ROR1, an embryonic protein with an emerging role in cancer biology

Receptor tyrosine kinase-like orphan receptor 1 (ROR1) is a member of the ROR family consisting of ROR1 and ROR2. RORs contain two distinct extracellular cysteine-rich domains and one transmembrane domain. Within the intracellular portion, ROR1 possesses a tyrosine kinase domain, two serine/threonine-rich domains and a proline-rich domain. RORs have been studied in the context of embryonic patterning and neurogenesis through a variety of homologs. These physiologic functions are dichotomous based on the requirement of the kinase domain. A growing literature has established ROR1 as a marker for cancer, such as in CLL and other blood malignancies. In addition, ROR1 is critically involved in progression of a number of blood and solid malignancies. ROR1 has been shown to inhibit apoptosis, potentiate EGFR signaling, and induce epithelial-mesenchymal transition (EMT). Importantly, ROR1 is only detectable in embryonic tissue and generally absent in adult tissue, making the protein an ideal drug target for cancer therapy

TRGAted: A web tool for survival analysis using protein data in the Cancer Genome Atlas. [version 1; referees: 2 approved]

Reverse-phase protein arrays (RPPAs) are a highthroughput approach to protein quantification utilizing an antibody-based micro-to-nano scale dot blot. Within the Cancer Genome Atlas (TCGA), RPPAs were used to quantify over 200 proteins in 8,167 tumor or metastatic samples. This protein-level data has particular advantages in assessing putative prognostic or therapeutic targets in tumors. However, many of the available pipelines do not allow for the partitioning of clinical and RPPA information to make meaningful conclusions. We developed a cloud-based application, TRGAted to enable researchers to better examine survival based on single or multiple proteins across 31 cancer types in the TCGA. TRGAted contains up-to-date overall survival, disease-specific survival, disease-free interval and progression-free interval information. Furthermore, survival information for primary tumor samples can be stratified based on gender, age, tumor stage, histological type, and subtype, allowing for highly adaptive and intuitive user experience. The code and processed data is open sourced and available on github  and with a tutorial built into the application for assisting users

Histone demethylase PHF8 promotes epithelial to mesenchymal transition and breast tumorigenesis

Histone demethylase PHF8 is upregulated and plays oncogenic roles in various cancers; however, the mechanisms underlying its dysregulation and functions in carcinogenesis remain obscure. Here, we report the novel functions of PHF8 in EMT (epithelial to mesenchymal transition) and breast cancer development. Genome-wide gene expression analysis revealed that PHF8 overexpression induces an EMT-like process, including the upregulation of SNAI1 and ZEB1. PHF8 demethylates H3K9me1, H3K9me2 and sustains H3K4me3 to prime the transcriptional activation of SNAI1 by TGF-β signaling. We show that PHF8 is upregulated and positively correlated with MYC at protein levels in breast cancer. MYC post-transcriptionally regulates the expression of PHF8 via the repression of microRNAs. Specifically, miR-22 directly targets and inhibits PHF8 expression, and mediates the regulation of PHF8 by MYC and TGF-β signaling. This novel MYC/microRNAs/PHF8 regulatory axis thus places PHF8 as an important downstream effector of MYC. Indeed, PHF8 contributes to MYC-induced cell proliferation and the expression of EMT-related genes. We also report that PHF8 plays important roles in breast cancer cell migration and tumor growth. These oncogenic functions of PHF8 in breast cancer confer its candidacy as a promising therapeutic target for this disease

Fluoromodule-based reporter/probes designed for in vivo fluorescence imaging

Optical imaging of whole, living animals has proven to be a powerful tool in multiple areas of preclinical research and has allowed noninvasive monitoring of immune responses, tumor and pathogen growth, and treatment responses in longitudinal studies. However, fluorescence-based studies in animals are challenging because tissue absorbs and autofluoresces strongly in the visible light spectrum. These optical properties drive development and use of fluorescent labels that absorb and emit at longer wavelengths. Here, we present a far-red absorbing fluoromodule-based reporter/probe system and show that this system can be used for imaging in living mice. The probe we developed is a fluorogenic dye called SC1 that is dark in solution but highly fluorescent when bound to its cognate reporter, Mars1. The reporter/probe complex, or fluoromodule, produced peak emission near 730 nm. Mars1 was able to bind a variety of structurally similar probes that differ in color and membrane permeability. We demonstrated that a tool kit of multiple probes can be used to label extracellular and intracellular reporter-tagged receptor pools with 2 colors. Imaging studies may benefit from this far-red excited reporter/probe system, which features tight coupling between probe fluorescence and reporter binding and offers the option of using an expandable family of fluorogenic probes with a single reporter gene

ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models

Large language models (LLMs) have recently demonstrated remarkable capabilities to comprehend human intentions, engage in reasoning, and design planning-like behavior. To further unleash the power of LLMs to accomplish complex tasks, there is a growing trend to build agent framework that equips LLMs, such as ChatGPT, with tool-use abilities to connect with massive external APIs. In this work, we introduce ModelScope-Agent, a general and customizable agent framework for real-world applications, based on open-source LLMs as controllers. It provides a user-friendly system library, with customizable engine design to support model training on multiple open-source LLMs, while also enabling seamless integration with both model APIs and common APIs in a unified way. To equip the LLMs with tool-use abilities, a comprehensive framework has been proposed spanning over tool-use data collection, tool retrieval, tool registration, memory control, customized model training, and evaluation for practical real-world applications. Finally, we showcase ModelScopeGPT, a real-world intelligent assistant of ModelScope Community based on the ModelScope-Agent framework, which is able to connect open-source LLMs with more than 1000 public AI models and localized community knowledge in ModelScope. The ModelScope-Agent library\footnote{https://github.com/modelscope/modelscope-agent} and online demo\footnote{https://modelscope.cn/studios/damo/ModelScopeGPT/summary} are now publicly available

Mapping the immune environment in clear cell renal carcinoma by single-cell genomics

Clear cell renal cell carcinoma (ccRCC) is one of the most immunologically distinct tumor types due to high response rate to immunotherapies, despite low tumor mutational burden. To characterize the tumor immune microenvironment of ccRCC, we applied single-cell-RNA sequencing (SCRS) along with T-cell-receptor (TCR) sequencing to map the transcriptomic heterogeneity of 25,688 individual CD4