Molecular heterogeneity of non-small cell lung carcinoma patient-derived xenografts closely reflect their primary tumors.

Availability of lung cancer models that closely mimic human tumors remains a significant gap in cancer research, as tumor cell lines and mouse models may not recapitulate the spectrum of lung cancer heterogeneity seen in patients. We aimed to establish a patient-derived tumor xenograft (PDX) resource from surgically resected non-small cell lung cancer (NSCLC). Fresh tumor tissue from surgical resection was implanted and grown in the subcutaneous pocket of non-obese severe combined immune deficient (NOD SCID) gamma mice. Subsequent passages were in NOD SCID mice. A subset of matched patient and PDX tumors and non-neoplastic lung tissues were profiled by whole exome sequencing, single nucleotide polymorphism (SNP) and methylation arrays, and phosphotyrosine (pY)-proteome by mass spectrometry. The data were compared to published NSCLC datasets of NSCLC primary and cell lines. 127 stable PDXs were established from 441 lung carcinomas representing all major histological subtypes: 52 adenocarcinomas, 62 squamous cell carcinomas, one adeno-squamous carcinoma, five sarcomatoid carcinomas, five large cell neuroendocrine carcinomas, and two small cell lung cancers. Somatic mutations, gene copy number and expression profiles, and pY-proteome landscape of 36 PDXs showed greater similarity with patient tumors than with established cell lines. Novel somatic mutations on cancer associated genes were identified but only in PDXs, likely due to selective clonal growth in the PDXs that allows detection of these low allelic frequency mutations. The results provide the strongest evidence yet that PDXs established from lung cancers closely mimic the characteristics of patient primary tumors.

Prognostic gene-expression signature of carcinoma-associated fibroblasts in non-small cell lung cancer.

The tumor microenvironment strongly influences cancer development, progression, and metastasis. The role of carcinoma-associated fibroblasts (CAFs) in these processes and their clinical impact has not been studied systematically in non-small cell lung carcinoma (NSCLC). We established primary cultures of CAFs and matched normal fibroblasts (NFs) from 15 resected NSCLC. We demonstrate that CAFs have greater ability than NFs to enhance the tumorigenicity of lung cancer cell lines. Microarray gene-expression analysis of the 15 matched CAF and NF cell lines identified 46 differentially expressed genes, encoding for proteins that are significantly enriched for extracellular proteins regulated by the TGF-ß signaling pathway. We have identified a subset of 11 genes (13 probe sets) that formed a prognostic gene-expression signature, which was validated in multiple independent NSCLC microarray datasets. Functional annotation using protein-protein interaction analyses of these and published cancer stroma-associated gene-expression changes revealed prominent involvement of the focal adhesion and MAPK signaling pathways. Fourteen (30%) of the 46 genes also were differentially expressed in laser-capture-microdissected corresponding primary tumor stroma compared with the matched normal lung. Six of these 14 genes could be induced by TGF-ß1 in NF. The results establish the prognostic impact of CAF-associated gene-expression changes in NSCLC patients.

Primary tumor xenografts of human lung adeno and squamous cell carcinoma express distinct proteomic signatures.

Nonsmall cell lung carcinoma (NSCLC) accounts for 80% of lung cancers. The most prevalent subtypes of NSCLC are adenocarcinoma (ADC) and squamous cell carcinoma (SCC), which combined account for approximately 90%. Ten resected NSCLC patient tumors (5 ADC and 5 SCC) were directly introduced into severely immune deficient (NOD-SCID) mice, and the resulting xenograft tumors were analyzed by standard histology and immunohistochemistry (IHC) and by proteomics profiling. Mass spectrometry (MS) methods involving 1- and 2-dimensional LC-MS/MS, and multiplexed selective reaction monitoring (SRM, or MRM), were applied to identify and quantify the xenograft proteomes. Hierarchical clustering of protein profiles distinguished between the ADC and SCC subtypes. The differential expression of 178 proteins, including a comprehensive panel of intermediate filament keratin proteins, was found to constitute a distinctive proteomic signature associated with the NSCLC subtypes. Epidermal growth factor receptor (EGFR) was expressed in ADC and SCC xenografts, and EGFR network activation was assessed by phosphotyrosine profiling by Western blot analysis and SRM measurement of EGFR levels, and mutation analysis. A multiplexed SRM/MRM method provided relative quantification of several keratin proteins, EGFR and plakophilin-1 in single LC-MS/MS runs. The protein quantifications by SRM and MS/MS spectral counting were associated with superior dynamic range and reproducibility but were otherwise consistent with orthogonal methods including IHC and Western immuno blotting. These findings illustrate the potential to develop a comprehensive MS-based platform in oncologic pathology for better classification and potentially treatment of NSCLC patients.

Genomic markers for malignant progression in pulmonary adenocarcinoma with bronchioloalveolar features.

Bronchioloalveolar carcinoma (BAC), a subtype of lung adenocarcinoma (ADC) without stromal, vascular, or pleural invasion, is considered an in situ tumor with a 100% survival rate. However, the histological criteria for invasion remain controversial. BAC-like areas may accompany otherwise invasive adenocarcinoma, referred to as mixed type adenocarcinoma with BAC features (AWBF). AWBF are considered to evolve from BAC, representing a paradigm for malignant progression in ADC. However, the supporting molecular evidence remains forthcoming. Here, we have studied the genomic changes of BAC and AWBF by array comparative genomic hybridization (CGH). We used submegabase-resolution tiling set array CGH to compare the genomic profiles of 14 BAC or BAC with focal area suspicious for invasion with those of 15 AWBF. Threshold-filtering and frequency-scoring analysis found that genomic profiles of noninvasive and focally invasive BAC are indistinguishable and show fewer aberrations than tumor cells in BAC-like areas of AWBF. These aberrations occurred mainly at the subtelomeric chromosomal regions. Increased genomic alterations were noted between BAC-like and invasive areas of AWBF. We identified 113 genes that best differentiated BAC from AWBF and were considered candidate marker genes for tumor invasion and progression. Correlative gene expression analyses demonstrated a high percentage of them to be poor prognosis markers in early stage ADC. Quantitative PCR also validated the amplification and overexpression of PDCD6 and TERT on chromosome 5p and the prognostic significance of PDCD6 in early stage ADC patients. We identified candidate genes that may be responsible for and are potential markers for malignant progression in AWBF.

Differential roles of cyclin D1 and D3 in pancreatic ductal adenocarcinoma.

BACKGROUND: The cyclin D1 (CCND1) and cyclin D3 (CCND3) are frequently co-overexpressed in pancreatic ductal adenocarcinoma (PDAC). Here we examine their differential roles in PDAC. RESULTS: CCND1 and CCND3 expression were selectively suppressed by shRNA in PDAC cell lines with expression levels of equal CCND1 and CCND3 (BxPC3), enhanced CCND1 (HPAC) or enhanced CCND3 (PANC1). Suppression of cell proliferation was greater with CCND3 than CCND1 downregulation. CCND3 suppression led to a reduced level of phosphorylated retinoblastoma protein (Ser795p-Rb/p110) and resulted in decreased levels of cyclin A mRNA and protein. A global gene expression analysis identified deregulated genes in D1- or D3-cyclin siRNA-treated PANC1 cells. The downregulated gene targets in CCND3 suppressed cells were significantly enriched in cell cycle associated processes (p < 0.005). In contrast, focal adhesion/actin cytoskeleton, MAPK and NF B signaling appeared to characterize the target genes and their interacting proteins in CCND1 suppressed PANC1 cells. CONCLUSIONS: Our results suggest that CCND3 is the primary driver of the cell cycle, in cooperation with CCND1 that integrates extracellular mitogenic signaling. We also present evidence that CCND1 plays a role in tumor cell migration. The results provide novel insights for common and differential targets of CCND1 and CCND3 overexpression during pancreatic duct cell carcinogenesis.

Validation of a histology-independent prognostic gene signature for early-stage, non-small-cell lung cancer including stage IA patients.

BACKGROUND: Patients with early-stage non-small-cell lung carcinoma (NSCLC) may benefit from treatments based on more accurate prognosis. A 15-gene prognostic classifier for NSCLC was identified from mRNA expression profiling of tumor samples from the NCIC CTG JBR.10 trial. In this study, we assessed its value in an independent set of cases. METHODS: Expression profiling was performed on RNA from frozen, resected tumor tissues corresponding to 181 stage I and II NSCLC cases collected at University Health Network (UHN181). Kaplan-Meier methodology was used to estimate 5-year overall survival probabilities, and the prognostic effect of the classifier was assessed using the log-rank test. A Cox proportional hazards model evaluated the signature's effect adjusting for clinical prognostic factors. RESULTS: Expression data of the 15-gene classifier stratified UHN181 cases into high- and low-risk subgroups with significantly different overall survival (hazard ratio [HR] = 1.92; 95% confidence interval [CI], 1.15-3.23; p = 0.012). In a subgroup analysis, this classifier predicted survival in 127 stage I patients (HR = 2.17; 95% CI, 1.12-4.20; p = 0.018) and the smaller subgroup of 48 stage IA patients (HR = 5.61; 95% CI, 1.19-26.45; p = 0.014). The signature was prognostic for both adenocarcinoma and squamous cell carcinoma cases (HR = 1.76, p = 0.058; HR = 4.19, p = 0.045, respectively). CONCLUSION: The prognostic accuracy of a 15-gene classifier was validated in an independent cohort of 181 early-stage NSCLC samples including stage IA cases and in different NSCLC histologic subtypes.

Prognostic gene expression signature for squamous cell carcinoma of lung.

PURPOSE: This study aimed to identify and validate a gene expression signature for squamous cell carcinoma of the lung (SQCC). EXPERIMENTAL DESIGN: A published microarray dataset from 129 SQCC patients was used as a training set to identify the minimal gene set prognostic signature. This was selected using the MAximizing R Square Algorithm (MARSA), a novel heuristic signature optimization procedure based on goodness-of-fit (R square). The signature was tested internally by leave-one-out-cross-validation (LOOCV), and then externally in three independent public lung cancer microarray datasets: two datasets of non-small cell lung cancer (NSCLC) and one of adenocarcinoma (ADC) only. Quantitative-PCR (qPCR) was used to validate the signature in a fourth independent SQCC cohort. RESULTS: A 12-gene signature that passed the internal LOOCV validation was identified. The signature was independently prognostic for SQCC in two NSCLC datasets (total n = 223) but not in ADC. The lack of prognostic significance in ADC was confirmed in the Director's Challenge ADC dataset (n = 442). The prognostic significance of the signature was validated further by qPCR in another independent cohort containing 62 SQCC samples (hazard ratio, 3.76; 95% confidence interval, 1.10-12.87; P = 0.035). CONCLUSIONS: We identified a novel 12-gene prognostic signature specific for SQCC and showed the effectiveness of MARSA to identify prognostic gene expression signatures.

Prognostic and predictive gene signature for adjuvant chemotherapy in resected non-small-cell lung cancer.

PURPOSE: The JBR.10 trial demonstrated benefit from adjuvant cisplatin/vinorelbine (ACT) in early-stage non-small-cell lung cancer (NSCLC). We hypothesized that expression profiling may identify stage-independent subgroups who might benefit from ACT. PATIENTS AND METHODS: Gene expression profiling was conducted on mRNA from 133 frozen JBR.10 tumor samples (62 observation [OBS], 71 ACT). The minimum gene set that was selected for the greatest separation of good and poor prognosis patient subgroups in OBS patients was identified. The prognostic value of this gene signature was tested in four independent published microarray data sets and by quantitative reverse-transcriptase polymerase chain reaction (RT-qPCR). RESULTS: A 15-gene signature separated OBS patients into high-risk and low-risk subgroups with significantly different survival (hazard ratio [HR], 15.02; 95% CI, 5.12 to 44.04; P < .001; stage I HR, 13.31; P < .001; stage II HR, 13.47; P < .001). The prognostic effect was verified in the same 62 OBS patients where gene expression was assessed by qPCR. Furthermore, it was validated consistently in four separate microarray data sets (total 356 stage IB to II patients without adjuvant treatment) and additional JBR.10 OBS patients by qPCR (n = 19). The signature was also predictive of improved survival after ACT in JBR.10 high-risk patients (HR, 0.33; 95% CI, 0.17 to 0.63; P = .0005), but not in low-risk patients (HR, 3.67; 95% CI, 1.22 to 11.06; P = .0133; interaction P < .001). Significant interaction between risk groups and ACT was verified by qPCR. CONCLUSION: This 15-gene expression signature is an independent prognostic marker in early-stage, completely resected NSCLC, and to our knowledge, is the first signature that has demonstrated the potential to select patients with stage IB to II NSCLC most likely to benefit from adjuvant chemotherapy with cisplatin/vinorelbine.

Understanding prognostic gene expression signatures in lung cancer.

In non-small-cell lung cancer (NSCLC), molecular profiling of tumors has led to the identification of gene expression patterns that are associated with specific phenotypes and prognosis. Such correlations could identify early-stage patients who are at increased risk of disease recurrence and death after complete surgical resection and who might benefit from adjuvant therapy. Profiling may also identify aberrant molecular pathways that might lead to specific molecularly targeted therapies. The technology behind the capturing and correlating of molecular profiles with clinical and biologic endpoints have evolved rapidly since microarrays were first developed a decade ago. In this review, we discuss multiple methods that have been used to derive prognostic gene expression signatures in NSCLC. Despite the diversity in the approaches used, 3 main steps are followed. First, the expression levels of several hundred to tens of thousands of genes are quantified by microarray or quantitative polymerase chain reaction techniques; the data are then preprocessed, normalized, and possibly filtered. In the second step, expression data are combined and grouped by clustering, risk score generation, or other means, to generate a gene signature that correlates with a clinical outcome, usually survival. Finally, the signature is validated in datasets of independent cohorts. This review discusses the concepts and methodologies involved in these analytical steps, primarily to facilitate the understanding of reports on large dataset gene expression studies that focus on prognostic signatures in NSCLC.

Three-gene prognostic classifier for early-stage non small-cell lung cancer.

PURPOSE: Several microarray studies have reported gene expression signatures that classify non-small-cell lung carcinoma (NSCLC) patients into different prognostic groups. However, the prognostic gene lists reported to date overlap poorly across studies, and few have been validated independently using more quantitative assay methods. PATIENTS AND METHODS: The expression of 158 putative prognostic genes identified in previous microarray studies was analyzed by reverse transcription quantitative polymerase chain reaction in the tumors of 147 NSCLC patients. Concordance indices and risk scores were used to identify a stage-independent set of genes that could classify patients with significantly different prognoses. RESULTS: We have identified a three-gene classifier (STX1A, HIF1A, and CCR7) for overall survival (hazard ratio = 3.8; 95% CI, 1.7 to 8.2; P < .001). The classifier was also able to stratify stage I and II patients and further improved the predictive ability of clinical factors such as histology and tumor stage. The predictive value of this three-gene classifier was validated in two large independent microarray data sets from Harvard and Duke Universities. CONCLUSION: We have identified a new three-gene classifier that is independent of and improves on stage to stratify early-stage NSCLC patients with significantly different prognoses. This classifier may be tested further for its potential value to improve the selection of resected NSCLC patients in adjuvant therapy.

Interaction between Oct3/4 and Cdx2 determines trophectoderm differentiation.

Trophectoderm (TE), the first differentiated cell lineage of mammalian embryogenesis, forms the placenta, a structure unique to mammalian development. The differentiation of TE is a hallmark event in early mammalian development, but molecular mechanisms underlying this first differentiation event remain obscure. Embryonic stem (ES) cells can be induced to differentiate into the TE lineage by forced repression of the POU-family transcription factor, Oct3/4. We show here that this event can be mimicked by overexpression of Caudal-related homeobox 2 (Cdx2), which is sufficient to generate proper trophoblast stem (TS) cells. Cdx2 is dispensable for trophectoderm differentiation induced by Oct3/4 repression but essential for TS cell self-renewal. In preimplantation embryos, Cdx2 is initially coexpressed with Oct3/4 and they form a complex for the reciprocal repression of their target genes in ES cells. This suggests that reciprocal inhibition between lineage-specific transcription factors might be involved in the first differentiation event of mammalian development.

Cdx2 is required for correct cell fate specification and differentiation of trophectoderm in the mouse blastocyst.

Blastocyst formation marks the segregation of the first two cell lineages in the mammalian preimplantation embryo: the inner cell mass (ICM) that will form the embryo proper and the trophectoderm (TE) that gives rise to the trophoblast lineage. Commitment to ICM lineage is attributed to the function of the two transcription factors, Oct4 (encoded by Pou5f1) and Nanog. However, a positive regulator of TE cell fate has not been described. The T-box protein eomesodermin (Eomes) and the caudal-type homeodomain protein Cdx2 are expressed in the TE, and both Eomes and Cdx2 homozygous mutant embryos die around the time of implantation. A block in early TE differentiation occurs in Eomes mutant blastocysts. However, Eomes mutant blastocysts implant, and Cdx2 and Oct4 expression are correctly restricted to the ICM TE. Blastocoel formation initiates in Cdx2 mutants but epithelial integrity is not maintained and embryos fail to implant. Loss of Cdx2 results in failure to downregulate Oct4 and Nanog in outer cells of the blastocyst and subsequent death of those cells. Thus, Cdx2 is essential for segregation of the ICM and TE lineages at the blastocyst stage by ensuring repression of Oct4 and Nanog in the TE.