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Background Intensive evidence has highlighted the effect of aberrant alternative splicing (AS) events on cancer progression when triggered by dysregulation of the SR protein family. Nonetheless, the underlying mechanism in breast cancer (BRCA) remains elusive. Here we sought to explore the molecular function of SRSF1 and identify the key AS events regulated by SRSF1 in BRCA. Methods We conducted a comprehensive analysis of the expression and clinical correlation of SRSF1 in BRCA based on the TCGA dataset, Metabric database and clinical tissue samples. Functional analysis of SRSF1 in BRCA was conducted in vitro and in vivo. SRSF1-mediated AS events and their binding motifs were identified by RNA-seq, RNA immunoprecipitation-PCR (RIP-PCR) and in vivo crosslinking followed by immunoprecipitation (CLIP), which was further validated by the minigene reporter assay. PTPMT1 exon 3 (E3) AS was identified to partially mediate the oncogenic role of SRSF1 by the P-AKT/C-MYC axis. Finally, the expression and clinical significance of these AS events were validated in clinical samples and using the TCGA database. Results SRSF1 expression was consistently upregulated in BRCA samples, positively associated with tumor grade and the Ki-67 index, and correlated with poor prognosis in a hormone receptor-positive (HR+) cohort, which facilitated proliferation, cell migration and inhibited apoptosis in vitro and in vivo. We identified SRSF1-mediated AS events and discovered the SRSF1 binding motif in the regulation of splice switching of PTPMT1. Furthermore, PTPMT1 splice switching was regulated by SRSF1 by binding directly to its motif in E3 which partially mediated the oncogenic role of SRSF1 by the AKT/C-MYC axis. Additionally, PTPMT1 splice switching was validated in tissue samples of BRCA patients and using the TCGA database. The high-risk group, identified by AS of PTPMT1 and expression of SRSF1, possessed poorer prognosis in the stage I/II TCGA BRCA cohort. Conclusions SRSF1 exerts oncogenic roles in BRCA partially by regulating the AS of PTPMT1, which could be a therapeutic target candidate in BRCA and a prognostic factor in HR+ BRCA patient.

Anaerobic oxidation of ammonium (anammox) is recognized as an important process for nitrogen (N) cycling, yet its role in agricultural ecosystems, which are intensively fertilized, remains unclear. In this study, we investigated the presence, activity, functional gene abundance and role of anammox bacteria in rhizosphere and non-rhizosphere paddy soils using catalyzed reporter deposition–fluorescence in situ hybridization, isotope-tracing technique, quantitative PCR assay and 16S rRNA gene clone libraries. Results showed that rhizosphere anammox contributed to 31–41% N 2 production with activities of 0.33–0.64 nmol N 2  g −1  soil h −1 , whereas the non-rhizosphere anammox bacteria contributed to only 2–3% N 2 production with lower activities of 0.08–0.26 nmol N 2  g −1  soil h −1 . Higher anammox bacterial cells were observed (0.75–1.4 × 10 7  copies g −1  soil) in the rhizosphere, which were twofold higher compared with the non-rhizosphere soil (3.7–5.9 × 10 6  copies g −1  soil). Phylogenetic analysis of the anammox bacterial 16S rRNA genes indicated that two genera of ‘ Candidatus Kuenenia’ and ‘ Candidatus Brocadia’ and the family of Planctomycetaceae were identified. We suggest the rhizosphere provides a favorable niche for anammox bacteria, which are important to N cycling, but were previously largely overlooked.

Background N6-methyladenosine (m6A) modification and long non-coding RNAs (lncRNAs) play pivotal roles in gastric cancer (GC) progression. The emergence of immunotherapy in GC has created a paradigm shift in the approaches of treatment, whereas there is significant heterogeneity with regard to degree of treatment responses, which results from the variability of tumor immune microenvironment (TIME). How the interplay between m6A and lncRNAs enrolling in the shaping of TIME remains unclear. Methods The RNA sequencing and clinical data of GC patients were collected from TCGA database. Pearson correlation test and univariate Cox analysis were used to screen out m6A-related lncRNAs. Consensus clustering method was implemented to classify GC patients into two clusters. Survival analysis, the infiltration level of immune cells, Gene set enrichment analysis (GSEA) and the mutation profiles were analyzed and compared between two clusters. A competing endogenous RNA (ceRNA) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of pathways in which m6A-related lncRNAs enriched. Then least absolute shrinkage and selection operator (LASSO) COX regression was implemented to select pivotal lncRNAs, and risk model was constructed accordingly. The prognosis value of the risk model was explored. In addition, the response to immune checkpoint inhibitors (ICIs) therapy were compared between different risk groups. Finally, we performed qRT-PCR to detect expression patterns of the selected lncRNAs in the 35 tumor tissues and their paired adjacent normal tissues, and validated the prognostic value of risk model in our cohort ( N  = 35). Results The expression profiles of 15 lncRNAs were included to cluster patients into 2 subtypes. Cluster1 with worse prognosis harbored higher immune score, stromal score, ESTIMATE score and lower mutation rates of the genes. Different immune cell infiltration patterns were also displayed between the two clusters. GSEA showed that cluster1 preferentially enriched in tumor hallmarks and tumor-related biological pathways. KEGG pathway analysis found that the target mRNAs which m6A-related lncRNAs regulated by sponging miRNAs mainly enriched in vascular smooth muscle contraction, cAMP signaling pathway and cGMP-PKG signaling pathway. Next, eight lncRNAs were selected by LASSO regression algorithm to construct risk model. Patients in the high-risk group had poor prognoses, which were consistent in our cohort. As for predicting responses to ICIs therapy, patients from high-risk group were found to have lower tumor mutation burden (TMB) scores and account for large proportion in the Microsatellite Instability-Low (MSI-L) subtype. Moreover, patients had distinct immunophenoscores in different risk groups. Conclusion Our study revealed that the interplay between m6A modification and lncRNAs might have critical role in predicting GC prognosis, sculpting TIME landscape and predicting the responses to ICIs therapy.

Hepatocellular carcinoma (HCC) is an immunotherapy-resistant malignancy characterized by high cellular heterogeneity. The diversity of cell types and the interplay between tumor and non-tumor cells remain to be clarified. Single cell RNA sequencing of human and mouse HCC tumors revealed heterogeneity of cancer-associated fibroblast (CAF). Cross-species analysis determined the prominent CD36 + CAFs exhibited high-level lipid metabolism and expression of macrophage migration inhibitory factor (MIF). Lineage-tracing assays showed CD36 + CAFs were derived from hepatic stellate cells. Furthermore, CD36 mediated oxidized LDL uptake-dependent MIF expression via lipid peroxidation/p38/CEBPs axis in CD36 + CAFs, which recruited CD33 + myeloid-derived suppressor cells (MDSCs) in MIF- and CD74-dependent manner. Co-implantation of CD36 + CAFs with HCC cells promotes HCC progression in vivo. Finally, CD36 inhibitor synergizes with anti-PD-1 immunotherapy by restoring antitumor T-cell responses in HCC. Our work underscores the importance of elucidating the function of specific CAF subset in understanding the interplay between the tumor microenvironment and immune system.

Background and aims The recurrence and metastasis of hepatocellular carcinoma (HCC) are mainly caused by microvascular invasion (MVI). Our study aimed to uncover the cellular atlas of MVI + HCC and investigate the underlying immune infiltration patterns with radiomics features. Methods Three MVI positive HCC and three MVI negative HCC samples were collected for single-cell RNA-seq analysis. 26 MVI positive HCC and 30 MVI negative HCC tissues were underwent bulk RNA-seq analysis. For radiomics analysis, radiomics features score (Radscore) were built using preoperative contrast MRI for MVI prediction and overall survival prediction. We deciphered the metabolism profiles of MVI + HCC using scMetabolism and scFEA. The correlation of Radscore with the level of APOE + macrophages and iCAFs was identified. Whole Exome Sequencing (WES) was applied to distinguish intrahepatic metastasis (IM) and multicentric occurrence (MO). Transcriptome profiles were compared between IM and MO. Results Elevated levels of APOE+ macrophages and iCAFs were detected in MVI + HCC. There was a strong correlation between the infiltration of APOE + macrophages and iCAFs, as confirmed by immunofluorescent staining. MVI positive tumors exhibited increased lipid metabolism, which was attributed to the increased presence of APOE+ macrophages. APOE + macrophages and iCAFs were also found in high levels in IM, as opposed to MO. The difference of infiltration level and Radscore between two nodules in IM was relatively small. Furthermore, we developed Radscore for predicting MVI and HCC prognostication that were also able to predict the level of infiltration of APOE + macrophages and iCAFs. Conclusion This study demonstrated the interactions of cell subpopulations and distinct metabolism profiles in MVI + HCC. Besides, MVI prediction Radscore and MVI prognostic Radscore were highly correlated with the infiltration of APOE + macrophages and iCAFs, which helped to understand the biological significance of radiomics and optimize treatment strategy for MVI + HCC.

The immune infiltration of tumors is closely related to clinical outcomes. The composition of tumor-infiltrating immune cells (TIICs) can serve as biomarkers for predicting response to treatment and survival in different patient subgroups in terms of chemotherapy and immunotherapy. This study is focused on investigating the clinical implications of TIICs in breast cancer patients. We performed several in silico analyses of gene expression profiles in 2976 nonmetastatic tumor samples. CIBERSORT was used to estimate the proportion of 22 immune cell types to analyze their correlation with overall survival (OS) and disease-free survival (DFS) in different breast cancer subtypes and stages. Our results showed that a higher fraction of plasma cells in estrogen receptor (ER)-positive breast cancer patients indicated an increase in DFS (hazard ratio [HR]=0.66, 95% confidence interval [CI] 0.54~0.82, p< 0.01), while a decreased OS was correlated with a greater number of M0 macrophages (HR=2.02, 95% CI 1.27~3.30, p=0.01) and regulatory T cells (HR=1.90, 95% CI 1.20~3.02, p=0.02). In ER-negative or progesterone receptor (PR)-negative subtypes or in a combined subtype, the increase in activated memory CD4+ T cells was correlated with increased DFS (HR=0.46, 95% CI 0.33~0.63, p< 0.01). In all breast cancer patients, a higher proportion of M0 macrophages indicated a decreased DFS (HR=1.67, 95% CI 1.22~2.27, p< 0.01), while increased OS was associated with relatively larger fractions of resting memory CD4+ T cells (HR=0.70, 95% CI 0.55~0.90, p=0.02) and γδ T cells (HR=0.66, 95% CI 0.51~0.85, p< 0.01). Therefore, this study revealed that the composition of TIICs is different in patients with various subtypes of breast cancer and is directly related to prognosis, suggesting that TIICs are important participants in tumor progression and may, potentially be used for future diagnosis and treatment.

Natural killer (NK) cell can inhibit tumor initiation and regulates metastatic dissemination, acting as key mediators of the innate immune response. Intrinsic factors modulating NK cells infiltration and its anticancer activity remain poorly characterized. We investigated the roles of dysregulation of micro(mi)RNAs and NK cells in progression of hepatocellular carcinoma (HCC). Methods: Small RNA sequencing were used to detect the miRNA profiles of tumor tissues from HCC patients with (n=14) or without (n=13) pulmonary metastasis and HCC cell lines with different pulmonary metastatic potentials. Chemokine expression profiling and bioinformatics were used to detect the downstream target of candidate target. In gain- and loss-of-function assays were used to investigate the role of miRNA in HCC progression. Different subsets of NK cells were isolated and used for chemotaxis and functional assays in vivo and in vitro. In situ hybridization and immunohistochemical analyses were performed to detect the expression of miRNA in tumor tissues from 242 HCC patients undergoing curative resection from 2010. Results: Three miRNAs (miR-137, miR-149-5p, and miR-561-5p) were identified to be associated with pulmonary metastasis in patients with HCC. miR-561-5p was most highly overexpressed in metastatic HCC tissues and high-metastatic-potential HCC cell lines. In gain- and loss-of-function assays in a murine model, miR-561-5p promoted tumor growth and spread to the lungs. Yet, miR-561-5p did not appear to affect cellular proliferation and migration in vitro. Bioinformatics and chemokine expression profiling identified chemokine (C-X3-C motif) ligand 1 (CX3CL1) as a potential target of miR-561-5p. Furthermore, miR-561-5p promoted tumorigenesis and metastasis via CX3CL1-dependent regulation of CX3CR1+ NK cell infiltration and function. CX3CR1+ NK cells demonstrated stronger in vivo anti-metastatic activity relative to CX3CR1- NK cells. CX3CL1 stimulated chemotactic migration and cytotoxicity in CX3CR1+ NK cells via STAT3 signaling. Blockade of CX3CL1, CX3CR1, or of pSTAT3 signaling pathways attenuated the antitumor responses. Clinical samples exhibited a negative correlation between miR-561-5p expression and levels of CX3CL1 and CX3CR1+ NK cells. High miR-561-5p abundance, low CX3CL1 levels, and low numbers of CX3CR1+ NK cells were associated with adverse prognosis. Conclusion: We delineated a miR-561-5p/CX3CL1/NK cell axis that drives HCC metastasis and demonstrated that CX3CR1+ NK cells serve as potent antitumor therapeutic effectors.

A mammalian brain contains numerous neurons with distinct cell types for complex neural circuits. Virus-based circuit tracing tools are powerful in tracking the interaction among the different brain regions. However, detecting brain-wide neural networks in vivo remains challenging since most viral tracing systems rely on postmortem optical imaging. We developed a novel approach that enables in vivo detection of brain-wide neural connections based on metal-free magnetic resonance imaging (MRI). The recombinant adeno-associated virus (rAAV) with retrograde ability, the rAAV2-retro, encoding the human water channel aquaporin 1 (AQP1) MRI reporter gene was generated to label neural connections. The mouse was micro-injected with the virus at the Caudate Putamen (CPU) region and subjected to detection with Diffusion-weighted MRI (DWI). The prominent structure of the CPU-connected network was clearly defined. In combination with a Cre-loxP system, rAAV2-retro expressing Cre-dependent AQP1 provides a CPU-connected network of specific type neurons. Here, we established a sensitive, metal-free MRI-based strategy for in vivo detection of cell type-specific neural connections in the whole brain, which could visualize the dynamic changes of neural networks in rodents and potentially in non-human primates.

We studied the value of circulating tumor DNA (ctDNA) in predicting early postoperative tumor recurrence and monitoring tumor burden in patients with hepatocellular carcinoma (HCC). Plasma‐free DNA, germline DNA, and tissue DNA were isolated from 41 patients with HCC. Serial ctDNAs were analyzed by next‐generation sequencing before and after operation. Whole‐exome sequencing was used to detect the DNA of HCC and adjacent tissues. In total, 47 gene mutations were identified in the ctDNA of the 41 patients analyzed before surgery. ctDNA was detected in 63.4% and 46% of the patient plasma pre‐ and postoperation, respectively. The preoperative ctDNA positivity rate was significantly lower in the nonrecurrence group than in the recurrence group. With a median follow‐up of 17.7 months, nine patients (22%) experienced tumor recurrence. ctDNA positivity at two time‐points was associated with significantly shorter recurrence‐free survival (RFS). Tumors with NRAS, NEF2L2, and MET mutations had significantly shorter times to recurrence than those without mutations and showed high recurrence prediction performance by machine learning. Multivariate analyses showed that the median variant allele frequency (VAF) of mutations in preoperative ctDNA was a strong independent predictor of RFS. ctDNA is a real‐time monitoring indicator that can accurately reflect tumor burden. The median VAF of baseline ctDNA is a strong independent predictor of RFS in individuals with HCC. Here, we studied the value of circulating tumor DNA (ctDNA), in combination with germline and tissue DNA by whole‐exome sequencing in patients withhepatocellular carcinoma (HCC). Our analysis demonstrated that ctDNA may serve as a real‐time monitoring indicator by accurately reflecting tumor burden, and as a strong independent predictor of recurrence‐free survival in HCC.

Clear cell renal cell carcinoma (ccRCC) is characterized by metabolic dysregulation and distinct immunological signatures. The interplay between metabolic and immune processes in the tumor microenvironment (TME) causes the complexity and heterogeneity of immunotherapy responses observed during ccRCC treatment. Herein, we initially identified two distinct metabolic subtypes (C1 and C2 subtypes) and immune subtypes (I1 and I2 subtypes) based on the occurrence of differentially expressed metabolism-related prognostic genes and immune-related components. Notably, we observed that immune regulators with upregulated expression actively participated in multiple metabolic pathways. Therefore, we further delineated four immunometabolism-based ccRCC subtypes (M1, M2, M3, and M4 subtypes) according to the results of the above classification. Generally, we found that high metabolic activity could suppress immune infiltration. Immunometabolism subtype classification was associated with immunotherapy response, with patients possessing the immune-inflamed, metabolic-desert subtype (M3 subtype) that benefits the most from immunotherapy. Moreover, differences in the shifts in the immunometabolism subtype after immunotherapy were observed in the responder and non-responder groups, with patients from the responder group transferring to subtypes with immune-inflamed characteristics and less active metabolic activity (M3 or M4 subtype). Immunometabolism subtypes could also serve as biomarkers for predicting immunotherapy response. To decipher the genomic and epigenomic features of the four subtypes, we analyzed multiomics data, including miRNA expression, DNA methylation status, copy number variations occurrence, and somatic mutation profiles. Patients with the M2 subtype possessed the highest VHL gene mutation rates and were more likely to be sensitive to sunitinib therapy. Moreover, we developed non-invasive radiomic models to reveal the status of immune activity and metabolism. In addition, we constructed a radiomic prognostic score (PRS) for predicting ccRCC survival based on the seven radiomic features. PRS was further demonstrated to be closely linked to immunometabolism subtype classification, immune score, and tumor mutation burden. The prognostic value of the PRS and the association of the PRS with immune activity and metabolism were validated in our cohort. Overall, our study established four immunometabolism subtypes, thereby revealing the crosstalk between immune and metabolic activities and providing new insights into personal therapy selection.