Ferroptosis-related gene transferrin receptor protein 1 expression correlates with the prognosis and tumor immune microenvironment in cervical cancer.

Background: Ferroptosis is a non-apoptotic iron-dependent form of cell death implicated in various cancer pathologies. However, its precise role in tumor growth and progression of cervical cancer (CC) remains unclear. Transferrin receptor protein 1 (TFRC), a key molecule associated with ferroptosis, has been identified as influencing a broad range of pathological processes in different cancers. However, the prognostic significance of TFRC in CC remains unclear. The present study utilized bioinformatics to explore the significance of the ferroptosis-related gene TFRC in the progression and prognosis of CC. Methods: We obtained RNA sequencing data and corresponding clinical information on patients with CC from The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx) and Gene Expression Omnibus (GEO) databases. Using least absolute shrinkage and selection operator (LASSO) Cox regression, we then generated a multigene signature of five ferroptosis-related genes (FRGs) for the prognostic prediction of CC. We investigated the relationship between TFRC gene expression and immune cell infiltration by employing single-sample GSEA (ssGSEA) analysis. The potential functional role of the TFRC gene was evaluated through gene set enrichment analysis (GSEA). Immunohistochemistry and qPCR was employed to assess TFRC mRNA and protein expression in 33 cases of cervical cancer. Furthermore, the relationship between TFRC mRNA expression and overall survival (OS) was investigated in patients. Results: CC samples had significantly higher TFRC gene expression levels than normal tissue samples. Higher TFRC gene expression levels were strongly associated with higher cancer T stages and OS events. The findings of multivariate analyses illustrated that the OS in CC patients with high TFRC expression is shorter than in patients with low TFRC expression. Significant increases were observed in the levels of TFRC mRNA and protein expression in patients diagnosed with CC. Conclusion: Increased TFRC expression in CC was associated with disease progression, an unfavorable prognosis, and dysregulated immune cell infiltration. In addition, it highlights ferroptosis as a promising therapeutic target for CC.

Nicotinamide riboside restores nicotinamide adenine dinucleotide levels and alleviates brain injury by inhibiting oxidative stress and neuroinflammation in a mouse model of intracerebral hemorrhage.

Hemorrhagic stroke is a global health problem owing to its high morbidity and mortality rates. Nicotinamide riboside is an important precursor of nicotinamide adenine dinucleotide characterized by a high bioavailability, safety profile, and robust effects on many cellular signaling processes. This study aimed to investigate the protective effects of nicotinamide riboside against collagenase-induced hemorrhagic stroke and its underlying mechanisms of action. An intracerebral hemorrhage model was constructed by stereotactically injecting collagenase into the right striatum of adult male Institute for Cancer Research mice. After 30 minutes, nicotinamide riboside was administered via the tail vein. The mice were sacrificed at different time points for assessments. Nicotinamide riboside reduced collagenase-induced hemorrhagic area, significantly reduced cerebral water content and histopathological damage, promoted neurological function recovery, and suppressed reactive oxygen species production and neuroinflammation. Nicotinamide riboside exerts neuroprotective effects against collagenase-induced intracerebral hemorrhage by inhibiting neuroinflammation and oxidative stress.

Novel hypoxia- and lactate metabolism-related molecular subtyping and prognostic signature for colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a serious global health burden because of its high morbidity and mortality rates. Hypoxia and massive lactate production are hallmarks of the CRC microenvironment. However, the effects of hypoxia and lactate metabolism on CRC have not been fully elucidated. This study aimed to develop a novel molecular subtyping based on hypoxia-related genes (HRGs) and lactate metabolism-related genes (LMRGs) and construct a signature to predict the prognosis of patients with CRC and treatment efficacy. METHODS: Bulk and single-cell RNA-sequencing and clinical data of CRC were downloaded from the TCGA and GEO databases. HRGs and LMRGs were obtained from the Molecular Signatures Database. The R software package DESeq2 was used to perform differential expression analysis. Molecular subtyping was performed using unsupervised clustering. A predictive signature was developed using univariate Cox regression, random forest model, LASSO, and multivariate Cox regression analyses. Finally, the sensitivity of tumor cells to chemotherapeutic agents before and after hypoxia was verified using in vitro experiments. RESULTS: We classified 575 patients with CRC into three molecular subtypes and were able to distinguish their prognoses clearly. The C1 subtype, which exhibits high levels of hypoxia, has a low proportion of CD8 + T cells and a high proportion of macrophages. The expression of immune checkpoint genes is generally elevated in C1 patients with severe immune dysfunction. Subsequently, we constructed a predictive model, the HLM score, which effectively predicts the prognosis of patients with CRC and the efficacy of immunotherapy. The HLM score was validated in GSE39582, GSE106584, GSE17536, and IMvigor210 datasets. Patients with high HLM scores exhibit high infiltration of CD8 + exhausted T cells (Tex), especially terminal Tex, and oxidative phosphorylation (OXPHOS)-Tex in the immune microenvironment. Finally, in vitro experiments confirmed that CRC cell lines were less sensitive to 5-fluorouracil, oxaliplatin, and irinotecan under hypoxic conditions. CONCLUSION: We constructed novel hypoxia- and lactate metabolism-related molecular subtypes and revealed their immunological and genetic characteristics. We also developed an HLM scoring system that could be used to predict the prognosis and efficacy of immunotherapy in patients with CRC.

Comprehensive analysis of cuproptosis-related genes involved in immune infiltration and their use in the diagnosis of hepatic ischemia‒reperfusion injury: an experimental Study.

BACKGROUND: Hepatic ischemia reperfusion injury (HIRI) is a common injury not only during liver transplantation but also during major hepatic surgery. HIRI causes severe complications and affects the prognosis and survival of patients. Cuproptosis, a newly identified form of cell death, plays an important role in a variety of illnesses. However, its role in HIRI remains unknown. MATERIALS AND METHODS: The GSE151648 dataset was mined from the Gene Expression Omnibus (GEO) database, and differences were analyzed for intersections. Based on the differentially expressed genes (DEGs), functional annotation, differentially expressed cuproptosis-related genes (DE-CRGs) identification and lasso logistic regression were conducted. Correlation analysis of DE-CRGs and immune infiltration was further conducted, and DE-CRGs were applied to construct an HIRI diagnostic model. The hierarchical clustering method was used to classify the specimens of HIRI, and functional annotation was conducted to verify the accuracy of these DE-CRGs in predicting HIRI progression. The GSE14951 microarray dataset and GSE171539 single-cell sequencing dataset were chosen as validation datasets. At the same time, the significance of DE-CRGs was verified using a mouse model of HIRI with cuproptosis inhibitors and inducers. Finally, a network of transcription-factor-DE-CRGs and miRNA-DE-CRGs was constructed to reveal the regulation mechanisms. And potential drugs for DE-CRGs were predicted using Drug Gene Interaction Database (DGIdb). RESULTS: Overall, 2390 DEGs and 19 DE-CRGs were identified. Through machine learning algorithms, 8 featured DE-CRGs (GNL3, ALAS1, TSC22D2, KLF5, GTF2B, DNTTIP2, SLFN11 and HNRNPU) were screened, and 2 cuproptosis-related subclusters were defined. Based on the 8 DE-CRGs obtained from the HIRI model (AUC=0.97), the nomogram model demonstrated accuracy in predicting HIRI. Eight DE-CRGs were highly expressed in HIRI samples and were negatively related to immune cell infiltration. A higher level of immune infiltration and expression of CRG group B was found in the HIRI population. Differences in cell death and immune regulation were found between the 2 groups. The diagnostic value of the 8 DE-CRGs was confirmed in the validation of two datasets. The identification of 7 DE-CRGs (SLFN11 excluded) by HIRI animal model experiments was also confirmed. Using hTFtarget, miRWalk and DGIDB database, we predicted that 17 transcription factors, 192 miRNAs and 10 drugs might interact with the DE-CRGs. CONCLUSION: This study shows that cuproptosis may occur in HIRI and is correlated with immune infiltration. Additionally, a cuproptosis-related predictive model was constructed for studying the causes of HIRI and developing targeted treatment options for HIRI.

HCCDB v2.0: Decompose Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC.

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma (HCC). Integrated 15 transcriptomic datasets of HCC clinical samples, the first version of HCC database (HCCDB v1.0) was released in 2018. Through the meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets, it provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness. With four years having passed, the database now needs integration of recently published datasets. Furthermore, the latest single-cell and spatial transcriptomics have provided a great opportunity to decipher complex gene expression variations at the cellular level with spatial architecture. Here, we present HCCDB v2.0, an updated version that combines bulk, single-cell, and spatial transcriptomic data of HCC clinical samples. It dramatically expands the bulk sample size by adding 1656 new samples from 11 datasets to the existing 3917 samples, thereby enhancing the reliability of transcriptomic meta-analysis. A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections, respectively. A novel single-cell level and 2-dimension (sc-2D) metric is proposed as well to summarize cell type-specific and dysregulated gene expression patterns. Results are all graphically visualized in our online portal, allowing users to easily retrieve data through a user-friendly interface and navigate between different views. With extensive clinical phenotypes and transcriptomic data in the database, we show two applications for identifying prognosis-associated cells and tumor microenvironment. HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.

Transient pacing in pigs with complete heart block via myocardial injection of mRNA coding for the T-box transcription factor 18.

The adenovirus-mediated somatic transfer of the embryonic T-box transcription factor 18 (TBX18) gene can convert chamber cardiomyocytes into induced pacemaker cells. However, the translation of therapeutic TBX18-induced cardiac pacing faces safety challenges. Here we show that the myocardial expression of synthetic TBX18 mRNA in animals generates de novo pacing and limits innate and inflammatory immune responses. In rats, intramyocardially injected mRNA remained localized, whereas direct myocardial injection of an adenovirus carrying a reporter gene resulted in diffuse expression and in substantial spillover to the liver, spleen and lungs. Transient expression of TBX18 mRNA in rats led to de novo automaticity and pacemaker properties and, compared with the injection of adenovirus, to substantial reductions in the expression of inflammatory genes and in activated macrophage populations. In rodent and clinically relevant porcine models of complete heart block, intramyocardially injected TBX18 mRNA provided rate-adaptive cardiac pacing for one month that strongly correlated with the animal's sinus rhythm and physical activity. TBX18 mRNA may aid the development of biological pacemakers.

A patient-specific lung cancer assembloid model with heterogeneous tumor microenvironments.

Cancer models play critical roles in basic cancer research and precision medicine. However, current in vitro cancer models are limited by their inability to mimic the three-dimensional architecture and heterogeneous tumor microenvironments (TME) of in vivo tumors. Here, we develop an innovative patient-specific lung cancer assembloid (LCA) model by using droplet microfluidic technology based on a microinjection strategy. This method enables precise manipulation of clinical microsamples and rapid generation of LCAs with good intra-batch consistency in size and cell composition by evenly encapsulating patient tumor-derived TME cells and lung cancer organoids inside microgels. LCAs recapitulate the inter- and intratumoral heterogeneity, TME cellular diversity, and genomic and transcriptomic landscape of their parental tumors. LCA model could reconstruct the functional heterogeneity of cancer-associated fibroblasts and reflect the influence of TME on drug responses compared to cancer organoids. Notably, LCAs accurately replicate the clinical outcomes of patients, suggesting the potential of the LCA model to predict personalized treatments. Collectively, our studies provide a valuable method for precisely fabricating cancer assembloids and a promising LCA model for cancer research and personalized medicine.

A combined pre- and intra-operative nomogram in evaluation of degrees of liver cirrhosis predicts post-hepatectomy liver failure: a multicenter prospective study.

Background: Adequate evaluation of degrees of liver cirrhosis is essential in surgical treatment of hepatocellular carcinoma (HCC) patients. The impact of the degrees of cirrhosis on prediction of post-hepatectomy liver failure (PHLF) remains poorly defined. This study aimed to construct and validate a combined pre- and intra-operative nomogram based on the degrees of cirrhosis in predicting PHLF in HCC patients using prospective multi-center's data. Methods: Consecutive HCC patients who underwent hepatectomy between May 18, 2019 and Dec 19, 2020 were enrolled at five tertiary hospitals. Preoperative cirrhotic severity scoring (CSS) and intra-operative direct liver stiffness measurement (DSM) were performed to correlate with the Laennec histopathological grading system. The performances of the pre-operative nomogram and combined pre- and intra-operative nomogram in predicting PHLF were compared with conventional predictive models of PHLF. Results: For 327 patients in this study, histopathological studies showed the rates of HCC patients with no, mild, moderate, and severe cirrhosis were 41.9%, 29.1%, 22.9%, and 6.1%, respectively. Either CSS or DSM was closely correlated with histopathological stages of cirrhosis. Thirty-three (10.1%) patients developed PHLF. The 30- and 90-day mortality rates were 0.9%. Multivariate regression analysis showed four pre-operative variables [HBV-DNA level, ICG-R15, prothrombin time (PT), and CSS], and one intra-operative variable (DSM) to be independent risk factors of PHLF. The pre-operative nomogram was constructed based on these four pre-operative variables together with total bilirubin. The combined pre- and intra-operative nomogram was constructed by adding the intra-operative DSM. The pre-operative nomogram was better than the conventional models in predicting PHLF. The prediction was further improved with the combined pre- and intra-operative nomogram. Conclusions: The combined pre- and intra-operative nomogram further improved prediction of PHLF when compared with the pre-operative nomogram. Trial Registration: Clinicaltrials.gov Identifier: NCT04076631.

FoxO3 Regulates Mouse Bone Mesenchymal Stem Cell Fate and Bone-Fat Balance During Skeletal Aging.

Age-related osteoporosis is characterized by an imbalance between osteogenic and adipogenic differentiation in bone mesenchymal stem cells (BMSCs). Forkhead box O 3 (FoxO3) transcription factor is involved in lifespan and cell differentiation. In this study, we explore whether FoxO3 regulates age-related bone loss and marrow fat accumulation. The expression levels of FoxO3 in BMSCs during aging were detected in vivo and in vitro. To explore the role of FoxO3 in osteogenic and adipogenic differentiation, primary BMSCs were isolated from young and aged mice. FoxO3 expression was modulated by adenoviral vector transfection. The role of FoxO3 in bone-fat balance was evaluated by alizarin red S staining, oil red O staining, quantitative reverse transcription-polymerase chain reaction, Western blot, and histological analysis. Age-related bone loss and fat deposit are associated with downregulation of FoxO3. Overexpression of FoxO3 alleviated age-related bone loss and marrow fat accumulation in aged mice. Mechanistically, FoxO3 reduced adipogenesis and enhanced osteogenesis of BMSCs via downregulation of PPAR-γ and Notch signaling, respectively. In conclusion, FoxO3 is an essential factor controlling the fate of BMSCs and is a potential target for the prevention of age-related osteoporosis.

[A multicenter clinical study on the treatment of lateral epicondylitis of humerus by manipulation].

OBJECTIVE: To investigate clinical effect of tendons pulling,poking and kneading for the treatment of external humeral epicondylitis. METHODS: From January 2018 to December 2021,a multicenter randomized controlled study was performed to collect 192 patients with external humeral epicondylitis in Wangjing Hospital,Beijing Dianli Hospital,and Beijing Fengsheng Osteotraumatology Hospital,respectively,and they were divided into treatment group and control group by random number table method. There were 96 patients in treatment group,including 36 males and 60 females,aged from 28 to 60 years old with an average of (41.20±5.50) years old;the course of disease ranged from 1 to 14 days with an average of (5.24±1.35) days;they were treated once every other day for 2 weeks. There were 96 patients in control group ,including 33 males and 63 females,aged from 26 to 60 years old with an average of (43.35±7.75) years old;the course of disease ranged from 1 to 14 days with an average of (5.86±1.48) days;they were treated with topical voltaalin combined with elbow joint fixation for 2 weeks. Visual analogue scale (VAS) and Hospital for Surgery Scoring System (HSS) elbow pronation and supination angles,wrist metacarpal flexion and dorsal extension angles,elbow tenderness between two groups were compared before treatment and at 1,3,5,7,11 and 13 days after treatment;Hospital for Surgery Scoring System 2 (HSS2) was compared before treatment and the final treatment. RESULTS: All patients were followed up for 10 to 14 days with an average of (12±1.6) days. VAS between treatment group and control group before treatment were 6.83±1.36 and 6.79±1.58,respectively,and decreased to 1.49±1.09 and 2.11±1.81 after the final treatment. VAS of treatment group were significantly lower than those of control group at 1,3,5,7,9,11 and 13 days after treatment (P<0.05). HSS between two groups were 61.73±11.00 and 36.47±12.45 before treatment,respectively,and increased to 94.42±5.9 and 91.44±9.11 at the final treatment. HSS of treatment group were significantly higher than those of control group at 1,3,5,7,9,11 and 13 days after treatment (P<0.05). On the 5th day after treatment,the external and internal rotation angles of elbow in treatment group were (66.41±12.69) ° and (66.35±13.54) °,while those in control group were (62.08±16.03) ° and (61.77±16.35) °. On the 7th day after treatment,the external and internal rotation angles of elbow were (69.79±12.64) ° and (70.02±13.55) ° in treatment group,and (65.28±15.86) ° and (65.09±16.67) ° in control group. Elbow joint motion in treatment group was higher than that in control group (P<0.05). On the 5th day after treatment,angles of wrist dorsiflexion and palm flexion were (39.43±15.94) ° and (46.68±11.10) ° in treatment group,and (38.51±18.49) ° and (44.27±13.58) ° in control group. On the 7th day after treatment,angles of wrist dorsiflexion and palm flexion were (42.52±16.50) ° and (49.23±10.96) ° in treatment group,and (41.18±20.09) ° and (46.64±14.63) ° in control group. The motion of wrist joint in treatment group was higher than that in control group (P<0.05). On the 13th day after treatment,HSS2 in treatment group 93.61±6.32 were higher than those in control group 92.06±7.94(P<0.05). There was no significant difference in elbow tenderness between two groups at each time point (P>0.05). CONCLUSION: Voltaren external treatment combined with elbow fixation and tendons pulling,poking and kneading could effectively improve symptoms of external humeral epicondylitis. Compared with voltaren external treatment,tendons pulling,poking and kneading has advantages of longer analgesic time and better elbow function recovery.

Deep whole-genome analysis of 494 hepatocellular carcinomas.

Over half of hepatocellular carcinoma (HCC) cases diagnosed worldwide are in China1-3. However, whole-genome analysis of hepatitis B virus (HBV)-associated HCC in Chinese individuals is limited4-8, with current analyses of HCC mainly from non-HBV-enriched populations9,10. Here we initiated the Chinese Liver Cancer Atlas (CLCA) project and performed deep whole-genome sequencing (average depth, 120×) of 494 HCC tumours. We identified 6 coding and 28 non-coding previously undescribed driver candidates. Five previously undescribed mutational signatures were found, including aristolochic-acid-associated indel and doublet base signatures, and a single-base-substitution signature that we termed SBS_H8. Pentanucleotide context analysis and experimental validation confirmed that SBS_H8 was distinct to the aristolochic-acid-associated SBS22. Notably, HBV integrations could take the form of extrachromosomal circular DNA, resulting in elevated copy numbers and gene expression. Our high-depth data also enabled us to characterize subclonal clustered alterations, including chromothripsis, chromoplexy and kataegis, suggesting that these catastrophic events could also occur in late stages of hepatocarcinogenesis. Pathway analysis of all classes of alterations further linked non-coding mutations to dysregulation of liver metabolism. Finally, we performed in vitro and in vivo assays to show that fibrinogen alpha chain (FGA), determined as both a candidate coding and non-coding driver, regulates HCC progression and metastasis. Our CLCA study depicts a detailed genomic landscape and evolutionary history of HCC in Chinese individuals, providing important clinical implications.

Clinicopathological characteristics and outcomes of colorectal mucinous adenocarcinoma: a retrospective analysis from China.

Background: Mucinous adenocarcinoma (MAC) is a unique subtype of colorectal cancer and its prognostic value remains controversial. This study aimed to compare the clinicopathological characteristics and prognostic differences between patients with MAC and non-mucinous adenocarcinoma (NMAC). Methods: 674 patients with NMAC, 110 patients with adenocarcinoma with mucinous component (ACWM) and 77 patients with MAC between 2016-2019 were enrolled in the study. Univariate and multivariate Cox regression were performed to analyze the factors associated with prognosis. Predictive nomograms of overall survival (OS) and cancer-specific survival (CSS) for patients with colorectal adenocarcinoma were constructed. Confounding factors were eliminated by propensity score matching (PSM). Results: Compared with patients with NMAC, patients with MAC were more likely to have a tumor located at the proximal colon, present with a larger tumor diameter, more advanced T stage, higher frequency of metastasis, deficiency of mismatch repair, and elevated preoperative carcinoembryonic antigen. Patients with MAC were related to worse OS (HR=2.53, 95%CI 1.73-3.68, p<0.01) and CSS (HR=3.09, 95%CI 2.10-4.57, p<0.01), which persisted after PSM. Subgroup analysis demonstrated that patients with left-sided or stage III/IV MAC exhibited a comparatively worse OS and CSS than those with NMAC. Furthermore, in patients with stage II with a high-risk factor and stage III MAC, adjuvant chemotherapy was associated with an improved OS, CSS, and RFS. Conclusion: Compared with the NMAC phenotype, the MAC phenotype was an independent risk factor for poor prognosis in colorectal adenocarcinoma with worse OS and CSS, particularly patients with left-sided colorectal cancer and stage III/IV. However, patients with MAC can still benefit from adjuvant chemotherapy.

No evidence of coronary plaque stabilization by allopurinol in patients with acute coronary syndrome.

BACKGROUND: Allopurinol, a xanthine inhibitor that lowers uric acid concentration, has been proven to reduce inflammation and oxidative stress in patients with cardiovascular disease. However, it is unknown whether these beneficial effects translate into favorable plaque modification in acute coronary syndromes (ACS). This study aimed to investigate whether allopurinol could improve coronary plaque stabilization using coronary computed tomography angiography (CCTA). METHODS: This was a prospective, single-center, randomized, double-blind clinical trial began in March 2019. A total of 162 ACS patients aged 18-80 years with a blood level of high-sensitivity C-reactive protein (hsCRP) â€‹> â€‹2 â€‹mg/L were included. The subjects were randomly assigned in a 1:1 ratio to receive either allopurinol sustained-release capsules (at a dose of 0.25 â€‹g once daily) or placebo for 12 months. The plaque analysis was performed at CCTA. The primary efficacy endpoint was the change in low-attenuation plaque volume (LAPV) from baseline to the 12-month follow-up. RESULTS: Among 162 patients, 54 in allopurinol group and 51 in placebo group completed the study. The median follow-up duration was 14 months in both groups. Compared with placebo, allopurinol therapy did not significantly alter LAPV (-13.4 â€‹± â€‹3.7 â€‹% vs. -17.8 â€‹± â€‹3.6 â€‹%, p â€‹= â€‹0.390), intermediate attenuation plaque volume (-16.1 â€‹± â€‹3.0 â€‹% vs. -16.2 â€‹± â€‹2.9 â€‹%, p â€‹= â€‹0.992), dense calcified plaque volume (12.2 â€‹± â€‹13.7 â€‹% vs. 9.7 â€‹± â€‹13.0 â€‹%, p â€‹= â€‹0.894), total atheroma volume (-15.2 â€‹± â€‹3.2 â€‹% vs. -16.4 â€‹± â€‹3.1 â€‹%, p â€‹= â€‹0.785), remodeling index (2.0 â€‹± â€‹3.9 â€‹% vs. 5.4 â€‹± â€‹3.8 â€‹%, p â€‹= â€‹0.536) or hsCRP levels (-73.6 [-91.6-17.9] % vs. -81.2 [-95.4-47.7] %, p â€‹= â€‹0.286). CONCLUSIONS: Our findings suggest that allopurinol does not improve atherosclerotic plaque stability or inflammation in ACS.

scCancer2: data-driven in-depth annotations of the tumor microenvironment at single-level resolution.

SUMMARY: Single-cell RNA-seq (scRNA-seq) is a powerful technique for decoding the complex cellular compositions in the tumor microenvironment (TME). As previous studies have defined many meaningful cell subtypes in several tumor types, there is a great need to computationally transfer these labels to new datasets. Also, different studies used different approaches or criteria to define the cell subtypes for the same major cell lineages. The relationships between the cell subtypes defined in different studies should be carefully evaluated. In this updated package scCancer2, designed for integrative tumor scRNA-seq data analysis, we developed a supervised machine learning framework to annotate TME cells with annotated cell subtypes from 15 scRNA-seq datasets with 594 samples in total. Based on the trained classifiers, we quantitatively constructed the similarity maps between the cell subtypes defined in different references by testing on all the 15 datasets. Secondly, to improve the identification of malignant cells, we designed a classifier by integrating large-scale pan-cancer TCGA bulk gene expression datasets and scRNA-seq datasets (10 cancer types, 175 samples, 663 857 cells). This classifier shows robust performances when no internal confidential reference cells are available. Thirdly, scCancer2 integrated a module to process the spatial transcriptomic data and analyze the spatial features of TME. AVAILABILITY AND IMPLEMENTATION: The package and user documentation are available at http://lifeome.net/software/sccancer2/ and https://doi.org/10.5281/zenodo.10477296.

Single-cell transcriptomic analysis reveals tumor cell heterogeneity and immune microenvironment features of pituitary neuroendocrine tumors.

BACKGROUND: Pituitary neuroendocrine tumors (PitNETs) are one of the most common types of intracranial tumors. Currently, the cellular characteristics of normal pituitary and various other types of PitNETs are still not completely understood. METHODS: We performed single-cell RNA sequencing (scRNA-seq) on 4 normal samples and 24 PitNET samples for comprehensive bioinformatics analysis. Findings regarding the function of PBK in the aggressive tumor cells were validated by siRNA knockdown, overexpression, and transwell experiments. RESULTS: We first constructed a reference cell atlas of the human pituitary. Subsequent scRNA-seq analysis of PitNET samples, representing major tumor subtypes, shed light on the intrinsic cellular heterogeneities of the tumor cells and tumor microenvironment (TME). We found that the expression of hormone-encoding genes defined the major variations of the PIT1-lineage tumor cell transcriptomic heterogeneities. A sub-population of TPIT-lineage tumor cells highly expressing GZMK suggested a novel subtype of corticotroph tumors. In immune cells, we found two clusters of tumor-associated macrophages, which were both highly enriched in PitNETs but with distinct functional characteristics. In PitNETs, the stress response pathway was significantly activated in T cells. While a majority of these tumors are benign, our study unveils a common existence of aggressive tumor cells in the studied samples, which highly express a set of malignant signature genes. The following functional experiments confirmed the oncogenic role of selected up-regulated genes. The over-expression of PBK could promote both tumor cell proliferation and migration, and it was also significantly associated with poor prognosis in PitNET patients. CONCLUSIONS: Our data and analysis manifested the basic cell types in the normal pituitary and inherent heterogeneity of PitNETs, identified several features of the tumor immune microenvironments, and found a novel epithelial cell sub-population with aggressive signatures across all the studied cases.

Overview of role of survivin in cancer: expression, regulation, functions, and its potential as a therapeutic target.

Survivin holds significant importance as a member of the inhibitor of apoptosis protein (IAP) family due to its predominant expression in tumours rather than normal terminally differentiated adult tissues. The high expression level of survivin in tumours is closely linked to chemotherapy resistance, heightened tumour recurrence, and increased tumour aggressiveness and serves as a negative prognostic factor for cancer patients. Consequently, survivin has emerged as a promising therapeutic target for cancer treatment. In this review, we delve into the various biological characteristics of survivin in cancers and its pivotal role in maintaining immune system homeostasis. Additionally, we explore different therapeutic strategies aimed at targeting survivin.

STEM enables mapping of single-cell and spatial transcriptomics data with transfer learning.

Profiling spatial variations of cellular composition and transcriptomic characteristics is important for understanding the physiology and pathology of tissues. Spatial transcriptomics (ST) data depict spatial gene expression but the currently dominating high-throughput technology is yet not at single-cell resolution. Single-cell RNA-sequencing (SC) data provide high-throughput transcriptomic information at the single-cell level but lack spatial information. Integrating these two types of data would be ideal for revealing transcriptomic landscapes at single-cell resolution. We develop the method STEM (SpaTially aware EMbedding) for this purpose. It uses deep transfer learning to encode both ST and SC data into a unified spatially aware embedding space, and then uses the embeddings to infer SC-ST mapping and predict pseudo-spatial adjacency between cells in SC data. Semi-simulation and real data experiments verify that the embeddings preserved spatial information and eliminated technical biases between SC and ST data. We apply STEM to human squamous cell carcinoma and hepatic lobule datasets to uncover the localization of rare cell types and reveal cell-type-specific gene expression variation along a spatial axis. STEM is powerful for mapping SC and ST data to build single-cell level spatial transcriptomic landscapes, and can provide mechanistic insights into the spatial heterogeneity and microenvironments of tissues.

Dual-Layer Spectral Detector Computed Tomography Quantitative Parameters: A Potential Tool for Lymph Node Activity Determination in Lymphoma Patients.

Dual-energy CT has shown promising results in determining tumor characteristics and treatment effectiveness through spectral data by assessing normalized iodine concentration (nIC), normalized effective atomic number (nZeff), normalized electron density (nED), and extracellular volume (ECV). This study explores the value of quantitative parameters in contrast-enhanced dual-layer spectral detector CT (SDCT) as a potential tool for detecting lymph node activity in lymphoma patients. A retrospective analysis of 55 lymphoma patients with 289 lymph nodes, assessed through 18FDG-PET/CT and the Deauville five-point scale, revealed significantly higher values of nIC, nZeff, nED, and ECV in active lymph nodes compared to inactive ones (p < 0.001). Generalized linear mixed models showed statistically significant fixed-effect parameters for nIC, nZeff, and ECV (p < 0.05). The area under the receiver operating characteristic curve (AUROC) values of nIC, nZeff, and ECV reached 0.822, 0.845, and 0.811 for diagnosing lymph node activity. In conclusion, the use of g nIC, nZeff, and ECV as alternative imaging biomarkers to PET/CT for identifying lymph node activity in lymphoma holds potential as a reliable diagnostic tool that can guide treatment decisions.

The spatial and single-cell analysis reveals remodeled immune microenvironment induced by synthetic oncolytic adenovirus treatment.

Oncolytic viruses are multifaceted tumor killers, which can function as tumor vaccines to boost systemic antitumor immunity. In previous study, we rationally designed a synthetic oncolytic adenovirus (SynOV) harboring a synthetic gene circuit, which can kill tumors in mouse hepatocellular carcinoma (HCC) models. In this study, we demonstrated that SynOV could sense the tumor biomarkers to lyse tumors in a dosage-dependent manner, and killed PD-L1 antibody resistant tumor cells in mouse model. Meanwhile, we observed SynOV could cure liver cancer and partially alleviate the liver cancer with distant metastasis by activating systemic antitumor immunity. To understand its high efficacy, it is essential to explore the cellular and molecular features of the remodeled tumor microenvironment (TME). By combining spatial transcriptome sequencing and single-cell RNA sequencing, we successfully depicted the remodeled TME at single cell resolution. The state transition of immune cells and stromal cells towards an antitumor and normalized status exemplified the overall cancer-suppressive TME after SynOV treatment. Specifically, SynOV treatment increased the proportion of CD8+ T cells, enhanced the cell-cell communication of Cxcl9-Cxcr3, and normalized the Kupffer cells and macrophages in the TME. Furthermore, we observed that SynOV could induce distant responses to reduce tumor burden in metastatic HCC patient in the Phase I clinical trial. In summary, our results suggest that SynOV can trigger systemic antitumor immunity to induce CD8+ T cells and normalize the abundance of immune cells to remodel the TME, which promises a powerful option to treat HCC in the future.

A recurrence-predictive model based on eight genes and tumor mutational burden/microsatellite instability status in Stage II/III colorectal cancer.

BACKGROUND: Although adjuvant chemotherapy (ACT) is widely used to treat patients with Stage II/III colorectal cancer (CRC), administering ACT to specific patients remains a challenge. The decision to ACT requires an accurate assessment of recurrence risk and absolute treatment benefit. However, the traditional TNM staging system does not accurately assess a patient's individual risk of recurrence. METHODS: To identify recurrence risk-related genetic factors for Stage II/III CRC patients after radical surgery, we conducted an analysis of whole-exome sequencing of 47 patients with Stage II/III CRC who underwent radical surgery at five institutions. Patients were grouped into non-recurrence group (NR, n = 24, recurrence-free survival [RFS] > 5 years) and recurrence group (R, n = 23, RFS <2 years). The TCGA-COAD/READ cohort was employed as the validation dataset. RESULTS: A recurrence-predictive model (G8plus score) based on eight gene (CUL9, PCDHA12, HECTD3, DCX, SMARCA2, FAM193A, AATK, and SORCS2) mutations and tumor mutation burden/microsatellite instability (TMB/MSI) status was constructed, with 97.87% accuracy in our data and 100% negative predictive value in the TCGA-COAD/READ cohort. For the TCGA-COAD/READ cohort, the G8plus-high group had better RFS (HR = 0.22, p = 0.024); the G8plus-high tumors had significantly more infiltrated immune cell types, higher tertiary lymphoid structure signature scores, and higher immunological signature scores. The G8plus score was also a predict biomarker for immunotherapeutic in advanced CRC in the PUCH cohort. CONCLUSIONS: In conclusion, the G8plus score is a powerful biomarker for predicting the risk of recurrence in patients with stage II/III CRC. It can be used to stratify patients who benefit from ACT and immunotherapy.