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.

Introduction Microsatellite instability (MSI) testing and tumor mutational burden (TMB) are genomic biomarkers used to identify patients who are likely to benefit from immune checkpoint inhibitors. Pembrolizumab was recently approved by the Food and Drug Administration for use in TMB-high (TMB-H) tumors, regardless of histology, based on KEYNOTE-158. The primary objective of this retrospective study was real-world applicability and use of immunotherapy in TMB/MSI-high patients to lend credence to and refine this biomarker. Methods Charts of patients with advanced solid tumors who had MSI/TMB status determined by next generation sequencing (NGS) (FoundationOne CDx) were reviewed. Demographics, diagnosis, treatment history, and overall response rate (ORR) were abstracted. Progression-free survival (PFS) was determined from Kaplan–Meier curves. PFS1 (chemotherapy PFS) and PFS2 (immunotherapy PFS) were determined for patients who received immunotherapy after progressing on chemotherapy. The median PFS2/PFS1 ratio was recorded. Results MSI-high or TMB-H [≥20 mutations per megabase (mut/MB)] was detected in 157 adults with a total of 27 distinct tumor histologies. Median turnaround time for NGS was 73 days. ORR for most recent chemotherapy was 34.4%. ORR for immunotherapy was 55.9%. Median PFS for patients who received chemotherapy versus immunotherapy was 6.75 months (95% confidence interval, 3.9-10.9 months) and 24.2 months (95% confidence interval, 9.6 months to not reached), respectively ( P = 0.042). Median PFS2/PFS1 ratio was 4.7 in favor of immunotherapy. Conclusion This real-world study reinforces the use of TMB as a predictive biomarker. Barriers exist to the timely implementation of NGS-based biomarkers and more data are needed to raise awareness about the clinical utility of TMB. Clinicians should consider treating TMB-H patients with immunotherapy regardless of their histology.

Highlights d Lung squamous cell carcinoma has a moderate level of intratumor genetic heterogeneity d Transcriptomic heterogeneity impacts cancer pathways, driving phenotypic heterogeneity d Neo-epitope burden negatively correlates with immune infiltration d Non-genetic heterogeneity influences tumor evolutionary dynamics

Traditional preclinical studies of cancer therapeutics have relied on the use of established human cell lines that have been adapted to grow in the laboratory and, therefore, may deviate from the cancer they were meant to represent. With the emphasis of cancer drug development shifting from non-specific cytotoxic agents to rationally designed molecularly targeted therapies or immunotherapy comes the need for better models with predictive value regarding therapeutic activity and response in clinical trials. Recently, the diversity and accessibility of immunodeficient mouse strains has greatly enhanced the production and utility of patient-derived xenograft (PDX) models for many tumor types, including non-small cell lung cancer (NSCLC). Combined with next-generation sequencing, NSCLC PDX mouse models offer an exciting tool for drug development and for studying targeted therapies while utilizing patient samples with the hope of eventually aiding in clinical decision-making. Here, we describe NSCLC PDX mouse models generated by us and others, their ability to reflect the parental tumors’ histomorphological characteristics, as well as the effect of clonal selection and evolution on maintaining genomic integrity in low-passage PDXs compared to the donor tissue. We also raise vital questions regarding the practical utility of PDX and humanized PDX models in predicting patient response to therapy and make recommendations for addressing those questions. Once collaborations and standardized xenotransplantation and data management methods are established, NSCLC PDX mouse models have the potential to be universal and invaluable as a preclinical tool that guides clinical trials and standard therapeutic decisions.

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