Value of antibodies to free light chains in immunoperoxidase studies of renal biopsies

Aims Because immunoglobulin abnormalities may affect the kidney, investigation of renal biopsies requires immunohistological study of light chains. A problem is that most antibodies to light chains react with whole immunoglobulins as well as free light chains, and there are generally many more whole immunoglobulins than free light chains. The usefulness of antibodies that only detected free light chains was investigated. Methods Antibodies to free light chains were used in an immunoperoxidase method on paraffin sections of 198 renal biopsies, and compared with conventional antibodies against light chains examined by immunofluorescence on 13 frozen sections and by immunoperoxidase on 46 paraffin sections. Results Immunofluorescence and immunoperoxidase were concordant on 10 of 13 biopsies. Immunofluorescence detected slight deposition of light chains in three biopsies not shown by immunoperoxidase, of undetermined clinical significance. Using immunoperoxidase, the free light chain antibodies were more sensitive than conventional antibodies, giving much cleaner staining and better detection of deposits in AL amyloid, light chain deposition disease and cryoglobulinaemic glomerulonephritis. The free light chain antibodies showed discordance or ambiguity between immunohistological and clinical findings in seven (4%) of 185 patients with known immunoglobulin status. These included two of 28 cases of AL amyloid that showed no light chain deposition. The method was not designed for detection of light chain restriction in neoplastic plasma or lymphoplasmacytic cells. Conclusions Polyclonal antibodies to free light chains are an improvement on conventional antibodies in immunoperoxidase study of paraffin sections of renal biopsies and are useful in everyday practice

No relationship between thymidine phosphorylase (TP, PD-ECGF) expression and hypoxia in carcinoma of the cervix

The expression of hypoxia-regulated genes promotes an aggressive tumour phenotype and is associated with an adverse cancer treatment outcome. Thymidine phosphorylase (TP) levels increase under hypoxia, but the protein has not been studied in association with hypoxia in human tumours. An investigation was made, therefore, of the relationship of tumour TP with hypoxia, the expression of other hypoxia-associated markers and clinical outcome. This retrospective study was carried out in patients with locally advanced cervical carcinoma who underwent radiotherapy. Protein expression was evaluated with immunohistochemistry. Hypoxia was measured using microelectrodes and the level of pimonidazole binding. There was no relationship of TP expression with tumour pO2 (r=−0.091, P=0.59, n=87) or pimonidazole binding (r=0.13, P=0.45, n=38). There was no relationship between TP and HIF-1α, but there was a weak borderline significant relationship with HIF-2α expression. There were weak but significant correlations of TP with the expression of VEGF, CA IX and Glut-1. In 119 patients, the presence of TP expression predicted for disease-specific (P=0.032) and metastasis-free (P=0.050) survival. The results suggest that TP is not a surrogate marker of hypoxia, but is linked to the expression of hypoxia-associated genes and has weak prognostic power

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases