Quantification of HLA class I molecules on renal cell carcinoma using Edman degradation

<p>Abstract</p> <p>Background</p> <p>Unimpaired HLA class I antigen presentation is a prerequisite for the recognition of tumor cells by cytotoxic T lymphocytes and thus essential for the success of anticancer immunotherapeutic concepts. Several approaches have been taken in the immunotherapy of metastatic renal cell carcinoma (RCC), however of limited success. HLA loss or down-regulation have often been reported and might interfere with immunotherapeutic approaches aimed at the recognition of HLA-presented peptides.</p> <p>Methods</p> <p>We employed a quantitative method of molecular analysis for the comparison of HLA amounts on primary tumor, normal kidney and metastases of RCC, using Edman degradation. We analyzed a series of 47 RCC samples including corresponding renal parenchyma, local lymph node metastases and distant metastases.</p> <p>Results</p> <p>Results of quantitative Edman degradation revealed significantly higher HLA yields on primary tumor and metastases compared to normal kidney tissue. This effect was shown not to result from infiltrating immune cells, since tumor-infiltrating lymphocytes had no influence on the overall HLA recovery from tumor tissue. Unexpectedly, we found a higher amount of HLA class I molecules on distant metastases compared to local lymph node metastases.</p> <p>Conclusion</p> <p>Edman degradation allows the direct quantitative comparison of HLA class I protein expression by tumor or normal tissue and metastases of RCC patients. Our results raise hopes for improving the success and effectiveness of future immunotherapeutic concepts for metastatic RCC.</p

Analyst information precision and small earnings surprises

This study proposes and tests an alternative to the extant earnings management explanation for zero and small positive earnings surprises (i.e., analyst forecast errors). We argue that analysts’ ability to strategically induce slight pessimism in earnings forecasts varies with the precision of their information. Accordingly, we predict that the probability that a firm reports a small positive instead of a small negative earnings surprise is negatively related to earnings forecast uncertainty, and we present evidence consistent with this prediction. Our findings have important implications for the earnings management interpretation of the asymmetry around zero in the frequency distribution of earnings surprises. We demonstrate how empirically controlling for earnings forecast uncertainty can materially change inferences in studies that employ the incidence of zero and small positive earnings surprises to categorize firms as suspected of managing earnings

Caldera size modulated by the yield stress within a crystal-rich magma reservoir

The largest volcanic eruptions in the geologic record have no analogue in the historical record. These eruptions had global impacts1,2, but are known only through their eruptive products. They have left behind calderas that formed as the surface collapsed when eruption evacuated magma chambers at 5–15 km depths3,4. It is generally assumed that calderas reflect the spatial dimensions of underlying magma reservoirs. Here we use a numerical model of conduit flow and dynamic magma-chamber drainage to show that caldera size can be affected by the material properties of crystal-rich silicic magma. We find that magma in the chamber can experience a rheological transition during eruption. This transition causes magma near the conduit to behave as a fluid, whereas magma farther away behaves elastically and remains locked. The intervening surface—the yield surface—expands through the chamber as eruption progresses. If a yielding transition occurs, calderas can form before complete mobilization of the entire reservoir. The resulting distribution of eruption volumes is then bimodal, as observed in the geologic record. We suggest that the presence or absence of a magma yield stress determines whether caldera size reflects the true spatial extent of magma storage