Classification of tumours

Tumours are classified according to the most differentiated cells with the exception of carcinomas where a few tumour cells show neuroendocrine differentiation. In this case these cells are regarded as redifferentiated tumour cells, and the tumour is not classified as neuroendocrine. However, it is now clear that normal neuroendocrine cells can divide, and that continuous stimulation of such cells results in tumour formation, which during time becomes increasingly malignant. To understand tumourigenesis, it is of utmost importance to recognize the cell of origin of the tumour since knowledge of the growth regulation of that cell may give information about development and thus possible prevention and prophylaxis of the tumour. It may also have implications for the treatment. The successful treatment of gastrointestinal stromal tumours by a tyrosine kinase inhibitor is an example of the importance of a correct cellular classification of a tumour. In the future tumours should not just be classified as for instance adenocarcinomas of an organ, but more precisely as a carcinoma originating from a certain cell type of that organ

Identification of novel neuroendocrine-specific tumour genes

Neuroendocrine tumours (NETs) comprise a heterogenous group of malignancies with an often unpredictable course, and with limited treatment options. Thus, new diagnostic, prognostic, and therapeutic markers are needed. To shed new lights into the biology of NETs, we have by cDNA transcript profiling, sought to identify genes that are either up- or downregulated in NE as compared with non-NE tumour cells. A panel of six NET and four non-NET cell lines were examined, and out of 12 743 genes examined, we studied in detail the 200 most significantly differentially expressed genes in the comparison. In addition to potential new diagnostic markers (NEFM, CLDN4, PEROX2), the results point to genes that may be involved in the tumorigenesis (BEX1, TMEPAI, FOSL1, RAB32), and in the processes of invasion, progression and metastasis (MME, STAT3, DCBLD2) of NETs. Verification by real time qRT–PCR showed a high degree of consistency to the microarray results. Furthermore, the protein expression of some of the genes were examined. The results of our study has opened a window to new areas of research, by uncovering new candidate genes and proteins to be further investigated in the search for new prognostic, predictive, and therapeutic markers in NETs

New genetic signatures associated with cancer cachexia as defined by low skeletal muscle index and weight loss.

Background Cachexia affects the majority with advanced cancer. Based on current demographic and clinical factors, it is not possible to predict who will develop cachexia or not. Such variation may, in part, be due to genotype. It has recently been proposed to extend the diagnostic criteria for cachexia to include a direct measure of low skeletal muscle index (LSMI) in addition to weight loss (WL). We aimed to explore our panel of candidate single nucleotide polymorphism (SNPs) for association with WL +/− computerized tomography‐defined LSMI. We also explored whether the transcription in muscle of identified genes was altered according to such cachexia phenotype Methods A retrospective cohort study design was used. Analysis explored associations of candidate SNPs with WL (n = 1276) and WL + LSMI (n = 943). Human muscle transcriptome (n = 134) was analysed using an Agilent platform. Results Single nucleotide polymorphisms in the following genes showed association with WL alone: GCKR, LEPR, SELP, ACVR2B, TLR4, FOXO3, IGF1, CPN1, APOE, FOXO1, and GHRL. SNPs in LEPR, ACVR2B, TNF, and ACE were associated with concurrent WL + LSMI. There was concordance between muscle‐specific expression for ACVR2B, FOXO1 and 3, LEPR, GCKR, and TLR4 genes and LSMI and/or WL (P < 0.05). Conclusions The rs1799964 in the TNF gene and rs4291 in the ACE gene are new associations when the definition of cachexia is based on a combination of WL and LSMI. These findings focus attention on pro‐inflammatory cytokines and the renin–angiotensin system as biomarkers/mediators of muscle wasting in cachexia