Comprehensive molecular classification predicted microenvironment profiles and therapy response for HCC.

BACKGROUND AND AIMS: Tumor microenvironment (TME) heterogeneity leads to a discrepancy in survival prognosis and clinical treatment response for patients with HCC. The clinical applications of documented molecular subtypes are constrained by several issues. APPROACH AND RESULTS: We integrated 3 single-cell data sets to describe the TME landscape and identified 6 prognosis-related cell subclusters. Unsupervised clustering of subcluster-specific markers was performed to generate transcriptomic subtypes. The predictive value of these molecular subtypes for prognosis and treatment response was explored in multiple external HCC cohorts and the Xiangya HCC cohort. TME features were estimated using single-cell immune repertoire sequencing, mass cytometry, and multiplex immunofluorescence. The prognosis-related score was constructed based on a machine-learning algorithm. Comprehensive single-cell analysis described TME heterogeneity in HCC. The 5 transcriptomic subtypes possessed different clinical prognoses, stemness characteristics, immune landscapes, and therapeutic responses. Class 1 exhibited an inflamed phenotype with better clinical outcomes, while classes 2 and 4 were characterized by a lack of T-cell infiltration. Classes 5 and 3 indicated an inhibitory tumor immune microenvironment. Analysis of multiple therapeutic cohorts suggested that classes 5 and 3 were sensitive to immune checkpoint blockade and targeted therapy, whereas classes 1 and 2 were more responsive to transcatheter arterial chemoembolization treatment. Class 4 displayed resistance to all conventional HCC therapies. Four potential therapeutic agents and 4 targets were further identified for high prognosis-related score patients with HCC. CONCLUSIONS: Our study generated a clinically valid molecular classification to guide precision medicine in patients with HCC.

A multi-omics analysis reveals CLSPN is associated with prognosis, immune microenvironment and drug resistance in cancers.

BACKGROUND: Immunotherapy is effective only in limited patients. It is urgent to discover a novel biomarker to predict immune cells infiltration status and immunotherapy response of different cancers. CLSPN has been reported to play a pivotal role in various biological processes. However, a comprehensive analysis of CLSPN in cancers has not been conducted. METHODS: To show the whole picture of CLSPN in cancers, a pan-cancer analysis was conducted in 9125 tumor samples across 33 cancer types by integrating transcriptomic, epigenomic and pharmacogenomics data. Moreover, the role of CLSPN in cancer was validated by CCK-8, EDU, colony formation and flow cytometry in vitro and tumor cell derived xenograft model in vivo. RESULTS: CLSPN expression was generally upregulated in most cancer types and was significantly associated with prognosis in different tumor samples. Moreover, elevated CLSPN expression was closely correlated with immune cells infiltration, TMB (tumor mutational burden), MSI (microsatellite instability), MMR (mismatch repair), DNA methylation and stemness score across 33 cancer types. Enrichment analysis of functional genes revealed that CLSPN participated in the regulation of numerous signaling pathways involved in cell cycle and inflammatory response. The expression of CLSPN in LUAD patients were further analyzed at the single-cell level. Knockdown CLSPN significantly inhibited cancer cell proliferation and cell cycle related cyclin-dependent kinase (CDK) family and Cyclin family expression in LUAD (lung adenocarcinoma) both in vitro and in vivo experiments. Finally, we conducted structure-based virtual screening by modelling the structure of CHK1 kinase domain and Claspin phosphopeptide complex. The top five hit compounds were screened and validated by molecular docking and Connectivity Map (CMap) analysis. CONCLUSION: Our multi-omics analysis offers a systematic understanding of the roles of CLSPN in pan-cancer and provides a potential target for future cancer treatment.

BMP4 promotes the metastasis of gastric cancer by inducing epithelial-mesenchymal transition via ID1.

Epithelial-mesenchymal transition (EMT) is a crucial process for cancer cells to acquire metastatic potential, which primarily causes death in gastric cancer (GC) patients. Bone morphogenetic protein 4 (BMP4) is a member of the TGF-ß family that plays an indispensable role in human cancers. However, little is known about its roles in GC metastasis. In this study, BMP4 was found to be frequently overexpressed in GC tissues and was correlated with poor patient's prognosis. BMP4 was upregulated in GC cell lines and promoted EMT and metastasis of GC cells both in vitro and in vivo, whereas knockdown of BMP4 significantly inhibited EMT and metastasis of GC cells. Furthermore, the inhibitor of DNA binding 1 (also known as DNA-binding protein inhibitor ID1) was identified as a downstream target of BMP4 using PCR arrays and was upregulated via SMAD1/5/8 phosphorylation. ID1 knockdown attenuated BMP4-induced EMT and invasion in GC cells. Moreover, ID1 overexpression in BMP4 knockdown cells restored the promotion of EMT and cell invasion. In summary, BMP4 induced EMT and promoted GC metastasis by upregulating ID1 expression. Antagonizing BMP4 could be a potential therapeutic strategy for GC metastasis.

AMICA1 is a diagnostic and prognostic biomarker and induces immune cells infiltration by activating cGAS-STING signaling in lung adenocarcinoma.

BACKGROUND: Adhesion molecule interacting with CXADR antigen 1 (AMICA1), also known as Junction Adhesion Molecule Like (JAML), a recently identified member of the JAMs family, plays a critical role in mediating cancer development and immune cells transmigration. However, AMICA1 has never been reported to be related to the genesis, development and immunotherapy effect of lung adenocarcinoma (LUAD). In this research, we investigated the role of AMICA1 in LUAD through bioinformatic analysis and in vitro experiments. METHODS: Bioinformatic analysis from TCGA and GEO databases were used to investigate the expression level of AMICA1 and the correlation between AMICA1 and clinical parameters in LUAD patients. The LinkedOmics database was analyzed to investigate the co-expression network of AMICA1. TIMER and TISIDB databases were used to analyze the correlation between AMICA1 expression and immune infiltration level. Except for bioinformatic analysis, the AMICA1 mRNA (26 patients) and protein level (6 patients) were also detected by real-time PCR and western blot. The infiltration level of CD8+ T cells (15 patients) and PD1+ T cells (13 patients) were detected by immunohistochemistry. The diagnostic value of AMICA1 was revealed by receiver operating characteristic (ROC) curves. The Spearman correlation coefficient was used to analyze the correlation between AMICA1 expression and CD8+ T cells and PD1+ T cells infiltration level. RESULTS: Bioinformatic data from public database and our data showed that AMICA1 was significantly downregulated in LUAD. Decreased AMICA1 expression in LUAD was associated with higher T stage, M stage and pathological stage. Kaplan-Meier survival analysis indicated that patients with low AMICA1 expression had a worse prognosis. ROC curves showed that AMICA1 had high diagnostic accuracy for LUAD patients. Multivariate Cox analysis further displayed that AMICA1 expression level was an independent prognostic factor for LUAD patients. Moreover, the expression of AMICA1 was significantly different in the immune cells subtype and was obviously linked to immune cells infiltration. In vitro experiments suggested that AMICA1 significantly suppressed the proliferation of LUAD cells and played an important role in activating cGAS-STING signaling. CONCLUSIONS: Our study suggested that AMICA1 might function as a diagnostic and prognostic biomarker and significantly suppressed the proliferation of LUAD cells. Besides, AMICA1 is positively correlated with immune cells infiltration in LUAD, and cGAS-STING signaling might play an important role in the process.

A comprehensive analysis of the efficacy and safety of COVID-19 vaccines.

The numbers of cases and deaths from coronavirus disease 2019 (COVID-19) are continuously increasing. Many people are concerned about the efficacy and safety of the COVID-19 vaccines. We performed a comprehensive analysis of the published trials of COVID-19 vaccines and the real-world data from the Vaccine Adverse Event Reporting System. Globally, our research found that the efficacy of all vaccines exceeded 70%, and RNA-based vaccines had the highest efficacy of 94.29%; moreover, Black or African American people, young people, and males may experience greater vaccine efficacy. The spectrum of vaccine-related adverse drug reactions (ADRs) is extremely broad, and the most frequent ADRs are pain, fatigue, and headache. Most ADRs are tolerable and are mainly grade 1 or 2 in severity. Some severe ADRs have been identified (thromboembolic events, 21-75 cases per million doses; myocarditis/pericarditis, 2-3 cases per million doses). In summary, vaccines are a powerful tool that can be used to control the COVID-19 pandemic, with high efficacy and tolerable ADRs. In addition, the spectrum of ADRs associated with the vaccines is broad, and most of the reactions appear within a week, although some may be delayed. Therefore, ADRs after vaccination need to be identified and addressed in a timely manner.

CLEC10A is a prognostic biomarker and correlated with clinical pathologic features and immune infiltrates in lung adenocarcinoma.

CLEC10A, (C-type lectin domain family 10, member A), as the member of C-type lectin receptors (CLRs), plays a vital role in modulating innate immunity and adaptive immunity and has shown great potential as an immunotherapy target for cancers. However, there is no functional research of CLEC10A in prognostic risk, immunotherapy or any other treatment of lung adenocarcinoma (LUAD). We performed bioinformatics analysis on LUAD data downloaded from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus), and jointly analysed with online databases such as HPA, LinkedOmics, TIMER, ESTIMATE and TISIDB. We found that lower expression of CLEC10A was accompanied with worse outcomes of LUAD patients. Moreover, CLEC10A expression was significantly correlated with a variety of the tumour-infiltrating immune cells (TIICs). As a promising prognosis predictor and potential immunotherapy target, the potential influence and mechanisms of CLEC10A in LUAD deserve further exploring.

Knockdown of Beclin-1 impairs epithelial-mesenchymal transition of colon cancer cells.

Activation of autophagy significantly affects cancer cell behaviors, such as proliferation, differentiation, and invasiveness. Epithelial-to-mesenchymal transition (EMT) as an initial step of malignant transformation of cancer cells was linked to the activation of autophagy, but the detailed molecular mechanisms are still unknown. The present study investigates the effects of Beclin-1, a key molecule involved in activation of autophagy, on EMT of colon cancer cells. The normal colon epithelia cell line of CCD-18Co and six colon cancer cell lines with different expression levels of Beclin-1 were used in this study. The activation of autophagy and EMT markers of cancer cells were monitored by Western blotting and quantitative real-time PCR assay in the presence or absence of rapamycin (autophagy activator) and 3-MA (autophagy inhibitor). The expression of Beclin-1 in selected cell lines was modulated using small interfering RNA, and consequentially EMT markers, and cancer cell behaviors including migration and invasion, were also explored. Activation or inhibition of autophagy in colon cancer cells had positive or negative impacts on the expression of EMT markers and malignant behaviors such as cell migration and invasion. Knockdown of beclin-1 by siRNA apparently inhibited the activation of autophagy induced by rapamycin, consequentially resulted in suppression of EMT and attenuation of invasiveness of colon cancer cells. The results in this study demonstrated an association between activation of autophagy and EMT in colon cancer cells. The results showed suppression of Beclin-1 expression significantly reduced EMT and invasive behaviors in colon cancer cells.

Converting "cold" to "hot": epigenetics strategies to improve immune therapy effect by regulating tumor-associated immune suppressive cells.

Significant developments in cancer treatment have been made since the advent of immune therapies. However, there are still some patients with malignant tumors who do not benefit from immunotherapy. Tumors without immunogenicity are called "cold" tumors which are unresponsive to immunotherapy, and the opposite are "hot" tumors. Immune suppressive cells (ISCs) refer to cells which can inhibit the immune response such as tumor-associated macrophages (TAMs), myeloid-derived suppressor cells (MDSCs), regulatory T (Treg) cells and so on. The more ISCs infiltrated, the weaker the immunogenicity of the tumor, showing the characteristics of "cold" tumor. The dysfunction of ISCs in the tumor microenvironment (TME) may play essential roles in insensitive therapeutic reaction. Previous studies have found that epigenetic mechanisms play an important role in the regulation of ISCs. Regulating ISCs may be a new approach to transforming "cold" tumors into "hot" tumors. Here, we focused on the function of ISCs in the TME and discussed how epigenetics is involved in regulating ISCs. In addition, we summarized the mechanisms by which the epigenetic drugs convert immunotherapy-insensitive tumors into immunotherapy-sensitive tumors which would be an innovative tendency for future immunotherapy in "cold" tumor.

Immune infiltration related CENPI associates with the malignant features and drug resistance of lung adenocarcinoma.

Centromere protein I (CENPI) is an important member of centromeric proteins family, which is crucial to chromosome alignment and segregation. Nevertheless, the interrelation between CENPI expression and tumor progression is in the shadows. In this reserch, we carried out a panoramic bioinformatic analysis about CENPI with TCGA, Timer 2.0, Oncomine, GEPIA, Cbioportal, LinkedOmics and CancerSEA databases. Besides, our bioinformatic results have been further confirmed through in vitro experiments, including Real-Time quantitative PCR (RT-qPCR), immunofluorescence (IF), immunohistochemistry (IHC), western blotting (WB), cell proliferation assays, EdU, cell cycle and apoptosis test. Our results suggested that CENPI was increased in most of the cancers, and may serve as a potential biomarker. What's more, the knock down of CENPI inhibited the expression of CDK2 in lung adenocarcinoma (LUAD), and resulted in the arrest of G0/G1 phase and apoptosis. Besides, CENPI was related to immune cells infiltration and drug sensitivity in pan-cancer, and can act as a potential treatment target to cure cancer patients.

Neuromedin U receptor 1 deletion leads to impaired immunotherapy response and high malignancy in colorectal cancer.

Colorectal cancer (CRC) exhibits significant heterogeneity, impacting immunotherapy efficacy, particularly in immune desert subtypes. Neuromedin U receptor 1 (NMUR1) has been reported to perform a vital function in immunity and inflammation. Through comprehensive multi-omics analyses, we have systematically characterized NMUR1 across various tumors, assessing expression patterns, genetic alterations, prognostic significance, immune infiltration, and pathway associations at both the bulk sequencing and single-cell scales. Our findings demonstrate a positive correlation between NMUR1 and CD8+ T cell infiltration, with elevated NMUR1 levels in CD8+ T cells linked to improved immunotherapy outcomes in patients with CRC. Further, we have validated the NMUR1 expression signature in CRC cell lines and patient-derived tissues, revealing its interaction with key immune checkpoints, including lymphocyte activation gene 3 and cytotoxic T-lymphocyte-associated protein 4. Additionally, NMUR1 suppression enhances CRC cell proliferation and invasiveness. Our integrated analyses and experiments open new avenues for personalized immunotherapy strategies in CRC treatment.

Patient-derived xenograft models in cancer therapy: technologies and applications.

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

A Multi-Omics Analysis of NASH-Related Prognostic Biomarkers Associated with Drug Sensitivity and Immune Infiltration in Hepatocellular Carcinoma.

Background: Nonalcoholic steatohepatitis (NASH)-driven hepatocellular carcinoma (HCC) is becoming a major health-related problem. The exploration of NASH-related prognostic biomarkers and therapeutic targets is necessary. Methods: Data were downloaded from the GEO database. The "glmnet" package was used to identify differentially expressed genes (DEGs). The prognostic model was constructed by the univariate Cox and LASSO regression analyses. Validation of the expression and prognosis by immunohistochemistry (IHC) in vitro. Drug sensitivity and immune cell infiltration were analyzed by CTR-DB and ImmuCellAI. Results: We constructed a prognostic model that identified the NASH-related gene set (DLAT, IDH3B, and MAP3K4), which was validated in a real-world cohort. Next, seven prognostic transcription factors (TFs) were identified. The prognostic ceRNA network included three mRNAs, four miRNAs, and seven lncRNAs. Finally, we found that the gene set was associated with drug response which was validated in six clinical trial cohorts. Moreover, the expression level of the gene set was inversely correlated with CD8 T cell infiltration in HCC. Conclusions: We established a NASH-related prognostic model. Upstream transcriptome analysis and the ceRNA network provided clues for mechanism exploration. The mutant profile, drug sensitivity, and immune infiltration analysis further guided precise diagnosis and treatment strategies.

Lipophagy-related gene RAB7A is involved in immune regulation and malignant progression in hepatocellular carcinoma.

BACKGROUND: RAB7A (RAS-related in Brain 7A) is an important member of the RAS oncogene family. However, the correlation between RAB7A and the development and immune infiltration of hepatocellular carcinoma (HCC) has rarely been studied. Here, we studied the role of RAB7A in HCC through bioinformatics analysis, real-world cohort validation, and in vitro experimental exploration. MATERIALS AND METHODS: The RAB7A expression level was analyzed through TCGA, HPA and TISIDB databases. TIMER and TISCH were used to analyze the correlation between RAB7A and tumor immune microenvironment. The expression of RAB7A was detected through real-time PCR and western blotting. The cell proliferation was detected by EdU and CCK8. Wound-healing and transwell assays were used to test the invasion and migration ability. Cell cycle distribution and reactive oxygen species (ROS) content were analyzed by flow cytometry. Identification of epithelial-mesenchymal transition (EMT) was performed by immunofluorescence double staining. Immunohistochemistry (IHC) was used to evaluate the correlation between RAB7A and immune checkpoints. RESULTS: RAB7A is upregulated in most of the tumor types, and the upregulation of RAB7A is associated with a poorer prognosis in many cancers. The results showed that RAB7A was significantly positively correlated with the infiltration of macrophages and cancer-associated fibroblasts (CAFs), but negatively correlated with M2-type macrophages in most tumors. The single-cell atlas also revealed the distribution and proportion of RAB7A in immune cells of HCC. The in vitro experiments suggested that RAB7A was increased in HCC tissue and cell lines. The knockdown of RAB7A inhibited the activation of the PIK3CA-AKT pathway and suppressed the expression of CDK4, CDK6 and CCNA2. Knockdown of RAB7A induced G0/G1 arrest and ROS accumulation in HCC. In addition, overexpression of RAB7A enhanced migration and invasion by inducing EMT. The real-world cohort showed that the expression level of RAB7A was positively correlated with the expression levels of TGFBR1 and PD-L1. CONCLUSIONS: RAB7A may serve as a potential tumor prognostic and immune infiltration-related biomarker, predicting immunotherapy efficacy in certain cancer types, especially in HCC. Besides, RAB7A was a multi-pathway target involved in the malignant progression of HCC.

RASGRP2 is a potential immune-related biomarker and regulates mitochondrial-dependent apoptosis in lung adenocarcinoma.

Background: Ras guanine nucleotide-releasing protein 2 (RASGRP2), one of the guanine nucleotide exchange factors (GEFs), has attracted much attention in recent years. However, the correlation between RASGRP2 and immune infiltration and malignant features in lung adenocarcinoma (LUAD) has rarely been mentioned. Methods: The Limma package and the LASSO regression model were performed to screen for differentially expressed genes. Data from the TCGA and 5 GEO databases were used to explore the expression level of RASGRP2 in LUAD patients. A weighted co-expression network and LinkFinder module were established to find the related genes of RASGRP2. The ESTIMATE algorithm was used to analyze the correlation between RASGRP2 and immune infiltration in LUAD. Tumor-infiltrating immune cells were sorted and sequenced at the single-cell level to analyze differences in RASGRP2. Real-time PCR and immunohistochemistry were performed in the real-world cohort to verify the expression of RASGRP2 and its correlation with immune-related genes. Clone formation and EdU assays were used to verify the proliferation ability. The proportion of apoptotic cells was analyzed by flow cytometry. Observation of mitochondrial membrane potential (MMP) changes by fluorescence microscopy. Results: Our results suggested that decreased RASGRP2 was associated with worse clinical parameters and prognosis in LUAD patients. And we constructed a FLI1-HSA-miR-1976-RASGRP2 transcriptional network to support the role of RASGRP2. Enrichment analysis revealed that RASGRP2 was involved in lymphocyte activation and leukocyte adhesion. RASGRP2 was found to be positively correlated with the infiltration of most immune cells, immunoregulators, and chemokines in a subsequent study. Meanwhile, the real-world cohort confirmed that the expression levels of PDCD1, CTLA4, CD40LG, CCL14, CXCR5, and CCR7 were higher in the high-RASGRP2 expression group. Cytological experiments proved that RASGRP2 inhibited cell proliferation in LUAD by regulating mitochondrial-dependent apoptosis. Conclusion: RASGRP2 was a potential immune-related biomarker of LUAD. In addition, RASGRP2 was involved in the malignant progression of LUAD through the regulation of mitochondrial-dependent apoptosis.

Neutrophil-lymphocyte ratio and platelet-lymphocyte ratio as potential predictive markers of treatment response in cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis.

Background: The role of platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR) as independent prognostic markers in different tumors is well established. However, there is a limited review of the potential of NLR and PLR as predictors of treatment outcomes from immune checkpoint inhibitors (ICIs). Objective: To establish a correlation between NLR and PLR and the potential of clinical benefit from ICIs. Methods: The literature search was performed for studies that reported the association between NLR, PLR, and treatment outcomes among cancer patients treated with ICIs. The outcomes of interest were objective response rate (ORR), disease control rate (DCR), and progressive disease (PD). ORR was the summation of patients who achieved complete response and partial response. DCR included patients who achieved stable disease. PD was the proportion of patients who progressed, relapsed, or discontinued the treatment. Statistical analysis was performed using the STATA 12.0 package. Heterogeneity was determined by the I2 value. Quality assessment was performed using the Newcastle-Ottawa Scale. Egger's test was used to establish publication bias and sensitivity analysis. Results: A total of 40 papers that met the inclusion criteria were included in the systematic review. However, only 17 studies were used in the meta-analysis to determine the correlation between NLR, PLR, and treatment response. We found that treatment with ICIs and monitoring of outcomes and adverse events using PLR and NLR parameters have been studied in different tumors. Our analysis showed that low NLR correlated with higher ORR (OR = 0.62 (95% CI 0.47-0.81, p = 0.001) and higher DCR (OR = 0.23, 95% CI 0.14-0.36, p < 0.001). Higher NLR predicted a higher probability of PD (OR = 3.12, 95% CI 1.44, 6.77, p = 0.004). Similarly, low PLR correlated with higher ORR (OR = 0.69, 95% CI 0.5, 0.95, p = 0.025). Generally, patients with low NLR and PLR were more likely to achieve clinical benefit and better response (p-value < 0.001). Meanwhile, patients with high ratios were more likely to progress (p-value < 0.005), although there was significant heterogeneity among studies. There was no significant publication bias observed. Conclusion: The study showed that high NLR and PLR either at baseline or during treatment is associated with poorer treatment outcome. Therefore, these ratios can be utilized in clinical practice with other markers to determine treatment efficacy from immunotherapy.

MTFR2 shapes a barrier of immune microenvironment in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death in the world. Mitochondrial fission regulator 2 (MTFR2) is involved in the development of various cancers. However, the roles of MTFR2 in HCC remain unknown. In this study, we conducted a comprehensive analysis of MTFR2 in HCC, which was generated from integrative MTFR2 analyses of eight HCC cell lines, and three datasets (public dataset, real-world dataset, and immunotherapy dataset) derived from bulk HCC tissues, survival, and immunotherapy data. We demonstrated that the expression level of MTFR2 is upregulated in HCC, leading to poor prognosis. MTFR2 is positively correlated with the level of immune cell infiltration, multiple immune checkpoints and immunotherapy response prediction pathways, and acts as an important role in cancer-immunity cycle. In conclusion, our work indicates that MTFR2 can shape a barrier of immune microenvironment and result in poor prognosis in hepatocellular carcinoma, but the immune barrier may be broken by immunotherapy.

A cancer-associated fibroblast subtypes-based signature enables the evaluation of immunotherapy response and prognosis in bladder cancer.

Bladder cancer (BLCA) is one of the most prevalent and heterogeneous urinary malignant tumors. Previous researches have reported a significant association between cancer-associated fibroblasts (CAFs) and poor prognosis of tumor patients. However, uncertainty surrounds the role of CAFs in the BLCA tumor microenvironment, necessitating further investigation into the CAFs-related gene signatures in BLCA. In this study, we identified three CAF subtypes in BLCA according to single-cell RNA-seq data and constructed CAFs-related risk score (CRRS) by screening 102,714 signatures. The survival analysis, ROC curves, and nomogram suggested that CRRS was a valuable predictor in 2,042 patients from 9 available public datasets and Xiangya real-world cohort. We further revealed the significant correlation between CRRS and clinicopathological characteristics, genome alterations, and epithelial-mesenchymal transition (EMT). A high CRRS indicated a non-inflamed phenotype and a lower remission rate of immunotherapy in BLCA. In conclusion, the CRRS had the potential to predict the prognosis and immunotherapy response of BLCA patients.

Identification of the lymph node metastasis-related automated breast volume scanning features for predicting axillary lymph node tumor burden of invasive breast cancer via a clinical prediction model.

Breast cancer has become the malignant tumor with the highest incidence in women. Axillary lymph node dissection (ALND) is an effective method of maintaining regional control; however, it is associated with a significant risk of complications. Meanwhile, whether the patients need ALND or not is according to sentinel lymph node biopsy (SLNB). However, the false-negative results of SLNB had been reported. Automated breast volume scanning (ABVS) is a routine examination in breast cancer. A real-world cohort consisting of 245 breast cancer patients who underwent ABVS examination were enrolled, including 251 tumor lesions. The ABVS manifestations were analyzed with the SLNB results, and the ALND results for selecting the lymph node metastasis were related to ABVS features. Finally, a nomogram was used to construct a breast cancer axillary lymph node tumor burden prediction model. Breast cancer patients with a molecular subtype of luminal B type, a maximum lesion diameter of ≥5 cm, tumor invasion of the Cooper's ligament, and tumor invasion of the nipple had heavy lymph node tumor burden. Molecular classification, tumor size, and Cooper's ligament status were used to construct a clinical prediction model of axillary lymph node tumor burden. The consistency indexes (or AUC) of the training cohort and the validation cohort were 0.743 and 0.711, respectively, which was close to SLNB (0.768). The best cutoff value of the ABVS nomogram was 81.146 points. After combination with ABVS features and SLNB, the AUC of the prediction model was 0.889, and the best cutoff value was 178.965 points. The calibration curve showed that the constructed nomogram clinical prediction model and the real results were highly consistent. The clinical prediction model constructed using molecular classification, tumor size, and Cooper's ligament status can effectively predict the probability of heavy axillary lymph node tumor burden, which can be the significant supplement to the SLNB. Therefore, this model may be used for individual decision-making in the diagnosis and treatments of breast cancer.

Pan-Cancer and Single-Cell Analysis Reveals CENPL as a Cancer Prognosis and Immune Infiltration-Related Biomarker.

Background: Centromere protein L (CENPL) is an important member of the centromere protein (CENP) family. However, the correlation between CENPL expression and cancer development and immune infiltration has rarely been studied. Here, we studied the role of CENPL in pan-cancer and further verified the results in lung adenocarcinoma (LUAD) through in vitro experiments. Methods: The CENPL expression level was studied with TIMER 2.0 and Oncomine databases. The potential value of CENPL as a diagnostic and prognostic biomarker in pan-cancer was evaluated with the TCGA database and GEPIA. The CENPL mutation character was analyzed using the cBioPortal database. The LinkedOmics and CancerSEA databases were used to carry out the function analysis of CENPL. The role of CENPL in immune infiltration was studied using the TIMER and TISIDB websites. Moreover, the expression of CENPL was detected through RT-qPCR and Western blotting. Immunohistochemistry was used to evaluate the infiltration level of CD8+ T cells. Cell proliferation was detected by EdU and CCK8. A flow cytometer was used to analyze the influence of CENPL in cell cycle and apoptosis. Results: CENPL was increased in most of the cancers. The upregulation and mutation of CENPL were associated with a poorer prognosis in many cancers. The results showed a significant positive correlation between CENPL and myeloid-derived suppressor cell (MDSC) infiltration and a negative correlation between CENPL and T-cell NK infiltration in most of the cancers. CENPL regulated cell proliferation and cell cycle, and was negatively correlated with the inflammation level of LUAD. The in vitro experiments suggested that CENPL was increased in LUAD tissue and cell lines. There was a negative correlation between CENPL expression and CD8+ T-cell infiltration. The knockdown of CENPL significantly suppressed the expression of CDK2 and CCNE2, and induced G0/G1 arrest and apoptosis of LUAD. Conclusions: CENPL may function as a potential biomarker and oncogene in pan-cancer, especially LUAD. Furthermore, CENPL was associated with immune cell infiltration in pan-cancer, providing a potential immune therapy target for tumor treatment.