This article reviews SCC as a disease, including: epidemiology, pathology, risk factors, molecular characteristics, prognostic markers, targeted therapy, and a new approach to studying SCCs. Through this comparison, several themes are apparent. For example, HPV infection is a common risk factor among the four major SCCs (NMSC, HNSC, ESCC, and NSCLC) and molecular abnormalities in cell-cycle regulation and signal transduction predominate. These data reveal that the molecular insights, new markers, and drug targets discovered in individual SCCs may shed light on this type of cancer as a whole.

Previous studies have identified several dysregulated microRNAs in esophageal squamous cell carcinoma (ESCC); however, to date there are no ex vivo analyses comparing expression levels of these regulatory molecules in esophageal squamous cell tumors versus patient-matched normal epithelium. We describe here a technical strategy to evaluate microRNAs in normal esophageal basal cells (NB), normal esophageal differentiated cells (ND), and tumor cells (T). Laser capture microdissection was used to procure target populations from five cases and 18 ESCC-associated microRNAs were measured by RT-qPCR. Five microRNAs (miR-25, miR-106b, miR-21, miR-203, and miR-145) demonstrated consistent differential expression in at least one of the three comparisons: T vs. NB, T vs. ND, or NB vs. ND. The potential regulatory role of the microRNAs in ESCC was further evaluated by correlating their expression with a matched mRNA dataset, which included the same five cases and cell populations. In conclusion, the present work demonstrates the feasibility of studying microRNA levels in precisely dissected cell populations from clinical samples, and sheds light on the molecular mechanisms associated with ESCC.

Previous studies have identified several dysregulated microRNAs in esophageal squamous cell carcinoma (ESCC); however, to date there are no ex vivo analyses comparing expression levels of these regulatory molecules in esophageal squamous cell tumors versus patient-matched normal epithelium. We describe here a technical strategy to evaluate microRNAs in normal esophageal basal cells (NB), normal esophageal differentiated cells (ND), and tumor cells (T). Laser capture microdissection was used to procure target populations from five cases and 18 ESCC-associated microRNAs were measured by RT-qPCR. Five microRNAs (miR-25, miR-106b, miR-21, miR-203, and miR-145) demonstrated consistent differential expression in at least one of the three comparisons: T vs. NB, T vs. ND, or NB vs. ND. The potential regulatory role of the microRNAs in ESCC was further evaluated by correlating their expression with a matched mRNA dataset, which included the same five cases and cell populations. In conclusion, the present work demonstrates the feasibility of studying microRNA levels in precisely dissected cell populations from clinical samples, and sheds light on the molecular mechanisms associated with ESCC.

Background

Esophageal squamous cell carcinomas (ESCC) are usually asymptomatic and go undetected until they are incurable. Cytological screening is one strategy to detect ESCC at an early stage and has shown promise in previous studies, although improvement in sensitivity and specificity are needed. Proteases modulate cancer progression by facilitating tumor invasion and metastasis. In the current study, matrix metalloproteinases (MMPs) were studied in a search for new early detection markers for ESCC.

Methods

Protein expression levels of MMPs were measured using zymography in 24 cases of paired normal esophagus and ESCC, and in the tumor-associated stroma and tumor epithelium in one sample after laser capture microdissection (LCM). MMP-3 and MMP-10 transcripts in both the epithelium and stroma in five cases were further analyzed by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR).

Results

Gelatin zymography showed bands corresponding in size to MMP-2, MMP-3, MMP-9, and MMP-10 enzymes in each of the 24 cancer cases. MMP levels tended to be higher in tumors than paired normal tissue; however, only the 45 kDa band that corresponds to the activated form of MMP-3 and MMP-10 was strongly expressed in all 24 tumors with little or no expression in the paired normal foci. LCM-based analysis showed the 45 kDA band to be present in both the stromal and epithelial components of the tumor microenvironment, and that MMP-3 and MMP-10 mRNA levels were higher in tumors than paired normal tissues for each compartment.

Conclusions

Increased levels of MMPs occur in ESCC suggesting their up-regulation is important in esophageal tumorigenesis. The up-regulated gene products have the potential to serve as early detection markers in the clinic.

A novel approach was developed for mapping the location of target DNA in tissue sections. The method combines a high-density, multi-well plate with an innovative single-tube procedure to directly extract, amplify, and detect the DNA in parallel while maintaining the two-dimensional (2D) architecture of the tissue. A 2D map of the gene glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was created from a tissue section and shown to correlate with the spatial area of the sample. It is anticipated that this approach may be easily adapted to assess the status of multiple genes within tissue sections, yielding a molecular map that directly correlates with the histology of the sample. This will provide investigators with a new tool to interrogate the molecular heterogeneity of tissue specimens.

Handling and processing of clinical specimens during and after surgical resection may significantly skew the molecular data obtained from analysis of those samples. Minimally invasive prostatectomy was used as a model to specifically study effects of surgical ischemia on gene expression in human clinical samples. Normal prostatic urethra cup biopsies were procured from 12 patients at three time points during laparoscopic radical prostatectomy. Homogeneous cells (stroma and epithelium) were microdissected. Transcript analysis of 3 oxygen-dependent, 3 oxygen-independent, and 3 control class genes was performed using quantitative RT-PCR. Data were analyzed by relative quantitation and two-sided t-test. Patient demographic and time covariates were fit by a linear mixed model. VEGF, an oxygen-dependent gene, showed significant expression alterations across three time points in epithelium (p=0.008), but not in stroma (p=0.66). Expression levels of VHL, STAT5B, and CYPA showed significant changes at the p<0.05 level in the stroma only. Effects of age, PSA, prostate size, Gleason score, surgery type, total surgery time, total ischemia time, and estimated blood loss on VEGF expression over time were not significant at the p<0.01 level. Therefore, surgical manipulation and tissue processing methods need to be taken into account when assessing prostatic biomarkers; however, resection does not dramatically alter mRNA profiles in prostate specimens.

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a valuable tool for measuring gene expression in biological samples. However, unique challenges are encountered when studies are performed on cells microdissected from tissues derived from animal models or the clinic, including specimen related issues, variability of RNA template quality and quantity, and normalization. qRT-PCR using small amounts of mRNA derived from dissected cell populations requires adaptation of standard methods to allow meaningful comparisons across sample sets. The protocol described here presents the rationale, technical steps, normalization strategy, and data analysis necessary to generate reliable gene expression measurements of transcripts from dissected samples. The entire protocol from tissue microdissection through qRT-PCR analysis requires approximately 16 hours.

Squamous cell carcinoma (SCC) is an epithelial malignancy involving many anatomical sites and is the most common cancer capable of metastatic spread. Development of early diagnosis methods and novel therapeutics are important for prevention and mortality reduction. In this effort, numerous molecular alterations have been described in SCCs. SCCs share many phenotypic and molecular characteristics, but they have not been extensively compared. This article reviews SCC as a disease, including: epidemiology, pathology, risk factors, molecular characteristics, prognostic markers, targeted therapy, and a new approach to studying SCCs. Through this comparison, several themes are apparent. For example, HPV infection is a common risk factor among the four major SCCs (NMSC, HNSC, ESCC, and NSCLC) and molecular abnormalities in cell-cycle regulation and signal transduction predominate. These data reveal that the molecular insights, new markers, and drug targets discovered in individual SCCs may shed light on this type of cancer as a whole.

PURPOSE

After an initial response to androgen ablation, most prostate tumors recur, ultimately progressing to highly aggressive androgen independent (AI) cancer. The molecular mechanisms underlying progression are not well known, in part due to the rarity of AI samples from primary and metastatic sites.

EXPERIMENTAL DESIGN

We compared the gene expression profiles of ten AI primary prostate tumor biopsies with ten primary, untreated androgen-dependent (AD) tumors. Samples were laser capture microdissected, the RNA was amplified, and gene expression was assessed using Affymetrix Human Genome U133A Gene Chips. Differential expression was examined with principle component analysis (PCA) and Student t testing. Analysis of gene ontology was performed with Expression Analysis Systematic Explorer (EASE) and gene expression data were integrated with genomic alterations with DIfferential Gene locus MAPping (DIGMAP).

RESULTS

Unsupervised PCA showed that the AD and AI tumors segregated from one another. After filtering the data, 239 differentially expressed genes were identified. Two main gene ontologies were found discordant between AI and AD tumors: macromolecule biosynthesis was down-regulated and cell adhesion up-regulated in AI tumors. Other differentially expressed genes were related to IL-6 signaling, as well as angiogenesis, cell adhesion, apoptosis, oxidative stress, and hormone response. The DIGMAP analysis identified nine regions of potential chromosomal deletion in the AI tumors including 1p36, 3p21, 6p21, 8p21, 11p15, 11q12, 12q23, 16q12, and 16q21.

CONCLUSIONS

Taken together, these data identify several unique characteristics of AI prostate cancer that may hold potential for the development of targeted therapeutic intervention.

Background

A functional blood supply is essential for tumor growth and proliferation. However, the mechanism of blood vessel recruitment to the tumor is still poorly understood. Ideally, a thorough molecular assessment of blood vessel cells would be critical in our comprehension of this process. Yet, to date, there is little known about the molecular makeup of the endothelial cells of tumor-associated blood vessels, due in part to the difficulty of isolating a pure population of endothelial cells from the heterogeneous tissue environment.

Methods

Here we describe the use of a recently developed technique, Expression Microdissection, to isolate endothelial cells from the tumor microenvironment. The methylation status of the dissected samples was evaluated for GSTP1 and RARβ2 promoters via the QMS-PCR method.

Results

Comparing GSTP1 and RARβ2 promoter methylation data, we show that 100% and 88% methylation is detected, respectively, in the tumor areas, both in epithelium and endothelium. Little to no methylation is observed in non-tumor tissue areas.

Conclusion

We applied an accurate microdissection technique to isolate endothelial cells from tissues, enabling DNA analysis such as promoter methylation status. The observations suggest that epigenetic alterations may play a role in determining the phenotype of tumor-associated vasculature.