Activin A signaling stimulates neutrophil activation and macrophage migration in pancreatitis.

Acute Pancreatitis (AP) is associated with high mortality and current treatment options are limited to supportive care. We found that blockade of activin A (activin) in mice improves outcomes in two murine models of AP. To test the hypothesis that activin is produced early in response to pancreatitis and is maintained throughout disease progression to stimulate immune cells, we first performed digital spatial profiling (DSP) of human chronic pancreatitis (CP) patient tissue. Then, transwell migration assays using RAW264.7 mouse macrophages and qPCR analysis of "neutrophil-like" HL-60 cells were used for functional correlation. Immunofluorescence and western blots on cerulein-induced pancreatitis samples from pancreatic acinar cell-specific Kras knock-in (Ptf1aCreER™; LSL-KrasG12D) and functional WT Ptf1aCreER™ mouse lines mimicking AP and CP to allow for in vivo confirmation. Our data suggest activin promotes neutrophil and macrophage activation both in situ and in vitro, while pancreatic activin production is increased as early as 1 h in response to pancreatitis and is maintained throughout CP in vivo. Taken together, activin is produced early in response to pancreatitis and is maintained throughout disease progression to promote neutrophil and macrophage activation.

Silencing of genes by promoter hypermethylation shapes tumor microenvironment and resistance to immunotherapy in clear-cell renal cell carcinomas.

The efficacy of immune checkpoint inhibitors varies in clear-cell renal cell carcinoma (ccRCC), with notable primary resistance among patients. Here, we integrate epigenetic (DNA methylation) and transcriptome data to identify a ccRCC subtype characterized by cancer-specific promoter hypermethylation and epigenetic silencing of Polycomb targets. We develop and validate an index of methylation-based epigenetic silencing (iMES) that predicts primary resistance to immune checkpoint inhibition (ICI) in the BIONIKK trial. High iMES is associated with VEGF pathway silencing, endothelial cell depletion, immune activation/suppression, EZH2 activation, BAP1/SETD2 deficiency, and resistance to ICI. Combination therapy with hypomethylating agents or tyrosine kinase inhibitors may benefit patients with high iMES. Intriguingly, tumors with low iMES exhibit increased endothelial cells and improved ICI response, suggesting the importance of angiogenesis in ICI treatment. We also develop a transcriptome-based analogous system for extended applicability of iMES. Our study underscores the interplay between epigenetic alterations and tumor microenvironment in determining immunotherapy response.

Delineating the interplay between oncogenic pathways and immunity in anaplastic Wilms tumors.

Wilms tumors are highly curable in up to 90% of cases with a combination of surgery and radio-chemotherapy, but treatment-resistant types such as diffuse anaplastic Wilms tumors pose significant therapeutic challenges. Our multi-omics profiling unveils a distinct desert-like diffuse anaplastic Wilms tumor subtype marked by immune/stromal cell depletion, TP53 alterations, and cGAS-STING pathway downregulation, accounting for one-third of all diffuse anaplastic cases. This subtype, also characterized by reduced CD8 and CD3 infiltration and active oncogenic pathways involving histone deacetylase and DNA repair, correlates with poor clinical outcomes. These oncogenic pathways are found to be conserved in anaplastic Wilms tumor cell models. We identify histone deacetylase and/or WEE1 inhibitors as potential therapeutic vulnerabilities in these tumors, which might also restore tumor immunogenicity and potentially enhance the effects of immunotherapy. These insights offer a foundation for predicting outcomes and personalizing treatment strategies for aggressive pediatric Wilms tumors, tailored to individual immunological landscapes.

Development and validation of radiomics nomograms for preoperative prediction of characteristics in non-small cell lung cancer and circulating tumor cells.

To develop and validate 3 radiomics nomograms for preoperative prediction of pathological and progression diagnosis in non-small cell lung cancer (NSCLC) as well as circulating tumor cells (CTCs). A total of 224 and 134 patients diagnosed with NSCLC were respectively gathered in 2018 and 2019 in this study. There were totally 1197 radiomics features that were extracted and quantified from the images produced by computed tomography. Then we selected the radiomics features with predictive value by least absolute shrinkage and selection operator and combined them into radiomics signature. Logistic regression models were built using radiomics signature as the only predictor, which were then converted to nomograms for individualized predictions. Finally, the performance of the nomograms was assessed on both cohorts. Additionally, immunohistochemical correlation analysis was also performed. As for discrimination, the area under the curve of pathological diagnosis nomogram and progression diagnosis nomogram in NSCLC were both higher than 90% in the training cohort and higher than 80% in the validation cohort. The performance of the CTC-diagnosis nomogram was somehow unexpected where the area under the curve were range from 60% to 70% in both cohorts. As for calibration, nonsignificant statistics (P > .05) yielded by Hosmer-Lemeshow tests suggested no departure between model prediction and perfect fit. Additionally, decision curve analyses demonstrated the clinically usefulness of the nomograms. We developed radiomics-based nomograms for pathological, progression and CTC diagnosis prediction in NSCLC respectively. Nomograms for pathological and progression diagnosis were demonstrated well-performed to facilitate the individualized preoperative prediction, while the nomogram for CTC-diagnosis prediction needed improvement.

Non-Canonical Activin A Signaling Stimulates Context-Dependent and Cellular-Specific Outcomes in CRC to Promote Tumor Cell Migration and Immune Tolerance.

We have shown that activin A (activin), a TGF-ß superfamily member, has pro-metastatic effects in colorectal cancer (CRC). In lung cancer, activin activates pro-metastatic pathways to enhance tumor cell survival and migration while augmenting CD4+ to CD8+ communications to promote cytotoxicity. Here, we hypothesized that activin exerts cell-specific effects in the tumor microenvironment (TME) of CRC to promote anti-tumoral activity of immune cells and the pro-metastatic behavior of tumor cells in a cell-specific and context-dependent manner. We generated an Smad4 epithelial cell specific knockout (Smad4-/-) which was crossed with TS4-Cre mice to identify SMAD-specific changes in CRC. We also performed IHC and digital spatial profiling (DSP) of tissue microarrays (TMAs) obtained from 1055 stage II and III CRC patients in the QUASAR 2 clinical trial. We transfected the CRC cells to reduce their activin production and injected them into mice with intermittent tumor measurements to determine how cancer-derived activin alters tumor growth in vivo. In vivo, Smad4-/- mice displayed elevated colonic activin and pAKT expression and increased mortality. IHC analysis of the TMA samples revealed increased activin was required for TGF-ß-associated improved outcomes in CRC. DSP analysis identified that activin co-localization in the stroma was coupled with increases in T-cell exhaustion markers, activation markers of antigen presenting cells (APCs), and effectors of the PI3K/AKT pathway. Activin-stimulated PI3K-dependent CRC transwell migration, and the in vivo loss of activin lead to smaller CRC tumors. Taken together, activin is a targetable, highly context-dependent molecule with effects on CRC growth, migration, and TME immune plasticity.

Single-cell Transcriptomics Reveals Early Molecular and Immune Alterations Underlying the Serrated Neoplasia Pathway Toward Colorectal Cancer.

BACKGROUND & AIMS: Approximately one-third of colorectal cancers develop from serrated lesions (SLs), including hyperplastic polyp (HP), sessile serrated lesion (SSL), traditional serrated adenoma (TSA), and SSL with dysplasia (SSLD) through the serrated neoplasia pathway, which progresses faster than the conventional adenoma-carcinoma pathway. We sought to depict the currently unclarified molecular and immune alterations by the single-cell landscape in SLs. METHODS: We performed single-cell RNA sequencing of 16 SLs (including 4 proximal HPs, 5 SSLs, 2 SSLDs, and 5 TSAs) vs 3 normal colonic tissues. RESULTS: A total of 60,568 high-quality cells were obtained. Two distinct epithelial clusters with redox imbalance in SLs were observed, along with upregulation of tumor-promoting SerpinB6 that regulated ROS level. Epithelial clusters of SSL and TSA showed distinct molecular features: SSL-specific epithelium manifested overexpressed proliferative markers with Notch pathway activation, whereas TSA-specific epithelium showed Paneth cell metaplasia with aberrant lysozyme expression. As for immune contexture, enhanced cytotoxic activity of CD8+ T cells was observed in SLs; it was mainly attributable to increased proportion of CD103+CD8+ tissue-resident memory T cells, which might be regulated by retinoic acid metabolism. Microenvironment of SLs was generally immune-activated, whereas some immunosuppressive cells (regulatory T cells, anti-inflammatory macrophages, MDK+IgA+ plasma cells, MMP11-secreting PDGFRA+ fibroblasts) also emerged at early stage and further accumulated in SSLD. CONCLUSION: Epithelial, immune, and stromal components in the serrated pathway undergo fundamental alterations. Future molecular subtypes of SLs and potential immune therapy might be developed.

An Enhancer Demethylator Phenotype Converged to Immune Dysfunction and Resistance to Immune Checkpoint Inhibitors in Clear-Cell Renal Cell Carcinomas.

PURPOSE: Immune checkpoint inhibitors (ICI) have revolutionized the treatment of patients with clear-cell renal cell carcinomas (ccRCC). Although analyses of transcriptome, genetic alterations, and the tumor microenvironment (TME) have shed light into mechanisms of response and resistance to these agents, the role of epigenetic alterations in this process remains fully unknown. EXPERIMENTAL DESIGN: We investigated the methylome of six ccRCC cohorts as well as one cell line dataset. Of note, we took advantage of the BIONIKK trial aiming to tailor treatments according to Paris Descartes 4-gene expression subgroups, and performed Illumina EPIC profiling for 46 samples related to patients treated with ipilimumab plus nivolumab, and 17 samples related to patients treated with sunitinib. RESULTS: A group of tumors associated with enhancer demethylation was discovered, namely TED. TED was associated with tumors with sarcomatoid differentiation and poor clinical outcome. TED harbored TET1 promoter demethylation, activated the gene expression signature of epithelial-mesenchymal transition and IL6/JAK/STAT3 pathways, and displayed a TME characterized by both immune activation and suppressive populations, fibroblast infiltration, and endothelial depletion. In addition, TED was a predictive factor of resistance to the combination of first-line ipilimumab-nivolumab in the BIONIKK clinical trial. Finally, TED was associated with activation of specific regulons, which we also found to be predictive of resistance to immunotherapy in an independent cohort. CONCLUSIONS: We report on the discovery of a novel epigenetic phenotype associated with resistance to ICIs that may pave the way to better personalizing patients' treatments. See related commentary by Zhou and Kim, p. 1170.

Metabolism-associated molecular classification of gastric adenocarcinoma.

Most gastric cancers (GC) are adenocarcinomas, whereas GC is a highly heterogeneous disease due to its molecular heterogeneity. However, traditional morphology-based classification systems, including the WHO classification and Lauren's classification, have limited utility in guiding clinical treatment. We performed nonnegative matrix factorization (NMF) clustering based on 2752 metabolism-associated genes. We characterized each of the subclasses from multiple angles, including subclass-associated metabolism signatures, immune cell infiltration, clinic10al characteristics, drug sensitivity, and pathway enrichment. As a result, four subtypes were identified: immune suppressed, metabolic, mesenchymal/immune exhausted and hypermutated. The subtypes exhibited significant prognostic differences, which suggests that the metabolism-related classification has clinical significance. Metabolic and hypermutated subtypes have better overall survival, and the hypermutated subtype is likely to be sensitive to anti-PD-1 immunotherapy. In addition, our work showed a strong connection with previously established classifications, especially Lei's subtype, to which we provided an interpretation based on the immune cell infiltration perspective, deepening the understanding of GC heterogeneity. Finally, a 120-gene classifier was generated to determine the GC classification, and a 10-gene prognostic model was developed for survival time prediction.

Identification and validation of an inflammation-related lncRNAs signature for improving outcomes of patients in colorectal cancer.

Background: Colorectal cancer is the fourth most deadly cancer worldwide. Although current treatment regimens have prolonged the survival of patients, the prognosis is still unsatisfactory. Inflammation and lncRNAs are closely related to tumor occurrence and development in CRC. Therefore, it is necessary to establish a new prognostic signature based on inflammation-related lncRNAs to improve the prognosis of patients with CRC. Methods: LASSO-penalized Cox analysis was performed to construct a prognostic signature. Kaplan-Meier curves were used for survival analysis and ROC curves were used to measure the performance of the signature. Functional enrichment analysis was conducted to reveal the biological significance of the signature. The R package "maftool" and GISTIC2.0 algorithm were performed for analysis and visualization of genomic variations. The R package "pRRophetic", CMap analysis and submap analysis were performed to predict response to chemotherapy and immunotherapy. Results: An effective and independent prognostic signature, IRLncSig, was constructed based on sixteen inflammation-related lncRNAs. The IRLncSig was proved to be an independent prognostic indicator in CRC and was superior to clinical variables and the other four published signatures. The nomograms were constructed based on inflammation-related lncRNAs and detected by calibration curves. All samples were classified into two groups according to the median value, and we found frequent mutations of the TP53 gene in the high-risk group. We also found some significantly amplificated regions in the high-risk group, 8q24.3, 20q12, 8q22.3, and 20q13.2, which may regulate the inflammatory activity of cancer cells in CRC. Finally, we identified chemotherapeutic agents for high-risk patients and found that these patients were more likely to respond to immunotherapy, especially anti-CTLA4 therapy. Conclusion: In short, we constructed a new signature based on sixteen inflammation-related lncRNAs to improve the outcomes of patients in CRC. Our findings have proved that the IRLncSig can be used as an effective and independent marker for predicting the survival of patients with CRC.

The Impact of Meteorology and Emissions on Surface Ozone in Shandong Province, China, during 2014-2019.

China has been experiencing severe ozone pollution problems in recent years. While a number of studies have focused on the ozone-pollution-prone regions such as the North China Plain, Yangtze River Delta, and Pearl River Delta regions, few studies have investigated the mechanisms modulating the interannual variability of ozone concentrations in Shandong Province, where a large population is located and is often subject to ozone pollution. By utilizing both the reanalysis dataset and regional numerical model (WRF-CMAQ), we delve into the potential governing mechanisms of ozone pollution in Shandong Province-especially over the major port city of Qingdao-during summer 2014-2019. During this period, ozone pollution in Qingdao exceeded the tier II standard of the Chinese National Ambient Air Quality (GB 3095-2012) for 75 days. From the perspective of meteorology, the high-pressure ridge over Baikal Lake and to its northeast, which leads to a relatively low humidity and sufficient sunlight, is the most critical weather system inducing high-ozone events in Qingdao. In terms of emissions, biogenic emissions contribute to ozone enhancement close to 10 ppb in the west and north of Shandong Province. Numerical experiments show that the local impact of biogenic emissions on ozone production in Shandong Province is relatively small, whereas biogenic emissions on the southern flank of Shandong Province enhance ozone production and further transport northeastward, resulting in an increase in ozone concentrations over Shandong Province. For the port city of Qingdao, ship emissions increase ozone concentrations when sea breezes (easterlies) prevail over Qingdao, with the 95th percentile reaching 8.7 ppb. The findings in this study have important implications for future ozone pollution in Shandong Province, as well as the northern and coastal areas in China.

Multi-Omics Integrative Analysis of Lung Adenocarcinoma: An in silico Profiling for Precise Medicine.

Lung adenocarcinoma (LUAD) is one of the most common histological subtypes of lung cancer. The aim of this study was to construct consensus clusters based on multi-omics data and multiple algorithms. In order to identify specific molecular characteristics and facilitate the use of precision medicine on patients we used gene expression, DNA methylation, gene mutations, copy number variation data, and clinical data of LUAD patients for clustering. Consensus clusters were obtained using a consensus ensemble of five multi-omics integrative algorithms. Four molecular subtypes were identified. The CS1 and CS2 subtypes had better prognosis. Based on the immune and drug sensitivity predictions, we inferred that CS1 may be less responsive to immunotherapy and less sensitive to chemotherapeutic drugs. The high immune infiltration of CS2 cells may respond well to immunotherapy. Additionally, the CS2 subtype may also respond to EGFR molecular targeted therapy. The CS3 and CS4 subtypes were associated with poor prognosis. These two subtypes had more mutations, especially TP53 ones, as well as higher sensitivity to chemotherapeutics for lung cancer. However, CS3 was enriched in immune-related pathways and may respond to anti-PD1 immunotherapy. In addition, CS1 and CS4 were less sensitive to ferroptosis inhibitors. We performed a comprehensive analysis of the five types of omics data using five clustering algorithms to reveal the molecular characteristics of LUAD patients. These findings provide new insights into LUAD subtypes and potential clinical treatment strategies to guide personalized management and treatment.

Identification of a DNA Damage Response and Repair-Related Gene-Pair Signature for Prognosis Stratification Analysis in Hepatocellular Carcinoma.

Background: Nowadays, although the cause of hepatocellular carcinoma (HCC) mortality and recurrence remains at a high level, the 5-year survival rate is still very low. The DNA damage response and repair (DDR) pathway may affect HCC patients' survival by influencing tumor development and therapeutic response. It is necessary to identify a prognostic DDR-related gene signature to predict the outcome of patients. Methods: Level 3 mRNA expression and clinical information were extracted from the TCGA website. The GSE14520 datasets, ICGC-LIRI datasets, and a Chinese HCC cohort were served as validation sets. Univariate Cox regression analysis and LASSO-penalized Cox regression analysis were performed to construct the DDR-related gene pair (DRGP) signature. Kaplan-Meier survival curves and time-dependent receiver operating characteristic (ROC) analysis curves were calculated to determine the predictive ability of this prognostic model. Then, a prognostic nomogram was established to help clinical management. We investigated the difference in biological processes between HRisk and LRisk by conducting several enrichment analyses. The TIDE algorithm and R package "pRRophetic" were applied to estimate the immunotherapeutic and chemotherapeutic response. Results: We constructed the prognostic signature based on 23 DDR-related gene pairs. The patients in the training datasets were divided into HRisk and LRisk groups at median cut-off. The HRisk group had significantly poorer OS than the LRisk group, and the signature was an independent prognostic indicator in HCC. Furthermore, a nomogram of the riskscore combined with TNM stage was constructed and detected by the calibration curve and decision curve. The LRisk group was associated with higher expression of HBV oncoproteins and metabolism pathways, while DDR-relevant pathways and cell cycle process were enriched in the HRisk group. Moreover, patients in the LRisk group may be more beneficial from immunotherapy. We also found that TP53 gene was more frequently mutated in the HRisk group. As for chemotherapeutic drugs commonly used in HCC, the HRisk group was highly sensitive to 5-fluorouracil, while the LRisk group presented with a significantly higher response to gefitinib and gemcitabine. Conclusion: Overall, we developed a novel DDR-related gene pair signature and nomogram to assist in predicting survival outcomes and clinical treatment of HCC patients. It also helps understand the underlying mechanisms of different DDR patterns in HCC.

Identification of Immune-Related Subtypes and Characterization of Tumor Microenvironment Infiltration in Bladder Cancer.

Tumors are closely related to the tumor microenvironment (TME). The complex interaction between tumor cells and the TME plays an indisputable role in tumor development. Tumor cells can affect the TME, promote tumor angiogenesis and induce immune tolerance by releasing cell signaling molecules. Immune cell infiltration (ICI) in the TME can affect the prognosis of patients with bladder cancer. However, the pattern of ICI of the TME in bladder cancer has not yet been elucidated. Herein, we identified three distinct ICI subtypes based on the TME immune infiltration pattern of 584 bladder cancer patients using the ESTIMATE and CIBERSORT algorithms. Then, we identified three gene clusters based on the differentially expressed genes (DEGs) between the three ICI subtypes. In addition, the ICI score was determined using single sample gene set enrichment analysis (ssGSEA). The results suggested that patients in the high ICI score subgroup had a favorable prognosis and higher expression of checkpoint-related and immune activity-related genes. The high ICI score subgroup was also linked to increased tumor mutation burden (TMB) and neoantigen burden. A cohort treated with anti-PD-L1 immunotherapy confirmed the therapeutic advantage and clinical benefit of patients with higher ICI scores. In the end, our study also shows that the ICI score represents an effective prognostic predictor for evaluating the response to immunotherapy. In conclusion, our study deepened the understanding of the TME, and it provides new ideas for improving patients' response to immunotherapy and promoting individualized tumor immunotherapy in the future.

Perception of attractive and unattractive face groups is driven by distinct spatial frequencies.

Our visual system is able to extract information on facial attractiveness from groups of faces that contain both coarse and detailed information. This raises the question: What information is extracted from a face group? Is the attractiveness perception of multiple faces driven by high or low spatial frequency that can highlight the local or global information of the faces, respectively? In the first experiment, we adapted participants to four unattractive faces with full bandwidth (FB), high spatial frequency (HSF), and low spatial frequency (LSF). We observed significant aftereffects in the HSF faces adaptation condition, which suggests that the perception of multiple unattractive faces is largely driven by HSF information. In the second experiment, we found a similar but different pattern in the direct-rating tasks, suggesting distinct perception mechanisms in unattractive versus attractive faces. In the third experiment, both the adaptation and direct-rating paradigms suggested that perception of multiple attractive faces is largely driven by LSF information. Overall, results from the three experiments together found that perception of multiple attractive and unattractive faces depends on visual information from different spatial frequencies, suggesting distinctive mechanisms in processing attractive and unattractive groups of faces.