Microsatellite instability in the high-grade dysplasia component of duodenal adenoma is associated with progression to adenocarcinoma.

PURPOSE: We examined the microsatellite instability of duodenal tumors to evaluate their molecular features associated with the adenoma-carcinoma sequence. METHODS: Fifty-two non-ampullary duodenal epithelial tumors collected by endoscopic mucosal resection or surgical resection were studied. When a tumor had two or more dysplasia grades, the highest grade was considered. Representative areas were macro-dissected and subjected to a microsatellite instability analysis and immunohistochemical staining. RESULTS: The 52 tumors were classified as either adenoma with low-grade dysplasia (n = 18), adenoma with high-grade dysplasia (n = 20), or adenocarcinomas (n = 14). Among these, 3 adenocarcinoma cases showed microsatellite instability and the remaining 49 tumors showed microsatellite stability. Of the 14 adenocarcinoma cases, 3 contained both high-grade dysplasia and adenocarcinoma components, and 11 contained only the adenocarcinoma component. Interestingly, all three adenocarcinoma + high-grade dysplasia cases were microsatellite instability-high in both the adenocarcinoma and high-grade dysplasia components. Immunohistochemical staining of mismatch repair proteins showed mismatch repair deficiency in three microsatellite instability-high adenocarcinoma + high-grade dysplasia cases. CONCLUSIONS: Only adenocarcinoma cases with high-grade dysplasia components were microsatellite instability-high (in both the adenocarcinoma and high-grade dysplasia components). This suggests that microsatellite instability in the high-grade dysplasia component of duodenal adenoma is associated with progression to adenocarcinoma.

Universal encoding of pan-cancer histology by deep texture representations.

Cancer histological images contain rich biological and clinical information, but quantitative representation can be problematic and has prevented the direct comparison and accumulation of large-scale datasets. Here, we show successful universal encoding of cancer histology by deep texture representations (DTRs) produced by a bilinear convolutional neural network. DTR-based, unsupervised histological profiling, which captures the morphological diversity, is applied to cancer biopsies and reveals relationships between histologic characteristics and the response to immune checkpoint inhibitors (ICIs). Content-based image retrieval based on DTRs enables the quick retrieval of histologically similar images using The Cancer Genome Atlas (TCGA) dataset. Furthermore, via comprehensive comparisons with driver and clinically actionable gene mutations, we successfully predict 309 combinations of genomic features and cancer types from hematoxylin-and-eosin-stained images. With its mounting capabilities on accessible devices, such as smartphones, universal encoding for cancer histology has a strong impact on global equalization for cancer diagnosis and therapies.

Focal adhesion ribonucleoprotein complex proteins are major humoral cancer antigens and targets in autoimmune diseases.

Despite the accumulating evidences of the significance of humoral cancer immunity, its molecular mechanisms have largely remained elusive. Here we show that B-cell repertoire sequencing of 102 clinical gastric cancers and molecular biological analyses unexpectedly reveal that the major humoral cancer antigens are not case-specific neo-antigens but are rather commonly identified as ribonucleoproteins (RNPs) in the focal adhesion complex. These common antigens are shared as autoantigens with multiple autoimmune diseases, suggesting a direct molecular link between cancer- and auto-immunity on the focal adhesion RNP complex. This complex is partially exposed to the outside of cancer cell surfaces, which directly evokes humoral immunity and enables functional bindings of antibodies to cancer cell surfaces in physiological conditions. These findings shed light on humoral cancer immunity in that it commonly targets cellular components fundamental for cytoskeletal integrity and cell movement, pointing to a novel modality of immunotherapy using humoral immunological reactions to cancers.

Colonic Neurogenic Lesion: An Admixture of Mucosal Neurofibromatous Lesion and Submucosal Ganglioneuromatous Lesion With Transition.

Benign neural tumors or tumor-like lesions are rarely detected in the gastrointestinal tract. In this article, we present the case of a neural lesion of the sigmoid colon, which was incidentally detected in a 68-year-old man treated with laparoscopic low anterior resection for an advanced carcinoma of the rectosigmoid junction. Within the resected specimen, a submucosal tumor-like protruding lesion was found in the sigmoid colon. Histologically, the growth was composed of mucosal neurofibromatous and submucosal ganglioneuromatous lesions, between which there was transition. Immunohistochemical analysis revealed a rupture of the perineurium in the area of transition, along with a proliferation of Schwann cells and supporting cells extending into the deep mucosa. This transition indicated that the mucosal and submucosal lesions comprised a single lesion, and that a diagnosis of neurofibroma or ganglioneuroma would be inadequate in this case. Because we could not classify it as an established single entity, we diagnosed the mass as an unclassifiable colonic neurogenic lesion. In summary, we report the case of an extremely rare occurrence of an unclassifiable colonic neurogenic lesion comprising an admixture of transitioning mucosal neurofibromatous and submucosal ganglioneuromatous lesions.

Capturing the differences between humoral immunity in the normal and tumor environments from repertoire-seq of B-cell receptors using supervised machine learning.

BACKGROUND: The recent success of immunotherapy in treating tumors has attracted increasing interest in research related to the adaptive immune system in the tumor microenvironment. Recent advances in next-generation sequencing technology enabled the sequencing of whole T-cell receptors (TCRs) and B-cell receptors (BCRs)/immunoglobulins (Igs) in the tumor microenvironment. Since BCRs/Igs in tumor tissues have high affinities for tumor-specific antigens, the patterns of their amino acid sequences and other sequence-independent features such as the number of somatic hypermutations (SHMs) may differ between the normal and tumor microenvironments. However, given the high diversity of BCRs/Igs and the rarity of recurrent sequences among individuals, it is far more difficult to capture such differences in BCR/Ig sequences than in TCR sequences. The aim of this study was to explore the possibility of discriminating BCRs/Igs in tumor and in normal tissues, by capturing these differences using supervised machine learning methods applied to RNA sequences of BCRs/Igs. RESULTS: RNA sequences of BCRs/Igs were obtained from matched normal and tumor specimens from 90 gastric cancer patients. BCR/Ig-features obtained in Rep-Seq were used to classify individual BCR/Ig sequences into normal or tumor classes. Different machine learning models using various features were constructed as well as gradient boosting machine (GBM) classifier combining these models. The results demonstrated that BCR/Ig sequences between normal and tumor microenvironments exhibit their differences. Next, by using a GBM trained to classify individual BCR/Ig sequences, we tried to classify sets of BCR/Ig sequences into normal or tumor classes. As a result, an area under the curve (AUC) value of 0.826 was achieved, suggesting that BCR/Ig repertoires have distinct sequence-level features in normal and tumor tissues. CONCLUSIONS: To the best of our knowledge, this is the first study to show that BCR/Ig sequences derived from tumor and normal tissues have globally distinct patterns, and that these tissues can be effectively differentiated using BCR/Ig repertoires.

Rapidly progressive miliary brain metastasis of lung cancer after EGFR tyrosine kinase inhibitor discontinuation: An autopsy report.

Miliary brain metastasis is a rare type of brain metastasis, in which carcinoma cells disseminate to numerous foci confined to Virchow-Robin/subpial spaces. Symptoms usually progress within several months, and magnetic resonance imaging (MRI) shows multiple small contrast-enhancing lesions. We report an autopsy case of a patient who rapidly deteriorated within a week due to miliary brain metastasis after epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) discontinuation, without contrast-enhancing lesions on MRI. A 74-year-old woman was diagnosed with stage IV lung adenocarcinoma with EGFR L868R mutation 2 years before presentation. Gefitinib, an EGFR-TKI was started. After 7 months, multiple new punctate contrast-enhancing lesions in the cerebral cortex appeared. After switching to another EGFR-TKI, erlotinib, these lesions disappeared. One year later, erlotinib was discontinued because of disease progression in the lung and docetaxel was initiated. Sixteen days later, cognitive decline appeared which rapidly progressed to bedridden state in 4 days. MRI showed multiple cortical small fluid-attenuated inversion recovery high intensity lesions which lacked contrast enhancement. The patient exhibited a state of akinetic mutism within a few days, and died 52 days after the appearance of neurological symptoms. The rapid progression indicated disease flare after EGFR-TKI discontinuation. Autopsy revealed numerous foci of metastasis in the cerebral cortex, basal ganglia, thalamus, and cerebellum, in which cancer cells were mostly confined to the Virchow-Robin/subpial spaces. These pathological findings were compatible with previous reports of miliary brain metastasis. Recent reports suggest that early disseminated cancer cells can survive for a long time and even remain after chemotherapy in supportive niches, and Virchow-Robin spaces are the niches in the brain. Our case suggests that these cancer cells may rapidly proliferate as a withdrawal burst after discontinuation of molecular targeted drugs, and show pathological findings of miliary brain metastasis.