RNA-binding proteins (RBPs) can recognize thousands of RNAs that help to maintain cell homeostasis, and RBP dysfunction is frequently observed in various cancers. However, whether specific RBPs are involved in tumor immune evasion by regulating programmed death ligand-1 (PD-L1) is unclear. Here, we perform targeted RBP CRISPR/Cas9 screening and identify density regulated re-initiation and release factor (DENR) as a PD-L1 regulator. DENR-depleted cancer cells exhibit reduced PD-L1 expression in vitro and in vivo. DENR depletion significantly suppresses tumor growth and enhances the tumor-killing activity of CD8⁺ T cells. Mechanistically, DENR antagonizes the translational repression of three consecutive upstream open reading frames (uORFs) upstream of Janus kinase 2 (Jak2); thus, DENR deficiency impairs JAK2 translation and the IFNγ-JAK-STAT signaling pathway, resulting in reduced PD-L1 expression in tumors. Overall, we discover an RBP DENR that could regulate PD-L1 expression for tumor immune evasion, and highlight the potential of DENR as a therapeutic target for immunotherapy.

Preoperative prediction of lateral lymph node metastasis is clinically crucial for guiding surgical strategy and prognosis assessment, yet precise prediction methods are lacking. We therefore develop Lateral Lymph Node Metastasis Network (LLNM-Net), a bidirectional-attention deep-learning model that fuses multimodal data (preoperative ultrasound images, radiology reports, pathological findings, and demographics) from 29,615 patients and 9836 surgical cases across seven centers. Integrating nodule morphology and position with clinical text, LLNM-Net achieves an Area Under the Curve (AUC) of 0.944 and 84.7% accuracy in multicenter testing, outperforming human experts (64.3% accuracy) and surpassing previous models by 7.4%. Here we show tumors within 0.25 cm of the thyroid capsule carry >72% metastasis risk, with middle and upper lobes as high-risk regions. Leveraging location, shape, echogenicity, margins, demographics, and clinician inputs, LLNM-Net further attains an AUC of 0.983 for identifying high-risk patients. The model is thus a promising for tool for preoperative screening and risk stratification.

Central lymph node metastasis (CNM) are highly prevalent but hard to detect preoperatively in papillary thyroid carcinoma (PTC) patients, while the significance of prophylactic compartment central lymph node dissection (CLND) remains controversial as a treatment option. We aim to establish a nomogram assessing risks of CNM in PTC patients, and explore whether prophylactic CLND should be recommended. One thousand four hundred thirty-eight patients from two clinical centers that underwent thyroidectomy with CLND for PTC within the period 2016-2019 were retrospectively analyzed. Univariate and multivariate analysis were performed to examine risk factors associated with CNM. A nomogram for predicting CNM was established, thereafter internally and externally validated. Seven variables were found to be significantly associated with CNM and were used to construct the model. These were as follows: thyroid capsular invasion (TCI), multifocality, creatinine (Cr) >70 μmol/L, age < 40, tumor size >1 cm, body mass index (BMI) < 22, and carcino-embryonic antigen (CEA) > 1 ng/ml. The nomogram had good discrimination with a concordance index (C-index) of 0.854 (95% confidence interval [CI], 0.843 to 0.867), supported by an external validation point estimate of 0.825 (95% CI, 0.793 to 0.857). A decision curve analysis (DCA) was made to evaluate nomogram and ultrasonography for predicting CNM. A validated nomogram utilizing readily available preoperative variables was developed to predict the probability of central lymph node metastases in patients presenting with PTC. This nomogram may help surgeons make appropriate surgical decisions in the management of PTC, especially in terms of whether prophylactic CLND is warranted.

Unveiling key oncogenic events in malignancies is the key to improving the prognosis and therapeutic outcome of malignancies. Lines of evidence have shown that super-enhancers control the expression of genes that determine the cell fate, but the oncogenic super-enhancers in colorectal cancer (CRC) and their impact on carcinogens remain largely unexplored. Here, we identified a new oncogenic super-enhancer-regulated gene, IL-20RA, in CRC. Using the integrative analysis of H3K27ac ChIP-seq and RNA-seq in CRC tumors and normal colon tissues, we obtained a series of oncogenic super-enhancers in CRC. We found that super-enhancer inhibition by JQ-1 or iBET-151 suppressed the growth of tumor cells and inhibited the expression of IL-20RA. We found that IL-20RA was highly expressed in the tumor tissue of CRC and related to the advanced stage. Further functional studies showed that knockdown of IL-20RA inhibited the growth and metastasis of CRC. In addition, we found that IL-20RA was involved in regulating oncogenic and immune pathways and affecting the expression of genes related to cell proliferation and immune evasion in CRC. Together, our study demonstrated a novel oncogene in CRC and shed new light on oncogenic super-enhancer contributions to cell proliferation and immune escape.