Many genes and signalling pathways controlling cell proliferation, death and differentiation, as well as genomic integrity, are involved in cancer development. New techniques, such as serial analysis of gene expression and cDNA microarrays, have enabled measurement of the expression of thousands of genes in a single experiment, revealing many new, potentially important cancer genes. These genome screening tools can comprehensively survey one tumor at a time; however, analysis of hundreds of specimens from patients in different stages of disease is needed to establish the diagnostic, prognostic and therapeutic importance of each of the emerging cancer gene candidates. Here we have developed an array-based high-throughput technique that facilitates gene expression and copy number surveys of very large numbers of tumors. As many as 1000 cylindrical tissue biopsies from individual tumors can be distributed in a single tumor tissue microarray. Sections of the microarray provide targets for parallel in situ detection of DNA, RNA and protein targets in each specimen on the array, and consecutive sections allow the rapid analysis of hundreds of molecular markers in the same set of specimens. Our detection of six gene amplifications as well as p53 and estrogen receptor expression in breast cancer demonstrates the power of this technique for defining new subgroups of tumors.

Multiple different oncogenes have been described previously to be amplified in breast cancer including HER2, EGFR, MYC, CCND1, and MDM2. Gene amplification results in oncogene overexpression but may also serve as an indicator of genomic instability. As such, presence of one or several gene amplifications may have prognostic significance. To assess the prognostic importance of amplifications and coamplifications of HER2, EGFR, MYC, CCND1, and MDM2 in breast cancer, we analyzed a breast cancer tissue microarray containing samples from 2197 cancers with follow-up information. Fluorescence in situ hybridizations revealed amplifications of CCND1 in 20.1%, HER2 in 17.3%, MDM2 in 5.7%, MYC in 5.3%, and EGFR in 0.8% of the tumors. All gene amplifications were significantly associated with high grade. HER2 (P < 0.001) and MYC amplification (P < 0.001) were also linked to shortened survival. In case of HER2, this was independent of grade, pT, and pN categories. MYC amplification was almost 3 times more frequent in medullary cancer (15.9%), than in the histologic subtype with the second highest frequency (ductal; 5.6%; P ‫؍‬ 0.0046). HER2 and MYC amplification were associated with estrogen receptor/progesterone receptor negativity (P < 0.001) whereas CCND1 amplification was linked to estrogen receptor/progesterone receptor positivity (P < 0.001). Coamplifications were more prevalent than expected based on the individual frequencies. Coamplifications of one or several other oncogenes occurred in 29.6% of CCND1, 43% of HER2, 55.7% of MDM2, 65% of MYC, and 72.8% of EGFR-amplified cancers. HER2/MYC-coamplified cancers had a worse prognosis than tumors with only one of these amplifications. Furthermore, a gradual decrease of survival was observed with increasing number of amplifications. In conclusion, these data support a major prognostic impact of genomic instability as determined by a broad gene amplification survey in breast cancer.

According to the clonal evolution model, tumour growth is driven by competing subclones in somatically evolving cancer cell populations, which gives rise to genetically heterogeneous tumours. Here we present a comparative targeted deep-sequencing approach combined with a customised statistical algorithm, called deepsnV, for detecting and quantifying subclonal single-nucleotide variants in mixed populations. We show in a rigorous experimental assessment that our approach is capable of detecting variants with frequencies as low as 1/10,000 alleles. In selected genomic loci of the TP53 and VHL genes isolated from matched tumour and normal samples of four renal cell carcinoma patients, we detect 24 variants at allele frequencies ranging from 0.0002 to 0.34. moreover, we demonstrate how the allele frequencies of known single-nucleotide polymorphisms can be exploited to detect loss of heterozygosity. our findings demonstrate that genomic diversity is common in renal cell carcinomas and provide quantitative evidence for the clonal evolution model.

A new WHO classification of renal cell carcinoma has been introduced in 2004. This classification includes the recently described renal cell carcinomas with the ASPL-TFE3 gene fusion and carcinomas with a PRCC-TFE3 gene fusion. Collectively, these tumors have been termed Xp11.2 or TFE3 translocation carcinomas, which primarily occur in children and young adults. To further study the characteristics of renal cell carcinoma in young patients and to determine their genetic background, 41 renal cell carcinomas of patients younger than 22 years were morphologically and genetically characterized. Loss of heterozygosity analysis of the von Hippel-Lindau gene region and screening for VHL gene mutations by direct sequencing were performed in 20 tumors. TFE3 protein overexpression, which correlates with the presence of a TFE3 gene fusion, was assessed by immunohistochemistry. Applying the new WHO classification for renal cell carcinoma, there were 6 clear cell (15%), 9 papillary (22%), 2 chromophobe, and 2 collecting duct carcinomas. Eight carcinomas showed translocation carcinoma morphology (20%). One carcinoma occurred 4 years after a neuroblastoma. Thirteen tumors could not be assigned to types specified by the new WHO classification: 10 were grouped as unclassified (24%), including a unique renal cell carcinoma with prominently vacuolated cytoplasm and WT1 expression. Three carcinomas occurred in combination with nephroblastoma. Molecular analysis revealed deletions at 3p25-26 in one translocation carcinoma, one chromophobe renal cell carcinoma, and one papillary renal cell carcinoma. There were no VHL mutations. Nuclear TFE3 overexpression was detected in 6 renal cell carcinomas, all of which showed areas with voluminous cytoplasm and foci of papillary architecture, consistent with a translocation carcinoma phenotype. The large proportion of TFE3 "translocation" carcinomas and "unclassified" carcinomas in the first two decades of life demonstrates that renal cell carcinomas in young patients contain genetically and phenotypically distinct tumors with further potential for novel renal cell carcinoma subtypes. The far lower frequency of clear cell carcinomas and VHL alterations compared with adults suggests that renal cell carcinomas in young patients have a unique genetic background.

Tertiary lymphoid structures (TLS) are associated with favorable outcome in non-metastatic colorectal carcinoma (nmCRC), but the dynamics of TLS maturation and its association with effective anti-tumor immune surveillance in nmCRC are unclear. Here, we hypothesized that not only the number of TLS but also their composition harbors information on recurrence risk in nmCRC. In a comprehensive molecular, tissue, laboratory, and clinical analysis of 109 patients with stage II/III nmCRC, we assessed TLS numbers and degree of maturation in surgical specimens by multi-parameter immunofluorescence of follicular dendritic cell (FDC) and germinal center (GC) markers. TLS formed in most tumors and were significantly more prevalent in highly-microsatellite-instable (MSI-H) and/or BRAF-mutant nmCRC. We could distinguish three sequential TLS maturation stages which were characterized by increasing prevalence of FDCs and mature B-cells: [1] Early TLS, composed of dense lymphocytic aggregates without FDCs, [2] Primary follicle-like TLS, having FDCs but no GC reaction, and [3] Secondary follicle-like TLS, having an active GC reaction. A simple integrated TLS immunoscore reflecting these parameters identified a large subgroup of nmCRC patients with a very low risk of recurrence independently of clinical co-variables such as ECOG performance status, age, stage, and adjuvant chemotherapy. We conclude that (1) mismatch repair and BRAF mutation status are associated with the formation of TLS in nmCRC, (2) TLS formation in nmCRC follows sequential maturation steps, culminating in germinal center formation, and (3) this maturation process harbors important prognostic information on the risk of disease recurrence.

Many genes and signaling pathways are involved in renal cell carcinoma (RCC) development. However, genetic tumor markers have not gained use in RCC diagnostics and prognosis prediction. Identification and evaluation of new molecular parameters are of utmost importance in cancer research and cancer treatment. Here we present a novel approach to rapidly identify clinically relevant molecular changes in cancer. To identify genes with relevance to RCC, a cDNA array analysis was first performed on 5184 cDNA clones on a filter to screen for genes with differential expression between the renal cancer cell line CRL-1933 and normal kidney tissue. There were 89 differentially expressed genes in the cancer cell line, one of them coding for vimentin, a cytoplasmic intermediate filament. In a second step, a renal cancer tissue microarray containing 532 RCC specimen was used to determine vimentin expression by immunohistochemistry. Vimentin expression was seen frequently in clear cell (51%) and papillary RCC (61%), but rarely in chromophobe RCC (4%) and oncocytomas (12%). Furthermore, vimentin expression was significantly associated with poor patient prognosis (P < 0.007) independent of grade and stage. These results obtained from minute arrayed tumor samples match well with previous findings on vimentin expression in renal tumors. It is concluded that the combination of tumor arrays and cDNA arrays is a powerful approach to rapidly identify and further evaluate genes that play a role in tumor biology.

The combination of cDNA and tissue microarray technologies enables rapid identification of genes associated with progression of prostate cancer to the hormone-refractory state and may facilitate analysis of the role of the encoded gene products in the pathogenesis of human prostate cancer.

Our data suggest that differences in HER-2 expression between primary tumors and their lymph node metastases cannot explain the high fraction of nonresponders to trastuzamab therapy.