Tumor susceptibility gene 101 (Tsg101) was identified in a random mutagenesis screen for potential tumor suppressors in NIH 3T3 cells. Altered transcripts of this gene have been detected in sporadic breast cancers and many other human malignancies. However, the involvement of this gene in neoplastic transformation and tumorigenesis is still elusive. Using gene targeting, we generated genetically engineered mice with a floxed allele of Tsg101. We investigated essential functions of this gene in vivo and examined whether the loss of function of Tsg101 results in tumorigenesis. Conventional knockout mice were generated through Cre-mediated excision of the first coding exon in the germ line of mouse mammary tumor virus (MMTV)-Cre transgenic mice. The complete ablation of Tsg101 in the developing embryo resulted in death around implantation. In contrast, mammary gland-specific knockout mice developed normally but were unable to nurse their young as a result of impaired mammogenesis during late pregnancy. Neither heterozygous null mutants nor somatic knockout mice developed mammary tumors after a latency of 2 years. The Cre-mediated deletion of Tsg101 in primary cells demonstrated that this gene is essential for the growth, proliferation, and survival of mammary epithelial cells. In summary, our results suggest that Tsg101 is required for normal cell function of embryonic and adult tissues but that this gene is not a tumor suppressor for sporadic forms of breast cancer.

Although a subset of clear cell renal cell carcinoma (ccRCC) patients respond to immune checkpoint blockade (ICB), predictors of response remain uncertain. We investigated whether abnormal expression of endogenous retroviruses (ERVs) in tumors is associated with local immune checkpoint activation (ICA) and response to ICB. Twenty potentially immunogenic ERVs (πERVs) were identified in ccRCC in The Cancer Genome Atlas data set, and tumors were stratified into 3 groups based on their expression levels. πERV-high ccRCC tumors showed increased immune infiltration, checkpoint pathway upregulation, and higher CD8+ T cell fraction in infiltrating leukocytes compared with πERV-low ccRCC tumors. Similar results were observed in ER+/HER2- breast, colon, and head and neck squamous cell cancers. ERV expression correlated with expression of genes associated with histone methylation and chromatin regulation, and πERV-high ccRCC was enriched in BAP1 mutant tumors. ERV3-2 expression correlated with ICA in 11 solid cancers, including the 4 named above. In a small retrospective cohort of 24 metastatic ccRCC patients treated with single-agent PD-1/PD-L1 blockade, ERV3-2 expression in tumors was significantly higher in responders compared with nonresponders. Thus, abnormal expression of πERVs is associated with ICA in several solid cancers, including ccRCC, and ERV3-2 expression is associated with response to ICB in ccRCC.

Spontaneous regression͞complete resistance (SR͞CR) mice resist very high doses of cancer cells that are lethal to WT mice even at low doses. In this study, we show that this resistance is mediated by rapid infiltration of leukocytes, mostly of innate immunity, in both primary and repeated challenges. Formation of rosettes with infiltrating natural killer cells, neutrophils, and macrophages was required for the subsequent destruction of cancer cells through rapid cytolysis. Highly purified natural killer cells, macrophages, and neutrophils from the SR͞CR mice independently killed cancer cells in vitro. The independent killing activity by each subset of effector cells is consistent with the observation that the resistance was abolished by depleting total infiltrating leukocytes but not by depleting only one or two subsets of leukocytes. The resistance was completely transferable to WT recipient mice through SR͞CR splenocytes, bone marrow cells, or enriched peritoneal macrophages, either for prevention against subsequent cancer challenges or eradication of established malignancy at distant sites. cellular cancer immunity ͉ adoptive transfer ͉ cancer therapy ͉ macrophages ͉ leukocyte depletion

Nuclei segmentation is a fundamental task in histopathology image analysis. Typically, such segmentation tasks require significant effort to manually generate accurate pixel-wise annotations for fully supervised training. To alleviate such tedious and manual effort, in this paper we propose a novel weakly supervised segmentation framework based on partial points annotation, i.e., only a small portion of nuclei locations in each image are labeled. The framework consists of two learning stages. In the first stage, we design a semi-supervised strategy to learn a detection model from partially labeled nuclei locations. Specifically, an extended Gaussian mask is designed to train an initial model with partially labeled data. Then, selftraining with background propagation is proposed to make use of the unlabeled regions to boost nuclei detection and suppress false positives. In the second stage, a segmentation model is trained from the detected nuclei locations in a weakly-supervised fashion. Two types of coarse labels with complementary information are derived from the detected points and are then utilized to train a deep neural network. The fully-connected conditional random field loss is utilized in training to further refine the model without introducing extra computational complexity during inference. The proposed method is extensively evaluated on two nuclei segmentation datasets. The experimental results demonstrate that our method can achieve competitive performance compared to the fully supervised counterpart and the state-of-the-art methods while requiring significantly less annotation effort.