Depletion of regulatory T cells enhancing the anti-tumor effect of in situ vaccination in solid tumors.

The emergence of immune checkpoint inhibitors (ICIs) has revolutionized the clinical treatment for tumor. However, the low response rate of ICIs remains the major obstacle for curing patients and effective approaches for patients with primary or secondary resistance to ICIs remain lacking. In this study, immune stimulating agent unmethylated CG-enriched (CpG) oligodeoxynucleotide (ODN) was locally injected into the tumor to trigger a robust immune response to eradicate cancer cells, while anti-CD25 antibody was applied to remove immunosuppressive regulatory T cells, which further enhanced the host immune activity to attack tumor systematically. The combination of CpG and anti-CD25 antibody obtained notable regression in mouse melanoma model. Furthermore, rechallenge of tumor cells in the xenograft model has resulted in smaller tumor volume, which demonstrated that the combinational treatment enhanced the activity of memory T cells. Remarkably, this combinational therapy presented significant efficacy on multiple types of tumors as well and was able to prevent relapse of tumor partially. Taken together, our combinational immunotherapy provides a new avenue to enhance the clinical outcomes of patients who are insensitive or resistant to ICIs treatments.

Tumor-selective activity of RAS-GTP inhibition in pancreatic cancer.

Broad-spectrum RAS inhibition holds the potential to benefit roughly a quarter of human cancer patients whose tumors are driven by RAS mutations1,2. RMC-7977 is a highly selective inhibitor of the active GTP-bound forms of KRAS, HRAS, and NRAS, with affinity for both mutant and wild type (WT) variants (RAS(ON) multi-selective)3. As >90% of human pancreatic ductal adenocarcinoma (PDAC) cases are driven by activating mutations in KRAS4, we assessed the therapeutic potential of the RAS(ON) multi-selective inhibitor RMC-7977 in a comprehensive range of PDAC models. We observed broad and pronounced anti-tumor activity across models following direct RAS inhibition at exposures that were well-tolerated in vivo. Pharmacological analyses revealed divergent responses to RMC-7977 in tumor versus normal tissues. Treated tumors exhibited waves of apoptosis along with sustained proliferative arrest whereas normal tissues underwent only transient decreases in proliferation, with no evidence of apoptosis. In the autochthonous KPC model, RMC-7977 treatment resulted in a profound extension of survival followed by on-treatment relapse. Analysis of relapsed tumors identified Myc copy number gain as a prevalent candidate resistance mechanism, which could be overcome by combinatorial TEAD inhibition in vitro. Together, these data establish a strong preclinical rationale for the use of broad-spectrum RAS-GTP inhibition in the setting of PDAC and identify a promising candidate combination therapeutic regimen to overcome monotherapy resistance.

Metastatic site influences driver gene function in pancreatic cancer.

Driver gene mutations can increase the metastatic potential of the primary tumor1-3, but their role in sustaining tumor growth at metastatic sites is poorly understood. A paradigm of such mutations is inactivation of SMAD4 - a transcriptional effector of TGFß signaling - which is a hallmark of multiple gastrointestinal malignancies4,5. SMAD4 inactivation mediates TGFß's remarkable anti- to pro-tumorigenic switch during cancer progression and can thus influence both tumor initiation and metastasis6-14. To determine whether metastatic tumors remain dependent on SMAD4 inactivation, we developed a mouse model of pancreatic ductal adenocarcinoma (PDAC) that enables Smad4 depletion in the pre-malignant pancreas and subsequent Smad4 reactivation in established metastases. As expected, Smad4 inactivation facilitated the formation of primary tumors that eventually colonized the liver and lungs. By contrast, Smad4 reactivation in metastatic disease had strikingly opposite effects depending on the tumor's organ of residence: suppression of liver metastases and promotion of lung metastases. Integrative multiomic analysis revealed organ-specific differences in the tumor cells' epigenomic state, whereby the liver and lungs harbored chromatin programs respectively dominated by the KLF and RUNX developmental transcription factors, with Klf4 depletion being sufficient to reverse Smad4's tumor-suppressive activity in liver metastases. Our results show how epigenetic states favored by the organ of residence can influence the function of driver genes in metastatic tumors. This organ-specific gene-chromatin interplay invites consideration of anatomical site in the interpretation of tumor genetics, with implications for the therapeutic targeting of metastatic disease.

Proteomic characterization of esophageal squamous cell carcinoma response to immunotherapy reveals potential therapeutic strategy and predictive biomarkers.

Immunotherapy is the first-line therapy for esophageal squamous cell carcinoma (ESCC), yet many patients do not respond due to drug resistance and the lack of reliable predictive markers. We collected 73 ESCC patients (including discovery cohort and validation cohort) without immune thrombocytopenia and undergoing anti-PD1 immunotherapy. Proteomic and phosphoproteomic analysis of 73 ESCC treatment-naive samples by mass spectrometry-based label-free quantification were applied to explore the potential resistant and sensitive mechanisms, and identify predictive markers of ESCC immunotherapy. Comparative analysis found the pathways related to immune and mitochondrial functions were associated with ESCC immunotherapy sensitivity; while platelet activation bioprocess showed negative correlation with CD8+ T cells and related to ESCC immunotherapy non-sensitivity. Finally, we identified 10 ESCC immunotherapy predictive biomarkers with high accuracy (≥ 0.90) to predict the immunotherapeutic response, which was validated in the independent cohort.

Somatic mouse models of gastric cancer reveal genotype-specific features of metastatic disease.

Metastatic gastric carcinoma is a highly lethal cancer that responds poorly to conventional and molecularly targeted therapies. Despite its clinical relevance, the mechanisms underlying the behavior and therapeutic response of this disease are poorly understood owing, in part, to a paucity of tractable models. Here we developed methods to somatically introduce different oncogenic lesions directly into the murine gastric epithelium. Genotypic configurations observed in patients produced metastatic gastric cancers that recapitulated the histological, molecular and clinical features of all nonviral molecular subtypes of the human disease. Applying this platform to both wild-type and immunodeficient mice revealed previously unappreciated links between the genotype, organotropism and immune surveillance of metastatic cells, which produced distinct patterns of metastasis that were mirrored in patients. Our results establish a highly portable platform for generating autochthonous cancer models with flexible genotypes and host backgrounds, which can unravel mechanisms of gastric tumorigenesis or test new therapeutic concepts.

SMCC: A Novel Clustering Method for Single- and Multi-Omics Data Based on Co-Regularized Network Fusion.

Clustering is a common technique for statistical data analysis and is essential for developing precision medicine. Numerous computational methods have been proposed for integrating multi-omics data to identify cancer subtypes. However, most existing clustering models based on network fusion fail to preserve the consistency of the distribution of the data before and after fusion. Motivated by this observation, we would like to measure and minimize the distribution difference between networks, which may not be in the same space, to improve the performance of data fusion. We were therefore motivated to develop a flexible clustering model, based on network fusion, that minimizes the distribution difference between the data before and after fusion by co-regularization; the model can be applied to both single- and multi-omics data. We propose a new network fusion model for single- and multi-omics data clustering for identifying cancer or cell subtypes based on co-regularized network fusion (SMCC). SMCC integrates low-rank subspace representation and entropy to fuse networks. In addition, it measures and minimizes the distribution difference between the similarity networks and the fusion network by co-regularization. The model can both reduce the noise interference in the source data and make the statistical characteristics of the fusion result closer to those of the source data. We evaluated the clustering performance of SMCC across 16 real single- and multi-omics dataset. The experimental results demonstrated that SMCC is superior to 17 state-of-the-art clustering methods. Moreover, it is effective for identifying cancer or cell subtypes, thereby promoting the development of precision medicine.

SGAE-MDA: Exploring the MiRNA-disease associations in herbal medicines based on semi-supervised graph autoencoder.

Research indicates that miRNAs present in herbal medicines are crucial for identifying disease markers, advancing gene therapy, facilitating drug delivery, and so on. These miRNAs maintain stability in the extracellular environment, making them viable tools for disease diagnosis. They can withstand the digestive processes in the gastrointestinal tract, positioning them as potential carriers for specific oral drug delivery. By engineering plants to generate effective, non-toxic miRNA interference sequences, it's possible to broaden their applicability, including the treatment of diseases such as hepatitis C. Consequently, delving into the miRNA-disease associations (MDAs) within herbal medicines holds immense promise for diagnosing and addressing miRNA-related diseases. In our research, we propose the SGAE-MDA model, which harnesses the strengths of a graph autoencoder (GAE) combined with a semi-supervised approach to uncover potential MDAs in herbal medicines more effectively. Leveraging the GAE framework, the SGAE-MDA model exactly integrates the inherent feature vectors of miRNAs and disease nodes with the regulatory data in the miRNA-disease network. Additionally, the proposed semi-supervised learning approach randomly hides the partial structure of the miRNA-disease network, subsequently reconstructing them within the GAE framework. This technique effectively minimizes network noise interference. Through comparison against other leading deep learning models, the results consistently highlighted the superior performance of the proposed SGAE-MDA model. Our code and dataset can be available at: https://github.com/22n9n23/SGAE-MDA.

Proteomic characterization of the colorectal cancer response to chemoradiation and targeted therapies reveals potential therapeutic strategies.

Chemoradiation and targeted therapies are the major treatments for colorectal cancer (CRC); however, molecular properties associated with therapy resistance are incompletely characterized. Here, we profile the proteome of 254 tumor tissues from patients with CRC undergoing chemotherapy, chemoradiation, or chemotherapy combined with targeted therapy. Proteome-based classification reveals four subtypes featured with distinct biological and therapeutic characteristics. The integrative analysis of CRC cell lines and clinical samples indicates that immune regulation is significantly associated with drug sensitivity. HSF1 can increase DNA damage repair and cell cycle, thus inducing resistance to radiation, while high expression of HDAC6 is negatively associated with response of cetuximab. Furthermore, we develop prognostic models with high accuracy to predict the therapeutic response, further validated by parallel reaction monitoring (PRM) assay in an independent validation cohort. This study provides a rich resource for investigating the mechanisms and indicators of chemoradiation and targeted therapy in CRC.

DlncRNALoc: A discrete wavelet transform-based model for predicting lncRNA subcellular localization.

The prediction of long non-coding RNA (lncRNA) subcellular localization is essential to the understanding of its function and involvement in cellular regulation. Traditional biological experimental methods are costly and time-consuming, making computational methods the preferred approach for predicting lncRNA subcellular localization (LSL). However, existing computational methods have limitations due to the structural characteristics of lncRNAs and the uneven distribution of data across subcellular compartments. We propose a discrete wavelet transform (DWT)-based model for predicting LSL, called DlncRNALoc. We construct a physicochemical property matrix of a 2-tuple bases based on lncRNA sequences, and we introduce a DWT lncRNA feature extraction method. We use the Synthetic Minority Over-sampling Technique (SMOTE) for oversampling and the local fisher discriminant analysis (LFDA) algorithm to optimize feature information. The optimized feature vectors are fed into support vector machine (SVM) to construct a predictive model. DlncRNALoc has been applied for a five-fold cross-validation on the three sets of benchmark datasets. Extensive experiments have demonstrated the superiority and effectiveness of the DlncRNALoc model in predicting LSL.

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials.

Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack of ground truth. Here we develop and characterize suites of publicly available multi-omics reference materials of matched DNA, RNA, protein and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters. These references provide built-in truth defined by relationships among the family members and the information flow from DNA to RNA to protein. We demonstrate how using a ratio-based profiling approach that scales the absolute feature values of a study sample relative to those of a concurrently measured common reference sample produces reproducible and comparable data suitable for integration across batches, labs, platforms and omics types. Our study identifies reference-free 'absolute' feature quantification as the root cause of irreproducibility in multi-omics measurement and data integration and establishes the advantages of ratio-based multi-omics profiling with common reference materials.

Proteogenomics of different urothelial bladder cancer stages reveals distinct molecular features for papillary cancer and carcinoma in situ.

The progression of urothelial bladder cancer (UC) is a complicated multi-step process. We perform a comprehensive multi-omics analysis of 448 samples from 190 UC patients, covering the whole spectrum of disease stages and grades. Proteogenomic integration analysis indicates the mutations of HRAS regulated mTOR signaling to form urothelial papilloma rather than papillary urothelial cancer (PUC). DNA damage is a key signaling pathway in the progression of carcinoma in situ (CIS) and related to APOBEC signature. Glucolipid metabolism increase and lower immune cell infiltration are associated with PUC compared to CIS. Proteomic analysis distinguishes the origins of invasive tumors (PUC-derived and CIS-derived), related to distinct clinical prognosis and molecular features. Additionally, loss of RBPMS, associated with CIS-derived tumors, is validated to increase the activity of AP-1 and promote metastasis. This study reveals the characteristics of two distinct branches (PUC and CIS) of UC progression and may eventually benefit clinical practice.

Quartet protein reference materials and datasets for multi-platform assessment of label-free proteomics.

BACKGROUND: Quantitative proteomics is an indispensable tool in life science research. However, there is a lack of reference materials for evaluating the reproducibility of label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based measurements among different instruments and laboratories. RESULTS: Here, we develop the Quartet standard as a proteome reference material with built-in truths, and distribute the same aliquots to 15 laboratories with nine conventional LC-MS/MS platforms across six cities in China. Relative abundance of over 12,000 proteins on 816 mass spectrometry files are obtained and compared for reproducibility among the instruments and laboratories to ultimately generate proteomics benchmark datasets. There is a wide dynamic range of proteomes spanning about 7 orders of magnitude, and the injection order has marked effects on quantitative instead of qualitative characteristics. CONCLUSION: Overall, the Quartet offers valuable standard materials and data resources for improving the quality control of proteomic analyses as well as the reproducibility and reliability of research findings.

Plasma proteomic profiling discovers molecular features associated with upper tract urothelial carcinoma.

Upper tract urothelial carcinoma (UTUC) is often diagnosed late and exhibits poor prognosis. Limited data are available on potential non-invasive biomarkers for disease monitoring. Here, we investigate the proteomic profile of plasma in 362 UTUC patients and 239 healthy controls. We present an integrated tissue-plasma proteomic approach to infer the signature proteins for identifying patients with muscle-invasive UTUC. We discover a protein panel that reflects lymph node metastasis, which is of interest in identifying UTUC patients with high risk and poor prognosis. We also identify a ten-protein classifier and establish a progression clock predicting progression-free survival of UTUC patients. Finally, we further validate the signature proteins by parallel reaction monitoring assay in an independent cohort. Collectively, this study portrays the plasma proteomic landscape of a UTUC cohort and provides a valuable resource for further biological and diagnostic research in UTUC.

MLL3 regulates the CDKN2A tumor suppressor locus in liver cancer.

Mutations in genes encoding components of chromatin modifying and remodeling complexes are among the most frequently observed somatic events in human cancers. For example, missense and nonsense mutations targeting the mixed lineage leukemia family member 3 (MLL3, encoded by KMT2C) histone methyltransferase occur in a range of solid tumors, and heterozygous deletions encompassing KMT2C occur in a subset of aggressive leukemias. Although MLL3 loss can promote tumorigenesis in mice, the molecular targets and biological processes by which MLL3 suppresses tumorigenesis remain poorly characterized. Here, we combined genetic, epigenomic, and animal modeling approaches to demonstrate that one of the mechanisms by which MLL3 links chromatin remodeling to tumor suppression is by co-activating the Cdkn2a tumor suppressor locus. Disruption of Kmt2c cooperates with Myc overexpression in the development of murine hepatocellular carcinoma (HCC), in which MLL3 binding to the Cdkn2a locus is blunted, resulting in reduced H3K4 methylation and low expression levels of the locus-encoded tumor suppressors p16/Ink4a and p19/Arf. Conversely, elevated KMT2C expression increases its binding to the CDKN2A locus and co-activates gene transcription. Endogenous Kmt2c restoration reverses these chromatin and transcriptional effects and triggers Ink4a/Arf-dependent apoptosis. Underscoring the human relevance of this epistasis, we found that genomic alterations in KMT2C and CDKN2A were associated with similar transcriptional profiles in human HCC samples. These results collectively point to a new mechanism for disrupting CDKN2A activity during cancer development and, in doing so, link MLL3 to an established tumor suppressor network.

Canagliflozin alleviates high glucose-induced peritoneal fibrosis via HIF-1α inhibition.

The cardioprotective effects of sodium-glucose cotransporter type 2 (SGLT2) inhibitors have been demonstrated in many studies. However, their benefits for end-stage kidney disease patients, particularly those on peritoneal dialysis, remain unclear. SGLT2 inhibition has shown peritoneal protective effects in some studies, but the mechanisms are still unknown. Herein, we investigated the peritoneal protective mechanisms of Canagliflozin in vitro by simulating hypoxia with CoCl2 in human peritoneal mesothelial cells (HPMCs) and rats by intraperitoneal injection of 4.25% peritoneal dialysate simulating chronic high glucose exposure. CoCl2 hypoxic intervention significantly increased HIF-1α abundance in HPMCs, activated TGF-ß/p-Smad3 signaling, and promoted the production of fibrotic proteins (Fibronectin, COL1A2, and α-SMA). Meanwhile, Canagliflozin significantly improved the hypoxia of HPMCs, decreased HIF-1α abundance, inhibited TGF-ß/p-Smad3 signaling, and decreased the expression of fibrotic proteins. Five-week intraperitoneal injection of 4.25% peritoneal dialysate remarkably increased peritoneal HIF-1α/TGF-ß/p-Smad3 signaling and promoted peritoneal fibrosis and peritoneal thickening. At the same time, Canagliflozin significantly inhibited the HIF-1α/TGF-ß/p-Smad3 signaling, prevented peritoneal fibrosis and peritoneal thickening, and improved peritoneal transportation and ultrafiltration. High glucose peritoneal dialysate increased the expression of peritoneal GLUT1, GLUT3 and SGLT2, all of which were inhibited by Canagliflozin. In conclusion, we showed that Canagliflozin could improve peritoneal fibrosis and function by ameliorating peritoneal hypoxia and inhibiting the HIF-1α/TGF-ß/p-Smad3 signaling pathway, providing theoretical support for the clinical use of SGLT2 inhibitors in patients on peritoneal dialysis.

Antihepatoma peptide, scolopentide, derived from the centipede scolopendra subspinipes mutilans.

BACKGROUND: Centipedes have been used to treat tumors for hundreds of years in China. However, current studies focus on antimicrobial and anticoagulation agents rather than tumors. The molecular identities of antihepatoma bioactive components in centipedes have not yet been extensively investigated. It is a challenge to isolate and characterize the effective components of centipedes due to limited peptide purification technologies for animal-derived medicines. AIM: To purify, characterize, and synthesize the bioactive components with the strongest antihepatoma activity from centipedes and determine the antihepatoma mechanism. METHODS: An antihepatoma peptide (scolopentide) was isolated and identified from the centipede scolopendra subspinipes mutilans using a combination of enzymatic hydrolysis, a Sephadex G-25 column, and two steps of high-performance liquid chromatography (HPLC). Additionally, the CCK8 assay was used to select the extracted fraction with the strongest antihepatoma activity. The molecular weight of the extracted scolopentide was characterized by quadrupole time of flight mass spectrometry (QTOF MS), and the sequence was matched by using the Mascot search engine. Based on the sequence and molecular weight, scolopentide was synthesized using solid-phase peptide synthesis methods. The synthetic scolopentide was confirmed by MS and HPLC. The antineoplastic effect of extracted scolopentide was confirmed by CCK8 assay and morphological changes again in vitro. The antihepatoma effect of synthetic scolopentide was assessed by the CCK8 assay and Hoechst staining in vitro and tumor volume and tumor weight in vivo. In the tumor xenograft experiments, qualified model mice (male 5-week-old BALB/c nude mice) were randomly divided into 2 groups (n = 6): The scolopentide group (0.15 mL/d, via intraperitoneal injection of synthetic scolopentide, 500 mg/kg/d) and the vehicle group (0.15 mL/d, via intraperitoneal injection of normal saline). The mice were euthanized by cervical dislocation after 14 d of continuous treatment. Mechanistically, flow cytometry was conducted to evaluate the apoptosis rate of HepG2 cells after treatment with extracted scolopentide in vitro. A Hoechst staining assay was also used to observe apoptosis in HepG2 cells after treatment with synthetic scolopentide in vitro. CCK8 assays and morphological changes were used to compare the cytotoxicity of synthetic scolopentide to liver cancer cells and normal liver cells in vitro. Molecular docking was performed to clarify whether scolopentide tightly bound to death receptor 4 (DR4) and DR5. qRT-PCR was used to measure the mRNA expression of DR4, DR5, fas-associated death domain protein (FADD), Caspase-8, Caspase-3, cytochrome c (Cyto-C), B-cell lymphoma-2 (Bcl-2), Bcl-2-associated X protein (Bax), x-chromosome linked inhibitor-of-apoptosis protein and Cellular fas-associated death domain-like interleukin-1ß converting enzyme inhibitory protein in hepatocarcinoma subcutaneous xenograft tumors from mice. Western blot assays were used to measure the protein expression of DR4, DR5, FADD, Caspase-8, Caspase-3, and Cyto-C in the tumor tissues. The reactive oxygen species (ROS) of tumor tissues were tested. RESULTS: In the process of purification, characterization and synthesis of scolopentide, the optimal enzymatic hydrolysis conditions (extract ratio: 5.86%, IC50: 0.310 mg/mL) were as follows: Trypsin at 0.1 g (300 U/g, centipede-trypsin ratio of 20:1), enzymolysis temperature of 46 °C, and enzymolysis time of 4 h, which was superior to freeze-thawing with liquid nitrogen (IC50: 3.07 mg/mL). A peptide with the strongest antihepatoma activity (scolopentide) was further purified through a Sephadex G-25 column (obtained A2) and two steps of HPLC (obtained B5 and C3). The molecular weight of the extracted scolopentide was 1018.997 Da, and the peptide sequence was RAQNHYCK, as characterized by QTOF MS and Mascot. Scolopentide was synthesized in vitro with a qualified molecular weight (1018.8 Da) and purity (98.014%), which was characterized by MS and HPLC. Extracted scolopentide still had an antineoplastic effect in vitro, which inhibited the proliferation of Eca-109 (IC50: 76.27 µg/mL), HepG2 (IC50: 22.06 µg/mL), and A549 (IC50: 35.13 µg/mL) cells, especially HepG2 cells. Synthetic scolopentide inhibited the proliferation of HepG2 cells (treated 6, 12, and 24 h) in a concentration-dependent manner in vitro, and the inhibitory effects were the strongest at 12 h (IC50: 208.11 µg/mL). Synthetic scolopentide also inhibited the tumor volume (Vehicle vs Scolopentide, P = 0.0003) and weight (Vehicle vs Scolopentide, P = 0.0022) in the tumor xenograft experiment. Mechanistically, flow cytometry suggested that the apoptosis ratios of HepG2 cells after treatment with extracted scolopentide were 5.01% (0 µg/mL), 12.13% (10 µg/mL), 16.52% (20 µg/mL), and 23.20% (40 µg/mL). Hoechst staining revealed apoptosis in HepG2 cells after treatment with synthetic scolopentide in vitro. The CCK8 assay and morphological changes indicated that synthetic scolopentide was cytotoxic and was significantly stronger in HepG2 cells than in L02 cells. Molecular docking suggested that scolopentide tightly bound to DR4 and DR5, and the binding free energies were-10.4 kcal/mol and-7.1 kcal/mol, respectively. In subcutaneous xenograft tumors from mice, quantitative real-time polymerase chain reaction and western blotting suggested that scolopentide activated DR4 and DR5 and induced apoptosis in SMMC-7721 Liver cancer cells by promoting the expression of FADD, caspase-8 and caspase-3 through a mitochondria-independent pathway. CONCLUSION: Scolopentide, an antihepatoma peptide purified from centipedes, may inspire new antihepatoma agents. Scolopentide activates DR4 and DR5 and induces apoptosis in liver cancer cells through a mitochondria-independent pathway.

Investigating students' attitudes towards translation technology: The status quo and structural relations with translation mindsets and future work self.

Introduction: Despite the growing attention paid to the research of translation technology teaching (TTT), there is still a lack of studies on students' attitudes and the motivational factors in relation to it. To this end, the paper reports on a questionnaire-based study that describes students' attitudes towards translation technology (in the Chinese MTI context) and explores its structural relations with translation mindsets and future work self. Methods: Data were collected from 108 grade 2021 MTI students of three selected Chinese universities and analyzed using descriptive statistics and structural equation modeling (SEM). Results: The results demonstrate that Chinese MTI students' overall attitudes towards translation technology are slightly positive. So far, they perceive translation technology to be slightly effective for translation and are slightly mindful of it. They are slightly influenced by teachers and still feel inhibited when learning and using it. Furthermore, the results also indicate that growth translation mindsets positively influence students' attitudes towards the effectiveness of translation technology, teacher influence, exhibition to translation technology, and mindfulness about translation technology, whereas fixed translation mindsets only negatively predict students' teacher influence. Likewise, future work self-salience positively associates with students' attitudes towards the effectiveness of translation technology and mindfulness about translation technology, while future work self-elaboration positively relates to students' exhibition to translation technology. Among them, growth translation mindsets are the strongest predictor for all attitudes components. Discussion: Theoretical and pedagogical implications are also discussed.

Comprehensive proteogenomic characterization of early duodenal cancer reveals the carcinogenesis tracks of different subtypes.

The subtypes of duodenal cancer (DC) are complicated and the carcinogenesis process is not well characterized. We present comprehensive characterization of 438 samples from 156 DC patients, covering 2 major and 5 rare subtypes. Proteogenomics reveals LYN amplification at the chromosome 8q gain functioned in the transmit from intraepithelial neoplasia phase to infiltration tumor phase via MAPK signaling, and illustrates the DST mutation improves mTOR signaling in the duodenal adenocarcinoma stage. Proteome-based analysis elucidates stage-specific molecular characterizations and carcinogenesis tracks, and defines the cancer-driving waves of the adenocarcinoma and Brunner's gland subtypes. The drug-targetable alanyl-tRNA synthetase (AARS1) in the high tumor mutation burden/immune infiltration is significantly enhanced in DC progression, and catalyzes the lysine-alanylation of poly-ADP-ribose polymerases (PARP1), which decreases the apoptosis of cancer cells, eventually promoting cell proliferation and tumorigenesis. We assess the proteogenomic landscape of early DC, and provide insights into the molecular features corresponding therapeutic targets.

Integrative proteogenomic characterization of early esophageal cancer.

Esophageal squamous cell carcinoma (ESCC) is malignant while the carcinogenesis is still unclear. Here, we perform a comprehensive multi-omics analysis of 786 trace-tumor-samples from 154 ESCC patients, covering 9 histopathological stages and 3 phases. Proteogenomics elucidates cancer-driving waves in ESCC progression, and reveals the molecular characterization of alcohol drinking habit associated signatures. We discover chromosome 3q gain functions in the transmit from nontumor to intraepithelial neoplasia phases, and find TP53 mutation enhances DNA replication in intraepithelial neoplasia phase. The mutations of AKAP9 and MCAF1 upregulate glycolysis and Wnt signaling, respectively, in advanced-stage ESCC phase. Six major tracks related to different clinical features during ESCC progression are identified, which is validated by an independent cohort with another 256 samples. Hyperphosphorylated phosphoglycerate kinase 1 (PGK1, S203) is considered as a drug target in ESCC progression. This study provides insight into the understanding of ESCC molecular mechanism and the development of therapeutic targets.

Senescence Rewires Microenvironment Sensing to Facilitate Antitumor Immunity.

Cellular senescence involves a stable cell-cycle arrest coupled to a secretory program that, in some instances, stimulates the immune clearance of senescent cells. Using an immune-competent liver cancer model in which senescence triggers CD8 T cell-mediated tumor rejection, we show that senescence also remodels the cell-surface proteome to alter how tumor cells sense environmental factors, as exemplified by type II interferon (IFNγ). Compared with proliferating cells, senescent cells upregulate the IFNγ receptor, become hypersensitized to microenvironmental IFNγ, and more robustly induce the antigen-presenting machinery-effects also recapitulated in human tumor cells undergoing therapy-induced senescence. Disruption of IFNγ sensing in senescent cells blunts their immune-mediated clearance without disabling the senescence state or its characteristic secretory program. Our results demonstrate that senescent cells have an enhanced ability to both send and receive environmental signals and imply that each process is required for their effective immune surveillance. SIGNIFICANCE: Our work uncovers an interplay between tissue remodeling and tissue-sensing programs that can be engaged by senescence in advanced cancers to render tumor cells more visible to the adaptive immune system. This new facet of senescence establishes reciprocal heterotypic signaling interactions that can be induced therapeutically to enhance antitumor immunity. See related article by Marin et al., p. 410. This article is highlighted in the In This Issue feature, p. 247.