Deep learning-based predictions of clear and eosinophilic phenotypes in clear cell renal cell carcinoma.

We have recently shown that histological phenotypes focusing on clear and eosinophilic cytoplasm in clear cell renal cell carcinoma (ccRCC) correlated with prognosis and the response to angiogenesis inhibition and checkpoint blockade. This study aims to objectively show the diagnostic utility of clear or eosinophilic phenotypes of ccRCC by developing an artificial intelligence (AI) model using the TCGA-ccRCC dataset and to demonstrate if the clear or eosinophilic predicted phenotypes correlate with pathological factors and gene signatures associated with angiogenesis and cancer immunity. Before the development of the AI model, histological evaluation using hematoxylin and eosin whole-slide images of the TCGA-ccRCC cohort (n = 435) was performed by a urologic pathologist. The AI model was developed as follows. First, the highest-grade area on each whole slide image was captured for image processing. Second, the selected regions were cropped into tiles. Third, the AI model was trained using transfer learning on a deep convolutional neural network, and clear or eosinophilic predictions were scaled as AI scores. Next, we verified the AI model using a validation cohort (n = 95). Finally, we evaluated the accuracy of the prognostic predictions of the AI model and revealed that the AI model detected clear and eosinophilic phenotypes with high accuracy. The AI model stratified the patients' outcomes, and the predicted eosinophilic phenotypes correlated with adverse clinicopathological characteristics and high immune-related gene signatures. In conclusion, the AI-based histologic subclassification accurately predicted clear or eosinophilic phenotypes of ccRCC, allowing for consistently reproducible stratification for prognostic and therapeutic stratification.

Biclonal Gammopathy as a Misleading Indicator to Diagnose POEMS Syndrome: An Autopsy Case Report and a Review of the Literature.

A 76-year-old man presented with a four-month history of progressive bilateral lower limb muscle weakness and dysesthesia. The patient had extravascular volume overload, and laboratory findings confirmed hypothyroidism, renal dysfunction, and chronic inflammation. Serum protein and immunofixation electrophoresis revealed biclonality of immunoglobulin A (IgA)-kappa and IgA-lambda, which was attributed to chronic inflammation. Subsequently, we detected the proliferation of monoclonal plasma cells in the bone marrow, which led to a diagnosis of POEMS syndrome. Despite the initiation of chemotherapy, the patient died of aspiration pneumonia. In this case, biclonal gammopathy in peripheral blood delayed a diagnosis of POEMS syndrome.