TCF7L2 promotes anoikis resistance and metastasis of gastric cancer by transcriptionally activating PLAUR

Integration analysis of PLAUR as a sunitinib resistance and macrophage related biomarker in ccRCC, an in silicon and experimental study

Sunitinib remains the preferred systemic treatment option for specific patients with advanced RCC who are ineligible for immune therapy. However, it's essential to recognize that Sunitinib fails to elicit a favourable response in all patients. Moreover, most patients eventually develop resistance to Sunitinib. Therefore, identifying new targets associated with Sunitinib resistance is crucial. Utilizing multiple datasets from public cohorts, we conducted an exhaustive analysis and identified a total of 8 microRNAs and 112 mRNAs displaying significant expression differences between Sunitinib responsive and resistant groups. A particular set of six genes, specifically NIPSNAP1, STK40, SDC4, NEU1, TBC1D9, and PLAUR, were identified as highly significant via WGCNA. To delve deeper into the resistance mechanisms, we performed additional investigations using cell, molecular, and flow cytometry tests. These studies confirmed PLAUR's pivotal role in fostering Sunitinib resistance, both in vitro and in vivo. Our findings suggest that PLAUR could be a promising therapeutic target across various cancer types. In conclusion, this investigation not only uncovers vital genes and microRNAs associated with Sunitinib resistance in RCC but also introduces PLAUR as a prospective therapeutic target for diverse cancers. The outcomes contribute to advancing personalized healthcare and developing superior therapeutic strategies.

SERPINE1 Facilitates Metastasis in Gastric Cancer Through Anoikis Resistance and Tumor Microenvironment Remodeling

SERPINE1 is a serine protease inhibitor upregulated in various malignancies and pivotal in gastric cancer (GC) metastasis and the tumor microenvironment (TME). This study elucidates the mechanisms by which SERPINE1 mediates anoikis resistance and fosters an immunosuppressive TME in advanced GC. SERPINE1 is highly expressed in GC tissues and metastatic lesions and serves as an independent risk factor for poor prognosis. The transcriptional activation of SERPINE1 by CEBPB triggers the PI3K/AKT and EMT signaling pathway via autocrine mechanisms, enhancing anoikis resistance and metastatic potential in GC cells. Furthermore, SERPINE1 facilitates M2 macrophage polarization by binding to lipoprotein receptor-related protein 1 (LRP1) in a paracrine manner, suppressing CD8+ T-cell infiltration and functionality in the TME. Therapeutic intervention combining SERPINE1 inhibition with PD-1 blockade exhibits synergistic antitumor effects. Clinically, high SERPINE1 expression is associated with an increased risk of recurrence following immune checkpoint inhibitor therapy in patients with advanced GC. These findings suggest that SERPINE1 is a critical driver of GC progression through anoikis resistance and TME remodeling. Hence, SERPINE1 can offer a promising therapeutic target and represent a predictive biomarker for immunotherapy outcomes in GC.

Development of a Nomogram-Based Online Calculator for Predicting Cancer-Specific Survival in Patients With Digestive Tract Mixed Neuroendocrine-Non-Neuroendocrine Neoplasms (MiNENs): An Analysis of the SEER Database

AIMS

Mixed neuroendocrine-non-neuroendocrine neoplasms (MiNENs) represent a rare and heterogeneous subgroup of neoplasms that typically consist of a neuroendocrine (NE) component, most commonly neuroendocrine carcinoma (NEC), alongside a non-neuroendocrine (non-NE) component. They commonly occur in the digestive tract, and their prognosis is influenced by multiple factors. This article aimed to identify factors that affect the cancer-specific survival (CSS) of MiNENs and develop an effective nomogram-based online calculator to validate its effectiveness.

METHODS

The clinical, pathological, epidemiological, and survival data of patients with digestive tract MiNENs were collected from the Surveillance, Epidemiology, and End Results (SEER) database spanning from 2000 to 2020. Then, the dataset was divided into a training cohort and a validation cohort. The χ2 test or Fisher's exact test was utilized to assess differences in demographic and clinicopathological characteristics between the two groups. Kaplan-Meier survival curves and log-rank tests were employed to conduct survival analysis. Additionally, univariate and multivariate Cox regression analyses were performed to identify potential prognostic factors and develop nomograms and an online calculator for predicting CSS at 1, 3, and 5 years. Lastly, the predictive ability of the online calculator was subsequently compared with the sixth edition of the American Joint Committee on Cancer (AJCC) TNM staging system using the Harrell concordance index (C-index), the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA).

RESULTS

A total of 330 patients were randomly assigned to two groups, namely, the training cohort (n = 231) and the validation cohort (n = 99). The log-rank test revealed a significant association between the lower cumulative survival and age ≥ 65 years, poor tumor grade, lack of surgical treatment, TNM stages III and IV, and distant metastasis. In the training cohort, a nomogram incorporating grade, surgery, TNM stage, and tumor metastasis was developed, which demonstrated favorable calibration and discriminatory capabilities. Compared to TNM staging, the nomogram exhibited satisfactory performance in predicting 1-year, 3-year, and 5-year CSS rates. The C-index value was 0.787 in the training cohort and 0.738 in the validation cohort, respectively. In the training cohort, the nomogram achieved an AUC of 85.81%, 85.86%, and 87.32% for 1-year CSS, 3-year CSS, and 5-year CSS, respectively. In contrast, these AUC values were 78.46%, 81.50%, and 83.88% in the validation cohort, respectively.

CONCLUSIONS

The developed online calculator offers a novel approach to predicting the prognosis of patients with digestive tract MiNENs. Indeed, it can accurately predict the CSS of these patients over 1, 3, and 5 years, thereby assisting in enhancing prognosis and formulating appropriate treatment strategies.

Overexpression of Neural Precursor Cell Expressed Developmentally Downregulated 9 (NEDD9) reduces ox-LDL-induced Anoikis in atherosclerotic vascular endothelial cells

Objective

This study purposes to explore the action of the Anoikis gene in vascular endothelial cell injury, explore diagnostic biomarkers, and provide new insights into potential molecular mechanisms, as well as offer a new perspective for disease detection and treatment.

Methods

The Anoikis gene set was used for enrichment analysis on the Gene Expression Omnibus (GEO: GSE100927) dataset, to identify the intersection genes related to Atherosclerosis. Further, the expression and pathway enrichment of Anoikis genes in GSE100927 was investigated. The Least Absolute Shrinkage and Selection Operator (LASSO) method for dimensionality reduction modeling was employed to obtain Atherosclerosis-related genes and construct Anoikis score. The NEDD9, FOSB, and ERCC1 expression in ox-LDL-induced the Bend.3 cells was validated by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Overexpression or silencing NEDD9 on Anoikis in ox-LDL and detachment-induced the Bend.3 cells was analyzed by using Cell Counting Kit-8 (CCK8), 5-Ethynyl-2'-deoxyuridine (EdU), and flow cytometry assays.

Results

Based on Anoikis gene analysis, NFIL3, NR4A3, ADAMTS4, NEDD9, STX17-AS1, and CSF3 were found to be under-expressed, while FOSB and ERCC1 were found to be over-expressed in the atherosclerosis group compared to the normal group. LASSO regression analysis yielded an Anoikis score = -9.522e-01 × NFIL3 - 3.410 × NEDD9 + 2.728e-01 × ADAMTS4 + 1.178 × FOSB + 5.896e-15 × ERCC1 + 1.558e+01. Compared with the blank group, NEDD9, FOSB, and ERCC1 were under-expressed in the ox-LDL intervention group. si-NEDD9 promoted an increase in reactive oxygen species (ROS) and apoptosis levels in the Bend.3 cells intervened by ox-LDL. Transfection with oe-NEDD9 increased the viability of Bend.3 cells induced by the ox-LDL and detachment, while decreasing ROS and apoptosis levels.

Conclusion

This study developed a reliable atherosclerotic Anoikis model for predicting endothelial cell injury. During Anoikis genes, the overexpression of NEDD9 reduces ox-LDL and detachment-induced endothelial cell Anoikis.

Inhibition of programmed cell death by melanoma cell subpopulations reveals mechanisms of melanoma metastasis and potential therapeutic targets

Melanoma is an aggressive type of skin cancer that arises from melanocytes, the cells responsible for producing skin pigment. In contrast to non-melanoma skin cancers like basal cell carcinoma and squamous cell carcinoma, melanoma is more invasive. Melanoma was distinguished by its rapid progression, high metastatic potential, and significant resistance to conventional therapies. Although it accounted for a small proportion of skin cancer cases, melanoma accounts for the majority of deaths caused by skin cancer due to its ability to invade deep tissues, adapt to diverse microenvironments, and evade immune responses. These unique features highlighted the challenges of treating melanoma and underscored the importance of advanced tools, such as single-cell sequencing, to unravel its biology and develop personalized therapeutic strategies. Thus, we conducted a single-cell analysis of the cellular composition within melanoma tumor tissues and further subdivided melanoma cells into subpopulations. Through analyzing metabolic pathways, stemness genes, and transcription factors (TFs) among cells in different phases (G1, G2/M, and S) as well as between primary and metastatic foci cells, we investigated the specific mechanisms underlying melanoma metastasis. We also revisited the cellular stemness and temporal trajectories of melanoma cell subpopulations, identifying the core subpopulation as C0 SOD3 + Melanoma cells. Our findings revealed a close relationship between the pivotal C0 SOD3 + Melanoma cells subpopulation and oxidative pathways in metastatic tumor tissues. Additionally, we analyzed prognostically relevant differentially expressed genes (DEGs) within the C0 SOD3 + Melanoma cells subpopulation and built a predictive model associated with melanoma outcomes. We selected the gene IGF1 with the highest coefficient (coef) value for further analysis, and experimentally validated its essential function in the proliferation and invasive metastasis of melanoma. In immune infiltration analysis, we discovered the critical roles played by M1/M2 macrophages in melanoma progression and immune evasion. Furthermore, the development and progression of malignant melanoma were closely associated with various forms of programmed cell death (PCD), including apoptosis, autophagic cell death, ferroptosis, and pyroptosis. Melanoma cells often resisted cell death mechanisms, maintaining their growth by inhibiting apoptosis and evading autophagic cell death. Meanwhile, the induction of ferroptosis and pyroptosis was thought to trigger immune responses that helped suppress melanoma dissemination. A deeper understanding of the relationship between melanoma and PCD pathways provided a critical foundation for developing novel targeted therapies, with the potential to enhance melanoma treatment efficacy. These findings contributed to the development of novel prognostic models for melanoma and shed light on research directions concerning melanoma metastasis mechanisms and therapeutic targets.

Training and experimental validation a novel anoikis- and epithelial‒mesenchymal transition-related signature for evaluating prognosis and predicting immunotherapy efficacy in gastric cancer

Anoikis resistance and improper activation of epithelial‒mesenchymal transition (EMT) are critical factors in tumor metastasis and progression. Despite their interaction, the combined impact of anoikis and EMT on prognosis and immunotherapy in gastric cancer remains underexplored. In this study, we identified 354 anoikis- and EMT-related genes (AERGs) through Venn analysis and performed unsupervised clustering to classify gastric cancer patients into two molecular clusters: A and B. Molecular cluster A showed poor prognosis and an immunosuppressive tumor microenvironment, suggesting a "cold tumor" phenotype. Then, a novel AERG-related prognostic model comprising CD24, CRYAB, MMP11, MUC4, PRKAA2, SERPINE1, SKP2, and TP53 was constructed and validated, accurately predicting the 1-, 3-, and 5-year survival rates of gastric cancer patients. Multivariate analysis revealed that the AERG-related risk score was an independent prognostic factor (hazard ratio = 1.651, 95% confidence interval = 1.429-1.907, P<0.001). Further studies demonstrated that, compared to the high-risk group, the low-risk group exhibited higher CD8+ T cell infiltration, tumor mutational burden, immunophenoscores, and lower tumor immune dysfunction and exclusion scores, indicating potential sensitivity to immunotherapy. RT‒qPCR and immunohistochemical staining validated the expression levels of the model's molecular markers. Overall, our AERG-related model shows promise for predicting outcomes and guiding the selection of tailored and precise therapies for gastric cancer patients.

Identification of Anoikis-related potential biomarkers and therapeutic drugs in chronic thromboembolic pulmonary hypertension via bioinformatics analysis and in vitro experiment

There is growing evidence that programmed cell death plays a significant role in the pathogenesis of chronic thromboembolic pulmonary hypertension (CTEPH). Anoikis is a newly discovered type of programmed death and has garnered great attention. However, the precise involvement of Anoikis in the progression of CTEPH remains poorly understood. The goal of this study was to identify Anoikis-related genes (ARGs) and explore potential therapeutic drugs for CTEPH. Differentially expressed genes were identified by limma and weighted gene co-expression network analysis (WGCNA) packages, and functional analyses were conducted based on the differentially expressed genes. Subsequently, a combination of protein-protein interaction (PPI), Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine Recursive Feature Elimination (SVM-RFE) methodologies was employed to screen hub genes associated with CTEPH, which were further verified by dataset GSE188938, quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot. CIBERSORT was utilized to evaluate the infiltration of immune cells and the relationship between infiltration-related immune cells and ARGs. Finally, targeted drug analysis and molecular docking were used to predict drugs targeting Anoikis process to treat CTEPH. Thirty-two differentially expressed genes related to Anoikis and CTEPH were screened through WGCNA analysis. Then, the key ARGs FASN, PLAUR, BCL2L1, HMOX1 and RHOB were screened by PPI, Lasso and SVM-RFE machine learning. Validation through dataset GSE188938, qRT-PCR, and Western blot analyses confirmed HMOX1 and PLAUR as powerful and promising biomarkers in CTEPH. In addition, CIBERSORT immunoinfiltration revealed that Mast_cells_activated and Neutrophils were involved in the pathological regulation of CTEPH. Correlation analysis indicated that HMOX1 was positively correlated with Neutrophils, while PLAUR was negatively correlated with Mast_cells_activated. Finally we used targeted drug analysis and molecular docking to identify that STANNSOPORFIN as a potential drug targeting HMOX1 for the treatment of CTEPH. HMOX1 and PLAUR emerge as potential biomarkers for CTEPH and may influence the development of CTEPH by regulating Anoikis. Mast_cells_activated and Neutrophils may be involved in Anoikis resistance in CTEPH patients, presenting novel insights into CTEPH therapeutic targets. STANNSOPORFIN is a potential agents targeting Anoikis process therapy for CTEPH.

Integrative analysis of multi-omics data identified PLG as key gene related to Anoikis resistance and immune phenotypes in hepatocellular carcinoma

PURPOSE

The extracellular matrix (ECM) plays a pivotal role in the initiation and progression of hepatocellular carcinoma (HCC) by facilitating the proliferation of HCC cells and enabling resistance to Anoikis. ECM also provide structural support that aids in the invasion of HCC cells, thereby influencing the tumor microenvironment. Due to genetic variations and molecular heterogeneity, significant challenges exist in the treatment of HCC, particularly with immunotherapy, which frequently leads to immune tolerance and suboptimal immune responses. Therefore, there is an urgent need for a multi-omics-based classification system for HCC that clarifies the molecular mechanisms underlying the establishment of immune phenotypes and Anoikis resistance in HCC cells. In this study, we employed advanced clustering algorithms to analyze and integrate multi-omics data from HCC patients, with the objective of identifying key genes that possess prognostic potential associated with the Anoikis resistance phenotype. This methodology resulted in the development of a consensus machine learning-driven signature (CMLS), which demonstrates robust predictive capabilities by examining variations in epigenetics, transcription, and immune metabolism, as well as their effects on the core differential gene, plasminogen (PLG).

RESULTS

The integrated multi-omics approach has identified PLG as a critical node within the gene regulatory network associated with Anoikis resistance and immunometabolic phenotypes. As an independent risk factor for poor prognosis in patients with HCC, PLG facilitates Anoikis resistance and enhances the migration of HCC cells. This study provides novel insights into the molecular subtypes of HCC through the application of robust clustering algorithms based on multi-omics data. The constructed CMLS serves as a valuable tool for early prognostic prediction and for screening potential drug candidates that may enhance the efficacy of immunotherapy, thereby establishing a foundation for personalized treatment strategies in HCC.

CONCLUSIONS

Our data underscore the pivotal role of PLG in the development of Anoikis resistance and the immunometabolic phenotype in HCC cells. Furthermore, we present compelling experimental evidence that PLG functions as a significant tumor promoter, suggesting its potential as a target for the formulation of tailored therapeutic strategies for HCC.

Single-cell analysis reveals that TCF7L2 facilitates the progression of ccRCC via tumor-associated macrophages

BACKGROUND

Tumor-associated macrophages (TAMs) play an important role in the recurrence and progression of clear cell renal cell carcinoma (ccRCC). However, the specified mechanism has not been elucidated.

METHODS

Single-cell and transcriptome analysis were applied to characterize the heterogeneity of TAMs. SCENIC would infer regulators of different subsets of TAMs. The CellChat algorithm was used to infer macrophage-tumor interaction networks, whereas pseudo-time traces were used to parse cell evolution and dynamics.

RESULTS

In this study, single-cell transcriptomic data of ccRCC were analyzed. Notably, the macrophages were clustered to select the cluster with a tendency toward M2-type TAM, which has an impact on the occurrence and metastasis of ccRCC. This macrophage cluster was defined as "TAM2". And this study revealed that TCF7L2 as a potential transcription factor regulating TAM2 transcriptional heterogeneity and differentiation. Pseudotime traces showed TCF7L2 trajectories during TAM2 cell cluster development. In addition, the results of cell interaction showed that TAM2 had the highest number and strength of interactions with cancer cells and endothelial cells. In vitro experiments, this study found that TCF7L2 was highly expressed in TAMs and promoted the polarization of macrophages to M2-type macrophages. And then overexpression of TCF7L2 in macrophages markedly promoted ccRCC invasion and proliferation.

CONCLUSION

TCF7L2 could play a key role in the progression of ccRCC via enhancing TAMs recruitment and M2-type polarization.

Inhibition of PI3K/Akt/mTOR Signaling Pathway Suppresses 5-Fluorouracil Resistance in Gastric Cancer

BACKGROUND

At present, 5-Fluorouracil (5-FU) is a crucial anti-cancer drug and is widely used for the treatment of various carcinomas, including gastric cancer (GC). The resistance of GC cells to 5-FU is still a matter of great concern.

OBJECTIVE

To illustrate the role of PI3K/Akt/mTOR signaling in regulating the cell cycle progression and migration of 5-FU-resistant GC cells.

MATERIAL AND METHODS

After the establishment of drug-resistant GC cell lines, the effects of 5-FU and/or BEZ235 (the dual inhibitor of PI3K and mTOR) on the activity of parental or drug-resistant GC cells were explored. The viability and localization of GC cells (MKN-45 and MKN-74) and their drug-resistant cells (MKN-45/R and MKN-74/R) were assessed using MTT assays and immunofluorescence staining. The impacts of 5-FU and/or BEZ235 on GC cell cycle progression and cell migration were assessed via flow cytometry analyses and wound healing assays, respectively. GC tissues were collected from patients with GC sensitive or refractory to 5-FU chemotherapy. RT-qPCR and western blot were conducted to measure PI3K, AKT, and mTOR levels in GC cells or tissues.

RESULTS

After 5-FU treatment, GC cells displayed 5-FU resistance and the viability of drug-resistant cells (MKN-45/R and MKN-74/R) was higher than that of parental cells (MKN-45 and MKN-74). The IC50 values for MKN-45 and MKN-45/R were 8.93 ug/ml and 140 ug/ml, and the values for MKN-74 and MKN-74/R were 3.93 ug/ml and 114.29 ug/ml. Additionally, the PI3K/Akt/mTOR signaling pathway was activated in drug-resistant GC cells and tumor tissues of patients refractory to 5-FU chemotherapy, as evidenced by high PI3K, Akt, and mTOR levels in MKN-45/R, MKN-74/R, and GC tissues resistant to 5-FU. BEZ235 promoted cell cycle arrest and suppressed the migration of GC cells. Moreover, the combination of BEZ235 and 5-FU led to more effective suppressive influence on cell cycle progression and cell migration relative to the single 5-FU or BEZ235 treatment.

CONCLUSIONS

Silencing of the PI3K/Akt/mTOR signaling pathway suppressed the 5-FU resistance of GC cells.

Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response

Background/Objectives: Anoikis-related genes (ANRGs) are crucial in the invasion and metastasis of breast cancer (BC). The underlying role of ANRGs in the prognosis of breast cancer patients warrants further study. Methods: The anoikis-related prognostic signature (ANRS) was generated using a variety of machine learning methods, and the correlation between the ANRS and the tumor microenvironment (TME), drug sensitivity, and immunotherapy was investigated. Moreover, single-cell analysis and spatial transcriptome studies were conducted to investigate the expression of prognostic ANRGs across various cell types. Finally, the expression of ANRGs was verified by RT-PCR and Western blot analysis (WB), and the expression level of PLK1 in the blood was measured by the enzyme-linked immunosorbent assay (ELISA). Results: The ANRS, consisting of five ANRGs, was established. BC patients within the high-ANRS group exhibited poorer prognoses, characterized by elevated levels of immune suppression and stromal scores. The low-ANRS group had a better response to chemotherapy and immunotherapy. Single-cell analysis and spatial transcriptomics revealed variations in ANRGs across cells. The results of RT-PCR and WB were consistent with the differential expression analyses from databases. NU.1025 and imatinib were identified as potential inhibitors for SPIB and PLK1, respectively. Additionally, findings from ELISA demonstrated increased expression levels of PLK1 in the blood of BC patients. Conclusions: The ANRS can act as an independent prognostic indicator for BC patients, providing significant guidance for the implementation of chemotherapy and immunotherapy in these patients. Additionally, PLK1 has emerged as a potential blood-based diagnostic marker for breast cancer patients.

HIF1A/PCDH7 axis mediates fatty acid synthesis and metabolism to inhibit lung adenocarcinoma anoikis

BACKGROUND

Aberrantly expressed PCDH7 participates in the malignant progression of many cancers. PCDH7 has been newly discovered as a risk factor in lung cancer, but its functional study in lung adenocarcinoma (LUAD) has not been conducted yet. This study aimed to investigate the functional role of PCDH7 in LUAD.

METHODS

Bioinformatics analyzed the expression of PCDH7 and HIF1A in LUAD tissues, predicted the binding sites between the two, analyzed the clinicopathological relevance of PCDH7 and examined the pathway enrichment of PCDH7. Expression of PCDH7 and HIF1A in LUAD cells was analyzed by RT-qPCR. A nude mouse transplantation tumor model was constructed to analyze the effect of PCDH7 on tumor growth in vivo. The binding relationship between PCDH7 and HIF1A was confirmed by chromatin immunoprecipitation experiments and the dual-luciferase assay. Cell viability was detected with Cell Counting Kit-8. Triglyceride content and Caspase3 activity were measured using corresponding reagent kits. FASN and ACC1 expression was determined utilizing western blot.

RESULTS

PCDH7 was highly expressed in LUAD and correlated with patients' overall survival time and N stage. In vitro and in vivo experiments confirmed that PCDH7 could promote LUAD growth and anoikis resistance. Moreover, overexpression of PCDH7 markedly increased the content of triglycerides in cells and promoted the expression of FASN and ACC1 proteins to inhibit LUAD cell anoikis. Cell rescue experiment confirmed that HIF1A activated PCDH7 to suppress LUAD anoikis by promoting fatty acid (FA) synthesis and metabolism.

CONCLUSION

Our findings demonstrated that the HIF1A/PCDH7 axis suppressed LUAD anoikis by promoting FA synthesis and metabolism. The FA synthesis pathway might be a key pathway regulated by PCDH7 in LUAD anoikis.

Expression of Anoikis-Related Genes and Potential Biomarkers in Colon Cancer Based on RNA-seq and scRNA-seq

Colon cancer (CC) is a malignant tumor in the colon. Despite some progress in the early detection and treatment of CC in recent years, some patients still experience recurrence and metastasis. Therefore, it is urgent to better predict the prognosis of CC patients and identify new biomarkers. Recent studies have shown that anoikis-related genes (ARGs) play a significant role in the progression of many tumors. Hence, it is essential to confirm the role of ARGs in the development and treatment of CC by integrating scRNA-seq and transcriptome data. This study integrated transcriptome and single-cell sequencing (scRNA-seq) data from CC samples to evaluate patient stratification, prognosis, and ARG expression in different cell types. Specifically, differential expression of ARGs was identified through consensus clustering to classify CC subtypes. Subsequently, a CC risk model composed of CDKN2A, NOX4, INHBB, CRYAB, TWIST1, CD36, SERPINE1, and MMP3 was constructed using prognosis-related ARGs. Finally, using scRNA-seq data of CC, the expression landscape of prognostic genes in different cell types and the relationship between important immune cells and other cells were explored. Through the above analysis, two CC subtypes were identified, showing significant differences in prognosis and clinical factors. Subsequently, a risk model comprising aforementioned genes successfully categorized all CC samples into two risk groups, which also exhibited significant differences in prognosis, clinical factors, involved pathways, immune landscape, and drug sensitivity. Multiple pathways (cell adhesion molecules (CAMs), and extracellular matrix (ECM) receptor interaction) and immune cells/immune functions (B cell naive, dendritic cell activate, plasma cells, and T cells CD4 memory activated) related to CC were identified. Furthermore, it was found that prognostic genes were highly expressed in various immune cells, and B cells exhibited more and stronger interaction pathways with other cells. The results of this study may provide references for personalized treatment and potential biomarker identification in CC.

Development and verification of a novel risk model related to ubiquitination linked with prognosis and therapeutic response in clear cell renal cell carcinoma

Increasing evidence highlights the important role of ubiquitination in cancer. The objective of our study is to establish a reliable marker for predicting clinical outcomes and treatment responses in patients with clear cell renal cell carcinoma (ccRCC) using genes related to ubiquitination (URGs). The URGs subtypes were identified using consensus clustering based on TCGA-KIRC, and a signature containing the prognostic differentially expressed genes of the subtypes was determined using LASSO and Cox regression analysis. To demonstrate the strength of the signature, verification analyses were performed on both E-MTAB-1980 and TCGA-KIRC test datasets. We developed a nomogram to enhance the effectiveness of our predictive tool. Risk genes expression was determined through RT-qPCR. Six genes were combined to create the URGs signature, which had a highly correlated with patient prognosis in patients with ccRCC. A nomogram was developed based on the URGs signature and clinicopathological characteristics. We found that the predictive power was substantially greater than the other individual predictors. Moreover, the study on the immune microenvironment revealed significant variations in the levels of immune cells and the expression of immune checkpoint genes among the groups categorized as high-risk and low-risk. Furthermore, it was found that immunotherapy yielded better outcomes in cohorts with low risk. The URGs signature might serve as a novel and powerful prognosis biomarker and offer a momentous reference for individualized treatment for patients in ccRCC.

Identification of Gαi3 as a promising molecular oncotarget of pancreatic cancer

The increasing mortality rate of pancreatic cancer globally necessitates the urgent identification for novel therapeutic targets. This study investigated the expression, functions, and mechanistic insight of G protein inhibitory subunit 3 (Gαi3) in pancreatic cancer. Bioinformatics analyses reveal that Gαi3 is overexpressed in human pancreatic cancer, correlating with poor prognosis, higher tumor grade, and advanced classification. Elevated Gαi3 levels are also confirmed in human pancreatic cancer tissues and primary/immortalized cancer cells. Gαi3 shRNA or knockout (KO) significantly reduced cell viability, proliferation, cell cycle progression, and mobility in primary/immortalized pancreatic cancer cells. Conversely, Gαi3 overexpression enhanced pancreatic cancer cell growth. RNA-sequencing and bioinformatics analyses of Gαi3-depleted cells indicated Gαi3's role in modulating the Akt-mTOR and PKA-Hippo-YAP pathways. Akt-S6 phosphorylation was decreased in Gαi3-depleted cells, but was increased with Gαi3 overexpression. Additionally, Gαi3 depletion elevated PKA activity and activated the Hippo pathway kinase LATS1/2, leading to YAP/TAZ inactivation, while Gαi3 overexpression exerted the opposite effects. There is an increased binding between Gαi3 promoter and the transcription factor TCF7L2 in pancreatic cancer tissues and cells. Gαi3 expression was significantly decreased following TCF7L2 silencing, but increased with TCF7L2 overexpression. In vivo, intratumoral injection of Gαi3 shRNA-expressing adeno-associated virus significantly inhibited subcutaneous pancreatic cancer xenografts growth in nude mice. A significant growth reduction was also observed in xenografts from Gαi3 knockout pancreatic cancer cells. Akt-mTOR inactivation and increased PKA activity coupled with YAP/TAZ inactivation were also detected in xenograft tumors upon Gαi3 depletion. Furthermore, bioinformatic analysis and multiplex immunohistochemistry (mIHC) staining on pancreatic cancer tissue microarrays showed a reduced proportion of M1-type macrophages and an increase in PD-L1 positive cells in Gαi3-high pancreatic cancer tissues. Collectively, these findings highlight Gαi3's critical role in promoting pancreatic cancer cell growth, potentially through the modulation of the Akt-mTOR and PKA-Hippo-YAP pathways and its influence on the immune landscape.

Malignant Transformation of Normal Oral Tissue to Dysplasia and Early Oral Squamous Cell Carcinoma: An In Silico Transcriptomics Approach

Background: Oral squamous cell carcinoma (OSCC) is a prevalent and aggressive form of head and neck cancer, often diagnosed at advanced stages. Elucidating the molecular mechanisms involved in the malignant transformation from normal oral tissue to oral preinvasive lesions (OPL) and primary OSCC could facilitate early diagnosis and improve therapeutic strategies. Methods: Differentially expressed genes (DEGs) were identified from the GSE30784 dataset by comparing normal oral tissue, oral dysplasia, and primary OSCC samples. Cross-validation was performed using an independent RNA-seq dataset, GSE186775. Protein-protein interaction (PPI) network analysis, gene ontology annotation, and pathway enrichment analysis were conducted on the common DEGs. Hub genes were identified, and their prognostic significance was evaluated using survival analysis. Transcription factor (TF) enrichment analysis, cross-validation, and immunohistochemistry analyses were also performed. Results: A total of 226 proteins and 677 interactions were identified in the PPI network, with 34 hub genes, including FN1, SERPINE1, PLAUR, THBS1, and ITGA6. Pathways such as "Formation of the cornified envelope," "Keratinization," and "Developmental biology" were enriched. Overexpression of SERPINE1, PLAUR, THBS1, and ITGA6 correlated with poor prognosis, while upregulation of CALML5 and SPINK5 was associated with favorable outcomes. NFIB emerged as the most significant TF-regulating hub genes. Immunohistochemistry validated ITGA6 overexpression in primary OSCC. Cross-validation using the RNA-seq dataset supported the involvement of critical genes in the malignant transformation process. Conclusion: This study identified vital genes, pathways, and prognostic markers involved in the malignant transformation from normal oral tissue to OPL and primary OSCC, providing insights for early diagnosis and targeted therapy development. Cross-validation with an independent RNA-seq dataset and immunohistochemistry reinforced the findings, supporting the robustness of the identified molecular signatures.

ATP11A Promotes Epithelial-mesenchymal Transition in Gastric Cancer Cells via the Hippo Pathway

Background: ATP11A, a P-type ATPase, functions as flippases at the plasma membrane to maintain cellular function and vitality in several cancers. However, the role of ATP11A in gastric cancer remains unknown. This study aimed to identify ATP11A related to the biological behavior of gastric cancer, and elucidate the underlying mechanism. Methods: The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were used to analyze the expression and prognosis of ATP11A. The biofunctions of ATP11A were explored through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA). The expression of ATP11A were validated by immunohistochemistry (IHC), qRT-PCR and Western blotting. Transwell, wound healing, CCK8 and colony-formation were to detected the migration, invasion and proliferation of gastric cancer cells. The epithelial-mesenchymal transition (EMT) and Hippo pathway markers were examined by Western blotting. Results: The expression of ATP11A was higher in gastric cancer tissues than in normal tissues, and high ATP11A levels were related to worse prognosis of gastric cancer patients. Additionally, we proved that ATP11A promoted the migration, invasion and proliferation in gastric cancer cells. Furthermore, ATP11A was found to promote EMT by devitalizing the Hippo pathway. Conclusion: ATP11A promoted migration, invasion, proliferation and EMT via Hippo signaling devitalization in gastric cancer cells.

Unraveling the relationship between anoikis-related genes and cancer-associated fibroblasts in liver hepatocellular carcinoma

This study intended to determine the molecular subtypes of liver hepatocellular carcinoma (LIHC) on the strength of anoikis-related genes (ARGs) and to assess their prognostic value and prospective relationship with immune cell infiltration and cancer-associated fibroblasts (CAFs). Univariate Cox regression analysis yielded 66 prognosis-related ARGs and classified LIHC into two distinct subtypes, with subtype A demonstrating overexpression of most prognosis-related ARGs and a significant survival disadvantage. Furthermore, a reliable prediction model was developed using ARGs to evaluate the risk of LIHC patients. This model served as an independent prognostic indicator and a quantitative tool for clinical prognostic prediction. Additionally, subtype-specific differences in immune cell infiltration were observed, and the risk score was potentially linked to immune-related characteristics. Moreover, the study identified a significant association between CAF score and LIHC prognosis, with a low CAF score indicating a favorable patient prognosis. In conclusion, this study reveals the molecular mechanisms underlying the development and progression of LIHC and identifies potential therapeutic targets for the disease.

Transcription factor 7 like 2 promotes metastasis in hepatocellular carcinoma via NEDD9-mediated activation of AKT/mTOR signaling pathway

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the digestive system, and the exact mechanism of HCC is still unclear. Transcription factor 7 like 2 (TCF7L2) plays a pivotal role in cell proliferation and stemness maintenance. However, the exact mechanism of TCF7L2 in HCC remains unclear.

METHODS

Clinical samples and public databases were used to analyze the expression and prognosis of TCF7L2 in HCC. The function of TCF7L2 in HCC was studied in vitro and in vivo. ChIP and luciferase assays were used to explore the molecular mechanism of TCF7L2. The relationship between TCF7L2 and NEDD9 was verified in HCC clinical samples by tissue microarrays.

RESULTS

The expression of TCF7L2 was upregulated in HCC, and high expression of TCF7L2 was associated with poor prognosis of HCC patients. Overexpression of TCF7L2 promoted the metastasis of HCC in vitro and in vivo, while Knockdown of TCF7L2 showed the opposite effect. Mechanically, TCF7L2 activated neural precursor cell expressed developmentally downregulated protein 9 (NEDD9) transcription by binding to the -1522/-1509 site of the NEDD9 promoter region, thereby increasing the phosphorylation levels of AKT and mTOR. The combination of TCF7L2 and NEDD9 could distinguish the survival of HCC patients.

CONCLUSIONS

This study demonstrated that TCF7L2 promotes HCC metastasis by activating AKT/mTOR pathway in a NEDD9-dependent manner, suggesting that potential of TCF7L2 and NEDD9 as prognostic markers and therapeutic targets for HCC.

Prognostic analysis of anoikis-related genes in bladder cancer: An observational study

Anoikis is proved to play a crucial role in the development of cancers. However, the impact of anoikis on the prognosis of bladder cancer (BLCA) is currently unknown. Thus, this study aimed to find potential effect of anoikis in BLCA. The Cancer Genome Atlas (TCGA)-BLCA and GSE13507 cohorts were downloaded from TCGA and the Gene Expression Omnibus (GEO) databases, respectively. Differentially expressed genes (DEGs) were screened between BLCA and normal groups, which intersected with anoikis-related genes to yield anoikis-related DEGs (AR DEGs). Univariate COX, rbsurv, and multivariate COX analyses were adopted in order to build a prognostic risk model. The differences of risk score in the different clinical subgroups and the relevance between survival rate and clinical characteristics were explored as well. Finally, chemotherapy drug sensitivity in different risk groups was analyzed. In total, 78 AR DEGs were acquired and a prognostic signature was build based on the 6 characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1), where the patients of low-risk group had longer survival time. The survival rate of BLCA patients was significantly differential in different groups of age, stage, smoking history, pathologic-T, and pathologic-N. The IC50 of 56 drugs showed significant differences between 2 risk groups, such as imatinib, docetaxel, and dasatinib. At last, the results of real time quantitative-polymerase chain reaction (RT-qPCR) demonstrated that the expression trend of CALR, HGF, and INHBB was consistent with the result obtained previously based on public databases. Taken together, this study identified 6 anoikis-related characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1) for the prognosis of BLCA patients, providing a scientific reference for further research on BLCA.

High Glucose Increases Lactate and Induces the Transforming Growth Factor Beta-Smad 1/5 Atherogenic Pathway in Primary Human Macrophages

Hundreds of millions of people worldwide are expected to suffer from diabetes mellitus. Diabetes is characterized as a dynamic and heterogeneous disease that requires deeper understanding of the pathophysiology, genetics, and metabolic shaping of this disease and its macro/microvascular complications. Macrophages play an essential role in regulating local immune responses, tissue homeostasis, and disease pathogenesis. Here, we have analyzed transforming growth factor beta 1 (TGFβ1)/Smad signaling in primary human macrophages grown in normal (NG) and high-glucose (HG; +25 mM glucose) conditions. Cell culture lactate concentration and cellular phosphofructokinase (PFK) activity were increased in HG concentrations. High glucose levels in the growth media led to increased macrophage mRNA expression of TGFβ1, and TGFβ-regulated HAMP and PLAUR mRNA levels, while the expression of TGFβ receptor II remained unchanged. Stimulation of cells with TGFβ1 protein lead to Smad2 phosphorylation in both NG and HG conditions, while the phosphorylation of Smad1/5 was detected only in response to TGFβ1 stimulation in HG conditions. The use of the specific Alk1/2 inhibitor dorsomorphin and the Alk5 inhibitor SB431542, respectively, revealed that HG conditions led TGFβ1 to activation of Smad1/5 signaling and its downstream target genes. Thus, high-glucose activates TGFβ1 signaling to the Smad1/5 pathway in primary human macrophages, which may contribute to cellular homeostasis in a harmful manner, priming the tissues for diabetic complications.

Integrative analysis of Anoikis-related genes reveals that FASN is a novel prognostic biomarker and promotes the malignancy of bladder cancer via Wnt/β-catenin pathway

Bladder cancer (BC) exhibits diversity in clinical outcomes and is characterized by heterogeneity. Anoikis, a form of programmed cell death, plays a crucial role in facilitating tumor invasion and metastasis. This study comprehensively investigated the genetic landscape of BC progression, identifying 300 differentially expressed Anoikis-related genes (DE-ARGs) through in-depth analysis of the GSE13507 datasets. Functional enrichment analysis revealed associations with diverse diseases and biological processes. Employing machine learning algorithms, a logistic regression model based on nine marker genes demonstrated superior accuracy in distinguishing BC from normal samples. Validation in TCGA datasets highlighted the prognostic significance of LRP1, FASN, and SIRT6, suggesting their potential as cancer biomarkers. Particularly, FASN emerged as an independent prognostic indicator, regulating BC cell proliferation and metastasis through the Wnt/β-catenin pathway. The study provides crucial insights into altered genetic landscapes and potential therapeutic strategies for BC, emphasizing the significance of FASN in BC prognosis and progression.

Identifying the Pattern Characteristics of Anoikis-Related Genes in Keloid

Objective: Anoikis is a kind of programmed cell death that is triggered when cells lose contact with each other or with the matrix. However, the potential value of anoikis-related genes (ARGs) in keloid (KD) has not been investigated. Approach: We downloaded three keloid fibroblast (KF) RNA sequencing (RNA-seq) datasets from the Gene Expression Omnibus (GEO) and obtained 338 ARGs from a search of the GeneCards database and PubMed articles. Weighted correlation network analysis was used to construct the coexpression network and obtain the KF-related ARGs. The LASSO-Cox method was used to screen the hub ARGs and construct the best prediction model. Then, GEO single-cell sequencing datasets were used to verify the expression of hub genes. We used whole RNA-seq for gene-level validation and the correlation between KD immune infiltration and anoikis. Results: Our study comprehensively analyzed the role of ARGs in KD for the first time. The least absolute shrinkage and selection operator (LASSO) regression analysis identified six hub ARGs (HIF1A, SEMA7A, SESN1, CASP3, LAMA3, and SIK2). A large number of miRNAs participate in the regulation of hub ARGs. In addition, correlation analysis revealed that ARGs were significantly correlated with the infiltration levels of multiple immune cells in patients with KD. Innovation: We explored the expression characteristics of ARGs in KD, which is extremely important for determining the molecular pathways and mechanisms underlying KD. Conclusions: This study provides a useful reference for revealing the characteristics of ARGs in the pathogenesis of KD. The identified hub genes may provide potential therapeutic targets for patients. This study provides new ideas for individualized therapy and immunotherapy.

Lopinavir enhances anoikis by remodeling autophagy in a circRNA-dependent manner

Macroautophagy/autophagy-mediated anoikis resistance is crucial for tumor metastasis. As a key autophagy-related protein, ATG4B has been demonstrated to be a prospective anti-tumor target. However, the existing ATG4B inhibitors are still far from clinical application, especially for tumor metastasis. In this study, we identified a novel circRNA, circSPECC1, that interacted with ATG4B. CircSPECC1 facilitated liquid-liquid phase separation of ATG4B, which boosted the ubiquitination and degradation of ATG4B in gastric cancer (GC) cells. Thus, pharmacological addition of circSPECC1 may serve as an innovative approach to suppress autophagy by targeting ATG4B. Specifically, the circSPECC1 underwent significant m6A modification in GC cells and was subsequently recognized and suppressed by the m6A reader protein ELAVL1/HuR. The activation of the ELAVL1-circSPECC1-ATG4B pathway was demonstrated to mediate anoikis resistance in GC cells. Moreover, we also verified that the above pathway was closely related to metastasis in tissues from GC patients. Furthermore, we determined that the FDA-approved compound lopinavir efficiently enhanced anoikis and prevented metastasis by eliminating repression of ELAVL1 on circSPECC1. In summary, this study provides novel insights into ATG4B-mediated autophagy and introduces a viable clinical inhibitor of autophagy, which may be beneficial for the treatment of GC with metastasis.

Targeting anoikis resistance as a strategy for cancer therapy

Anoikis, known as matrix detachment-induced apoptosis or detachment-induced cell death, is crucial for tissue development and homeostasis. Cancer cells develop means to evade anoikis, e.g. anoikis resistance, thereby allowing for cells to survive under anchorage-independent conditions. Uncovering the mechanisms of anoikis resistance will provide details about cancer metastasis, and potential strategies against cancer cell dissemination and metastasis. Here, we summarize the principal elements and core molecular mechanisms of anoikis and anoikis resistance. We discuss the latest progress of how anoikis and anoikis resistance are regulated in cancers. Furthermore, we summarize emerging data on selective compounds and nanomedicines, explaining how inhibiting anoikis resistance can serve as a meaningful treatment modality against cancers. Finally, we discuss the key limitations of this therapeutic paradigm and possible strategies to overcome them. In this review, we suggest that pharmacological modulation of anoikis and anoikis resistance by bioactive compounds could surmount anoikis resistance, highlighting a promising therapeutic regimen that could be used to overcome anoikis resistance in cancers.

PLAUR facilitates the progression of clear cell renal cell carcinoma by activating the PI3K/AKT/mTOR signaling pathway

Background

PLAUR has been found upregulated in various tumors and closely correlated with the malignant phenotype of tumor cells. The aim of this study was to investigate the relationship between PLAUR and clear cell renal cell carcinoma (ccRCC) and its potential mechanism of promoting tumor progression.

Methods

The expression levels and clinical significance of PLAUR, along with the associated signaling pathways, were extensively investigated in ccRCC samples obtained from The Cancer Genome Atlas (TCGA). PLAUR expression in 20 pairs of ccRCC tumor tissues and the adjacent tissues was assessed using qRT-PCR and IHC staining. Additionally, a series of in vitro experiments were conducted to investigate the impact of PLAUR suppression on cellular proliferation, migration, invasion, cell cycle progression, and apoptosis in ccRCC. The Western blot analysis was employed to investigate the expression levels of pivotal genes associated with the PI3K/AKT/mTOR signaling pathway.

Results

The expression of PLAUR was significantly upregulated in ccRCC compared to normal renal tissues, and higher PLAUR expression in ccRCC was associated with a poorer prognosis than low expression. The in-vitro functional investigations demonstrated that knockdown of PLAUR significantly attenuated the proliferation, migration, and invasion capabilities of ccRCC cells. Concurrently, PLAUR knockdown effectively induced cellular apoptosis, modulated the cell cycle, inhibited the EMT process, and attenuated the activation of the PI3K/AKT/mTOR signaling pathway. PLAUR may represent a key mechanism underlying ccRCC progression.

Conclusions

The involvement of PLAUR in ccRCC progression may be achieved through the activation of the PI3K/AKT/mTOR signaling pathway, making it a reliable biomarker for the identification and prediction of ccRCC.

Integrated analysis of colorectal cancer metastasis identifies characteristics of tumor cell during metastasis

Background

Metastasis is the main cause of death in colorectal cancer (CRC). Metastasis is a sequential and dynamic process, but the development of tumor cells during this process is unclear. In this study, we aimed to reveal characteristics of tumor cell subset during CRC metastasis.

Methods

Single-cell RNA sequence CRC data of normal epithelium, non-metastatic primary tumor, metastatic primary tumor, and liver metastases from gene expression omnibus (GEO) dataset were analyzed to reveal characteristics of CRC metastasis. Primary tumor tissues of three non-metastatic CRC and three metastatic CRC patients from Union Hospital of Tongji Medical College (Wuhan, China) were used to verify the characteristics of CRC metastasis.

Results

We identified a metastasis-related cancer cell subset EP1, which was characterized with a high expression of KRT17, LAMC2, EMP1, and PLAC8. EP1 had an enhanced cell-cell interaction, which interacted with SPP+ macrophages and drove them toward anti-inflammatory and immunosuppressive phenotype. Dynamic changes in genes and TF regulons during the metastasis were also revealed.

Conclusions

This study advanced our understanding of the development of tumor cells during CRC metastasis and further identified metastasis-related subset and potential therapeutic targets for the treatment and prevention of CRC metastasis.

A novel anoikis-related signature predicts prognosis risk and treatment responsiveness in diffuse large B-cell lymphoma

BACKGROUND

Although anoikis plays a role in cancer metastasis and aggressiveness, it has rarely been reported in diffuse large B cell lymphoma (DLBCL).

METHODS

We obtained RNA sequencing data and matched clinical data from the GEO database. An anoikis-related genes (ARGs)-based risk signature was developed in GSE10846 training cohort and validated in three other cohorts. Additionally, we predicted half-maximal inhibitory concentration (IC50) of drugs based on bioinformatics method and obtained the actual IC50 to some chemotherapy drugs via cytotoxicity assay.

RESULTS

The high-risk group, as determined by our signature, was associated with worse prognosis and an immunosuppressive environment in DLBCL. Meanwhile, the nomogram based on eight variables had more accurate ability in forecasting the prognosis than the international prognostic index in DLBCL. The prediction of IC50 indicated that DLBCL patients in the high-risk group were more sensitive to doxorubicin, IPA-3, lenalidomide, gemcitabine, and CEP.701, while patients in the low-risk group were sensitive to cisplatin and dasatinib. Consistent with the prediction, cytotoxicity assay suggested the higher sensitivity to doxorubicin and gemcitabine and the lower sensitivity to dasatinib in the high-risk group in DLBCL.

CONCLUSION

The ARG-based signature may provide a promising direction for prognosis prediction and treatment optimization for DLBCL patients.

Clinical value of molecular subtypes identification based on anoikis-related lncRNAs in castration-resistant prostate cancer

BACKGROUND

Anoikis is a distinctive type of apoptosis. It is involved in tumor progression and metastasis. But its function in castration-resistant prostate cancer (CRPC) remains veiled. We aimed to develop a prognostic indicator based on anoikis-related long non-coding RNAs (arlncRNAs) and to investigate their biological function in CRPC.

MATERIAL AND METHOD

Differentially expressed anoikis-related genes were extracted from two CRPC datasets, GSE51873, and GSE78201. Four lncRNAs associated with the anoikis-related genes were selected. A risk model based on these lncRNAs was developed and validated in The Cancer Genome Atlas (TCGA) and the Memorial Sloan-Kettering Cancer Center (MSKCC) prostate cancer cohorts. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, immune infiltration, immune checkpoints expression, and drug susceptibility were performed based on the model. To identify the biofunction of anoikis-related lncRNA, CCK-8 assays, colony formation assays, and flow cytometry were used.

RESULT

Twenty-nine anoikis-related genes were differentially expressed in the CRPC datasets. And 36 prognostic arlncRNAs were selected for the LASSO Cox analysis. Patients were subsequently classified into two subtypes by constructing an anoikis-related lncRNA based prognostic index (ARPI). The accuracy of this index was validated. KEGG enrichment analysis revealed that the high-ARPI group was enriched in cancer-related and immune-related pathways. Immune infiltration analysis has indicated a positive association between high-ARPI groups and increased immune infiltration. Fulvestrant, OSI-027, Lapatinib, Dabrafenib, and Palbociclib were identified as potential sensitive drugs for high-ARPI patients. In vitro experiments exhibited that silencing LINC01138 dampened the proliferation, migration and enzalutamide resistance in CRPC. Furthermore, it stimulated apoptosis and inhibited the eithelial-mesenchymal transition process.

CONCLUSION

Four arlncRNAs were identified and a risk model was established to predict the prognosis of patients with prostate cancer. Immune infiltration and drug susceptibility analysis revealed a potential therapeutic strategy for patients with castration-resistant prostate cancer.

Identification of the molecular subtypes and signatures to predict the prognosis, biological functions, and therapeutic response based on the anoikis-related genes in colorectal cancer

BACKGROUND

Tumors that resist anoikis, a programmed cell death triggered by detachment from the extracellular matrix, promote metastasis; however, the role of anoikis-related genes (ARGs) in colorectal cancer (CRC) stratification, prognosis, and biological functions remains unclear.

METHODS

We obtained transcriptomic profiles of CRC and 27 ARGs from The Cancer Genome Atlas, the Gene Expression Omnibus, and MSigDB databases, respectively. CRC tissue samples were classified into two clusters based on the expression pattern of ARGs, and their functional differences were explored. Hub genes were screened using weighted gene co-expression network analysis, univariate analysis, and least absolute selection and shrinkage operator analysis, and validated in cell lines, tissues, or the Human Protein Atlas database. We constructed an ARG-risk model and nomogram to predict prognosis in patients with CRC, which was validated using an external cohort. Multifaceted landscapes, including stemness, tumor microenvironment (TME), immune landscape, and drug sensitivity, between high- and low-risk groups were examined.

RESULTS

Patients with CRC were divided into C1 and C2 clusters. Cluster C1 exhibited higher TME scores, whereas cluster C2 had favorable outcomes and a higher stemness index. Eight upregulated hub ARGs (TIMP1, P3H1, SPP1, HAMP, IFI30, ADAM8, ITGAX, and APOC1) were utilized to construct the risk model. The qRT-PCR, Western blotting, and immunohistochemistry results were consistent with those of the bioinformatics analysis. Patients with high risk exhibited worse overall survival (p < 0.01), increased stemness, TME, immune checkpoint expression, immune infiltration, tumor mutation burden, and drug susceptibility compared with the patients with low risk.

CONCLUSION

Our results offer a novel CRC stratification based on ARGs and a risk-scoring system that could predict the prognosis, stemness, TME, immunophenotypes, and drug susceptibility of patients with CRC, thereby improving their prognosis. This stratification may facilitate personalized therapies.

Anoikis-related genes as potential prognostic biomarkers in gastric cancer: A multilevel integrative analysis and predictive therapeutic value

BACKGROUND

Gastric cancer (GC) is a frequent malignancy of the gastrointestinal tract. Exploring the potential anoikis mechanisms and pathways might facilitate GC research.

PURPOSE

The authors aim to determine the significance of anoikis-related genes (ARGs) in GC prognosis and explore the regulatory mechanisms in epigenetics.

METHODS

After describing the genetic and transcriptional alterations of ARGs, we searched differentially expressed genes (DEGs) from the cancer genome atlas and gene expression omnibus databases to identify major cancer marker pathways. The non-negative matrix factorisation algorithm, Lasso, and Cox regression analysis were used to construct a risk model, and we validated and assessed the nomogram. Based on multiple levels and online platforms, this research evaluated the regulatory relationship of ARGs with GC.

RESULTS

Overexpression of ARGs is associated with poor prognosis, which modulates immune signalling and promotes anti-anoikis. The consistency of the DEGs clustering with weighted gene co-expression network analysis results and the nomogram containing 10 variable genes improved the clinical applicability of ARGs. In anti-anoikis mode, cytology, histology, and epigenetics could facilitate the analysis of immunophenotypes, tumour immune microenvironment (TIME), and treatment prognosis.

CONCLUSION

A novel anoikis-related prognostic model for GC is constructed, and the significance of anoikis-related prognostic genes in the TIME and the metabolic pathways of tumours is initially explored.

Ubiquitin specific peptidase 38 epigenetically regulates KLF transcription factor 5 to augment malignant progression of lung adenocarcinoma

Protein ubiquitination is a common post-translational modification and a critical mechanism for regulating protein stability. This study aimed to explore the role and potential molecular mechanism of ubiquitin-specific peptidase 38 (USP38) in the progression of lung adenocarcinoma (LUAD). USP38 expression was significantly higher in patients with LUAD than in their counterparts, and higher USP38 expression was closely associated with a worse prognosis. USP38 silencing suppresses the proliferation of LUAD cells in vitro and impedes the tumorigenic activity of cells in xenograft mouse models in vivo. Further, we found that USP38 affected the protein stability of transcription factor Krüppel-like factors 5 (KLF5) by inhibiting its degradation. Subsequent mechanistic investigations showed that the N-terminal of USP38 (residues 1-400aa) interacted with residues 1-200aa of KLF5, thereby stabilizing the KLF5 protein by deubiquitination. Moreover, we found that PIAS1-mediated SUMOylation of USP38 was promoted, whereas SENP2-mediated de-SUMOylation of USP38 suppressed the deubiquitination effects of USP38 on KLF5. Additionally, our results demonstrated that KLF5 overexpression restored the suppression of the malignant properties of LUAD cells by USP38 knockdown. SUMOylation of USP38 enhances the deubiquitination and stability of KLF5, thereby augmenting the malignant progression of LUAD.

Transcriptome and single-cell transcriptomics reveal prognostic value and potential mechanism of anoikis in skin cutaneous melanoma

BACKGROUND

Skin cutaneous melanoma (SKCM) is a highly lethal cancer, ranking among the top four deadliest cancers. This underscores the urgent need for novel biomarkers for SKCM diagnosis and prognosis. Anoikis plays a vital role in cancer growth and metastasis, and this study aims to investigate its prognostic value and mechanism of action in SKCM.

METHODS

Utilizing consensus clustering, the SKCM samples were categorized into two distinct clusters A and B based on anoikis-related genes (ANRGs), with the B group exhibiting lower disease-specific survival (DSS). Gene set enrichment between distinct clusters was examined using Gene Set Variation Analysis (GSVA) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis.

RESULTS

We created a predictive model based on three anoikis-related differently expressed genes (DEGs), specifically, FASLG, IGF1, and PIK3R2. Moreover, the mechanism of these prognostic genes within the model was investigated at the cellular level using the single-cell sequencing dataset GSE115978. This analysis revealed that the FASLG gene was highly expressed on cluster 1 of Exhausted CD8( +) T (Tex) cells.

CONCLUSIONS

In conclusion, we have established a novel classification system for SKCM based on anoikis, which carries substantial clinical implications for SKCM patients. Notably, the elevated expression of the FASLG gene on cluster 1 of Tex cells could significantly impact SKCM prognosis through anoikis, thus offering a promising target for the development of immunotherapy for SKCM.

Metastatic outgrowth via the two-way interplay of autophagy and metabolism

Metastasis represents one of the most dangerous issue of cancer progression, characterized by intricate interactions between invading tumor cells, various proteins, and other cells on the way towards target sites. Tumor cells, while undergoing metastasis, engage in dynamic dialogues with stromal cells and undertake epithelial-mesenchymal transition (EMT) phenoconversion. To ensure survival, tumor cells employ several strategies such as restructuring their metabolic needs to adapt to the alterations of the microenvironmental resources via different mechanisms including macroautophagy (autophagy) and to circumvent anoikis-a form of cell death induced upon detachment from the extracellular matrix (ECM). This review focuses on the puzzling connections of autophagy and energetic metabolism within the context of cancer metastasis.

Immune-related long noncoding RNA zinc finger protein 710-AS1-201 promotes the metastasis and invasion of gastric cancer cells

BACKGROUND

Gastric cancer (GC) is a prevalent malignant tumor of the gastrointestinal system. ZNF710 is a transcription factor (TF), and zinc finger protein 710 (ZNF710)-AS1-201 is an immune-related long noncoding RNA (lncRNA) that is upregulated in GC cells.

AIM

To assess the correlation between ZNF710-AS1-201 and immune microenvironment features and to investigate the roles of ZNF710-AS1-201 in the invasion and metastasis processes of GC cells.

METHODS

We obtained data from The Cancer Genome Atlas and Wujin Hospital. We assessed cell growth, migration, invasion, and programmed cell death using cell counting kit-8, EdU, scratch, Transwell, and flow cytometry assays. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to identify the potential downstream targets of ZNF710-AS1-201.

RESULTS

In GC tissues with low ZNF710-AS1-201 expression, immunoassays detected significant infiltration of various antitumor immune cells, such as memory CD8 T cells and activated CD4 T cells. In the low-expression group, the half-maximal inhibitory concentrations (IC50s) of 5-fluorouracil, cisplatin, gemcitabine, and trametinib were lower, whereas the IC50s of dasatinib and vorinostat were higher. The malignant degree of GC was higher and the stage was later in the high-expression group. Additionally, patients with high expression of ZNF710-AS1-201 had lower overall survival and disease-free survival rates. In vitro, the overexpression of ZNF710-AS1-201 greatly enhanced growth, metastasis, and infiltration while suppressing cell death in HGC-27 cells. In contrast, the reduced expression of ZNF710-AS1-201 greatly hindered cell growth, enhanced apoptosis, and suppressed the metastasis and invasion of MKN-45 cells. The expression changes in ZNF710 were significant, but the corresponding changes in isocitrate dehydrogenase-2, Semaphorin 4B, ARHGAP10, RGMB, hsa-miR-93-5p, and ZNF710-AS1-202 were not consistent or statistically significant after overexpression or knockdown of ZNF710-AS1-201, as determined by qRT-PCR.

CONCLUSION

Immune-related lncRNA ZNF710-AS1-201 facilitates the metastasis and invasion of GC cells. It appears that ZNF710-AS1-201 and ZNF710 have potential as effective targets for therapeutic intervention in GC. Nevertheless, it is still necessary to determine the specific targets of the ZNF710 TF.

Prognostic value and immune landscapes of anoikis-associated lncRNAs in lung adenocarcinoma

BACKGROUND

Methods for predicting the outcome of lung adenocarcinoma (LUAD) in the clinic are limited. Anoikis is an important route to programmed cell death in LUAD, and the prognostic value of a model constructed with anoikis-related lncRNAs (ARlncRNAs) in LUAD is unclear.

METHODS

Transcriptome and basic information for LUAD patients was obtained from the Cancer Genome Atlas. Coexpression and Cox regression analyses were utilized to identify prognostically significant ARlncRNAs and construct a prognostic signature. Furthermore, the signature was combined with clinical characteristics to create a nomogram. Finally, we performed principal component, enrichment, tumor mutation burden (TMB), tumor microenvironment (TME) and drug sensitivity analyses to evaluate the basic research and clinical merit of the signature.

RESULTS

The prognostic signature developed with eleven ARlncRNAs can accurately predict that high-risk group patients have a worse prognosis, as proven by the receiver operating characteristic (ROC) curve (AUC: 0.718). Independent prognostic analyses indicated that the risk score is a significant independent prognostic element for LUAD (P<0.001). In the high-risk group, enrichment analysis demonstrated that glucose metabolism and DNA replication were the main enrichment pathways. TMB analysis indicated that the high-risk group had a high TMB (P<0.05). Drug sensitivity analyses can recognize drugs that are sensitive to different risk groups. Finally, 11 ARlncRNAs of this signature were verified by RT-qPCR analysis.

CONCLUSIONS

A novel prognostic signature developed with 11 ARlncRNAs can accurately predict the OS of LUAD patients and offer clinical guidance value for immunotherapy and chemotherapy treatment.

ITGBL1 promotes anoikis resistance and metastasis in human gastric cancer via the AKT/FBLN2 axis

The resistance to anoikis plays a critical role in the metastatic progression of various types of malignancies, including gastric cancer (GC). Nevertheless, the precise mechanism behind anoikis resistance is not fully understood. Here, our primary focus was to examine the function and underlying molecular mechanism of Integrin beta-like 1 (ITGBL1) in the modulation of anoikis resistance and metastasis in GC. The findings of our investigation have demonstrated that the overexpression of ITGBL1 significantly augmented the resistance of GC cells to anoikis and promoted their metastatic potential, while knockdown of ITGBL1 had a suppressive effect on both cellular processes in vitro and in vivo. Mechanistically, we proved that ITGBL1 has a role in enhancing the resistance of GC cells to anoikis and promoting metastasis through the AKT/Fibulin-2 (FBLN2) axis. The inhibition of AKT/FBLN2 signalling was able to reverse the impact of ITGBL1 on the resistance of GC cells to anoikis and their metastatic capability. Moreover, the expression levels of ITGBL1 were found to be significantly elevated in the cancerous tissues of patients diagnosed with GC, and there was a strong correlation observed between high expression levels of ITGBL1 and worse prognosis among individuals diagnosed with GC. Significantly, it was revealed that within our cohort of GC patients, individuals exhibiting elevated ITGBL1 expression and diminished FBLN2 expression experienced the worst prognosis. In conclusion, the findings of our study indicate that ITGBL1 may serve as a possible modulator of resistance to anoikis and the metastatic process in GC.

Extracellular vesicles from Fusobacterium nucleatum: roles in the malignant phenotypes of gastric cancer

The increase of the Fusobacterium nucleatum level has been previously identified in various cancers including gastric cancer (GC), but how the F. nucleatum exerts its carcinogenic role in GC remains unclear. Several studies revealed that F. nucleatum contributes to cancer progression via its secretion of extracellular vehicles (EVs). Hence, it's designed to reveal the influence of F. nucleatum-derived EVs (Fn-EVs) in GC progression. The tumor and adjacent tissues were collected from 30 GC patients, and the abundance of F. nucleatum was found to be highly expressed in tumor samples. The ultracentrifugation was employed to isolate EVs from F. nucleatum and Escherischia coli (E. coli), which were labeled Fn-EVs and E. coli-EVs, respectively. After treating GC cells with Fn-EVs and E. coli-EVs, cell counting kit 8, colony formation, wound healing as well as transwell assay were performed, which revealed that Fn-EVs effectively enhanced oxaliplatin resistance, and facilitated cell proliferation, migration, invasion, and stemness in GC cells while E. coli-EVs exert no significant effect on GC cells. Besides, the stemness and DNA repair of GC cells were also enhanced by Fn-EVs, as revealed by the sphere-forming assay and the detection of stemness- and DNA repair-associated proteins by western blotting. In vivo analyses demonstrated that Fn-EVs administration not only promoted GC tumor growth and liver metastasis but also conferred GC tumor resistance to oxaliplatin resistance. This study first revealed the contributive role of F. nucleatum in GC development via Fn-EVs, which provided a better perspective for manipulating F. nucleatum in treating GC patients with malignant phenotypes.

Multiple databases analyzed the prognosis prediction of renin secretion pathway-related genes in renal clear cell carcinoma and immunotherapy

Background

Clear cell renal cell carcinoma (ccRCC) is a malignant kidney tumour and its progression is associated with the renin secretion pathway, so this study aimed to develop a prognostic model based on renin secretion pathway-related genes.

Methods

First, 453 renin secretion pathway-related genes were acquired [|log fold change (FC)| >1.5, false discovery rate (FDR) <0.05] from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The data were combined and further screened for 188 genes associated with ccRCC prognosis (P<0.05) by univariate independent prognostic analysis. These genes were subjected to least absolute shrinkage and selection operator regression to identify potential prognostic genes to construct the prognostic model. The stability of the model was externally validated. Combined risk scores and clinical information were used to create nomograms to accurately reflect patient survival. The model-related genes were further mined for subsequent analysis.

Results

A prognostic model of six renin secretion pathway genes (IGFBP3, PLAUR, CHKB-CPT1B, HOXA13, CDH13, and CDC20) was developed. Its reliability in predicting disease prognosis was confirmed by survival analysis, receiver operating characteristic (ROC) curve analysis and a risk curve. The nomogram and calibration curve showed good accuracy. The immune-related analyses revealed that the low-risk group would benefit more from immunotherapy.

Conclusions

The prognostic model of ccRCC based on six renin secretion pathway-related genes can be used to guide the precise treatment of ccRCC patients.

Development of adaptive anoikis resistance promotes metastasis that can be overcome by CDK8/19 Mediator kinase inhibition

Anoikis resistance or evasion of cell death triggered by cell detachment into suspension is a hallmark of cancer that is concurrent with cell survival and metastasis. The effects of frequent matrix detachment encounters on the development of anoikis resistance in cancer remains poorly defined. Here we show using a panel of ovarian cancer models, that repeated exposure to suspension stress in vitro followed by attached recovery growth leads to the development of anoikis resistance paralleling in vivo development of anoikis resistance in ovarian cancer ascites. This resistance is concurrent with enhanced invasion, chemoresistance and the ability of anoikis adapted cells to metastasize to distant sites. Adapted anoikis resistant cells show a heightened dependency on oxidative phosphorylation and can also evade immune surveillance. We find that such acquired anoikis resistance is not genetic, as acquired resistance persists for a finite duration in the absence of suspension stress. Transcriptional reprogramming is however essential to this process, as acquisition of adaptive anoikis resistance in vitro and in vivo is exquisitely sensitive to inhibition of CDK8/19 Mediator kinase, a pleiotropic regulator of transcriptional reprogramming. Our data demonstrate that growth after recovery from repeated exposure to suspension stress is a direct contributor to metastasis and that inhibition of CDK8/19 Mediator kinase during such adaptation provides a therapeutic opportunity to prevent both local and distant metastasis in cancer.

A Prediction Model for Deciphering Intratumoral Heterogeneity Derived from the Microglia/Macrophages of Glioma Using Non-Invasive Radiogenomics

Microglia and macrophages play a major role in glioma immune responses within the glioma microenvironment. We aimed to construct a prognostic prediction model for glioma based on microglia/macrophage-correlated genes. Additionally, we sought to develop a non-invasive radiogenomics approach for risk stratification evaluation. Microglia/macrophage-correlated genes were identified from four single-cell datasets. Hub genes were selected via lasso-Cox regression, and risk scores were calculated. The immunological characteristics of different risk stratifications were assessed, and radiomics models were constructed using corresponding MRI imaging to predict risk stratification. We identified eight hub genes and developed a relevant risk score formula. The risk score emerged as a significant prognostic predictor correlated with immune checkpoints, and a relevant nomogram was drawn. High-risk groups displayed an active microenvironment associated with microglia/macrophages. Furthermore, differences in somatic mutation rates, such as IDH1 missense variant and TP53 missense variant, were observed between high- and low-risk groups. Lastly, a radiogenomics model utilizing five features from magnetic resonance imaging (MRI) T2 fluid-attenuated inversion recovery (Flair) effectively predicted the risk groups under a random forest model. Our findings demonstrate that risk stratification based on microglia/macrophages can effectively predict prognosis and immune functions in glioma. Moreover, we have shown that risk stratification can be non-invasively predicted using an MRI-T2 Flair-based radiogenomics model.

WIPF1 promotes gastric cancer progression by regulating PI3K/Akt signaling in a myocardin-dependent manner

Wiskott-Aldrich syndrome protein-interacting protein family member 1 (WIPF1) is associated with malignant tumor progression. However, molecular links between WIPF1 and gastric cancer (GC) remain elusive. The expression of WIPF1 was detected in GC tissues and cells. WIPF1 was overexpressed in GC tissues and cells and high expression of WIPF1 was an independent risk factor for a poor prognosis in patients with GC. Further experiments indicated that WIPF1 promoted the proliferation, invasion, and migration of GC cells in vivo and in vitro. WIPF1-regulated genes were closely related to cell proliferation and migration in GC, and silencing WIPF1 significantly repressed PI3K/AKT signaling pathway activation. WIPF1 was activated by myocardin (MYOCD) translation. Rescue experiments confirmed that MYOCD promotes the proliferation, invasion, and migration of GC cells in a WIPF1-dependent manner and activates the PI3K/AKT signaling pathway. MYOCD may transactivate WIPF1 and facilitate GC cell growth and metastasis by activating the PI3K/AKT signaling pathway.

A novel risk model for predicting peritoneal metastasis in colorectal cancer based on the SEER database

BACKGROUND

Early detection and intervention could significantly improve the prognosis of patients with peritoneal metastasis (PM). Our main purpose was to develop a model to predict the risk of PM in patients with colorectal cancer (CRC).

METHODS

Patients from the Surveillance, Epidemiology, and End Results (SEER) database with CRC classified according to the AJCC 8th TNM staging system were selected for the study. After data pre-processing, the dataset was divided into a training set and a validation set. In the training set, univariate logistic analysis and stepwise multivariate logistic regression analysis were utilized to screen clinical features and construct a risk prediction model. Then, we validated the model using the confusion matrix, receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves to examine its performance.

RESULTS

The model constructed using stepwise multivariate logistic regression analysis incorporated the following eight clinical features: age, tumor location, histological type, T stage, carcinoembryonic antigen (CEA) level, tumor deposits (TDs), log odds (LODDS) of metastatic lymph nodes, and extraperitoneal metastasis (EM). The areas under the curve (AUCs) of the model in the training and validation sets were 0.924 and 0.912, respectively. The accuracy and the recall ratio were higher than 0.8 in both cohorts. DCA and the calibration curves also confirmed its excellent predictive power.

CONCLUSIONS

Our model can effectively predict the risk of PM in CRC patients, which is of great significance for the timely identification of patients at high risk of PM and further clinical decision-making.

STAT1 suppresses the transcriptional activity of TRIM21 in gastric cancer

PURPOSE

Tripartite motif-containing protein 21 (TRIM21) has E3 ubiquitin ligase activity and is involved in the regulation of various biological processes in vivo. TRIM21 has been found to have strong associations with various cancers. However, its role in gastric cancer is unclear.

METHODS

The TCGA database was screened to obtain TRIM21 using WGCNA and PPI analyses. The TCGA database was used to evaluate the correlation of TRIM21 expression with patients' clinical characteristics, prognosis, functional enrichment and immune cell infiltration. The role of TRIM21 in cell proliferation, apoptosis and invasion was verified by in vivo and in vitro assays. The UCSC and JASPAR databases were used to evaluate the regulatory role of STAT1 on TRIM21 transcription. Finally, dual-luciferase reporter assay was used to confirm the regulation of TRIM21 transcriptional activity by STAT1.

RESULTS

As a key gene, high expression of TRIM21 inhibited the gastric cancer growth and was significantly enriched in apoptosis, cell proliferation, and JAK/STAT signaling pathways. TRIM21 expression was positively correlated with a variety of TICs, including T cells, NK cells, and DCs. In vivo assays, TRIM21 inhibited functions in gastric cancer cell lines, including inhibition of proliferation and migration, and promotion of apoptosis. Database analysis and dual-luciferase reporter assay showed that STAT1 inhibited the transcriptional activity of TRIM21. In vivo assays confirmed that TRIM21 inhibited tumor growth, and STAT1 expression was negatively correlated with STAT1.

CONCLUSION

TRIM21 is a tumor-suppressive gene in gastric cancer, and its transcriptional activity is inhibited by STAT1.

Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients

Gastric cancer (GC) has been a common tumor type with high mortality. Distal metastasis is one of the main causes of death in GC patients, which is also related to poor prognosis. The mRNA profiles and clinical information of GC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Univariate Cox and LASSO Cox analyses were used to screen the optimal metastasis-related genes (MRGs) to establish a prognostic Risk Score model for GC patients. The nomogram was used to visualize the Risk Score and predict the 1-, 3-, 5-year survival rate. The immune cell infiltration was analyzed by CIBERSORT and the ratio of immune-stromal component was calculated by the ESTIMATE algorithm. A total of 142 differentially expressed genes were identified between metastatic and non-metastatic GC samples. The optimal 8 genes, comprising GAMT (guanidinoacetate N-methyltransferase), ABCB5 (ATP-binding cassette subfamily B member 5), ITIH3 (inter-alpha-trypsin inhibitor heavy chain 3), GDF3 (growth differentiation factor 3), VSTM2L (V-set and transmembrane domain-containing 2 like), CIDEA (cell death inducing DFFA like effector a), NPTX1 (neuronal pentraxin-1), and UMOD (uromodulin), were further screened to establish a prognostic Risk Score, which proved to be an independent prognostic factor. Patients in high-risk group had a poor prognosis. There were significant differences in the proportion of 11 tumor-infiltrating immune cells between high-risk and low-risk subgroups. In addition, the StromalScore, ImmuneScore, and ESTIMATEScore in high-risk group were higher than those in low-risk group, indicating that the tumor microenvironment of the high-risk group was more complex. A Risk Score model based on eight metastasis-related genes could clearly distinguish the prognosis of GC patients. The poor prognosis of patients with high-Risk Score might be associated with the complex tumor microenvironments.

A novel anoikis-related gene signature predicts prognosis in patients with breast cancer and reveals immune infiltration

Breast cancer (BRCA) is a common malignancy worldwide that is associated with a high mortality rate. Despite recent improvements in diagnosis and treatment, there is an urgent need to investigate the processes underlying cancer progression and identify novel prognostic indicators. Anoikis, which plays a role in the development of human malignant tumors, has been gaining increasing interest from researchers. However, the potential role of anoikis-related genes (ANRGs) in the advancement of BRCA remains unknown. In this study, we aimed to assess the predictive value of ANRGs in BRCA, construct a prognostic model based on ANRGs, and explore the tumor microenvironment in different prognostic score groups. This study utilized data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to collect clinical information and RNA sequencing data from patients with BRCA. Information on ANRGs was gathered from GeneCards and Harmonizome portals. A risk score model based on ANRGs was created using least absolute shrinkage and selection operator Cox (LASSO) regression analysis. Additionally, the study explored the tumor microenvironment and enriched pathways in different risk groups. Finally, a novel ANRG-based nomogram is developed. A total of 142 differentially expressed genes associated with survival were identified, of which 5 genes were selected to create the ANRG signature. The risk score based on this signature proved to be an independent prognostic factor. Further analysis revealed that different risk subgroups exhibited variations in the tumor microenvironment and drug sensitivities. Subsequently, a nomogram was developed using risk scores and clinicopathological factors. The decision curve analysis results suggest that patients with BRCA might derive clinical treatment benefits from utilizing this prognostic model. Based on the results of this study, the ANRG signature and nomograph established can be used for clinical decision-making in patients with BRCA.

Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma

Background

Despite numerous treatments available, clear cell renal cell carcinoma (ccRCC) remains a deadly and invasive cancer. Anoikis-related genes (ARGs) are essential regulators of tumor metastasis and development. However, the potential roles of ARGs in ccRCC remain unclear.

Methods

Based on the TCGA-KIRC cohort and GeneCards database, we identified differentially expressed ARGs in ccRCC. Then a 4 ARGs risk model was created by Cox regression and LASSO. The Kaplan-Meier and receiver operating characteristic (ROC) curves were utilized to verify the predictive efficacy of the prognostic signature. Subsequently, the possible molecular mechanism of ARGs was investigated by functional enrichment analysis. To assess the immune infiltration, immune checkpoint genes, and immune function in various risk groups, single sample gene set enrichment (ssGSEA) algorithm was employed. Furthermore, the low-risk and high-risk groups were compared in terms of tumor mutation burden (TMB). Ultimately, we analyzed the protein expression of these four ARGs utilizing the western blot test.

Results

Four genes were utilized to create a risk signature that may predict prognosis, enabling the classification of KIRC patients into groups with low or high risk. The reliability of the signature was examined utilizing survival analysis and ROC analysis. According to the multivariate Cox regression result, the risk score was a reliable independent prognostic predictor for KIRC patients. The novel risk model could differentiate between KIRC patients with various clinical outcomes and represent KIRC's specific immune status. An analysis of the correlation of TMB and risk score indicated a positive correlation between them, with high TMB being potentially linked to worse outcomes.

Conclusion

Based on our findings, the prognostic signature of ARGs may be employed as an independent prognostic factor for ccRCC patients. It may introduce alternative perspectives on prognosis evaluation and serve as a prominent reference for personalized and precise therapy in KIRC.

Construction and validation of a novel prognostic model of neutrophil‑related genes signature of lung adenocarcinoma

Lung adenocarcinoma (LUAD) remains an incurable disease with a poor prognosis. This study aimed to explore neutrophil‑related genes (NRGs) and develop a prognostic signature for predicting the prognosis of LUAD. NRGs were obtained by intersecting modular genes identified by weighted gene co-expression network analysis (WGCNA) using bulk RNA-seq data and the marker genes of neutrophils identified from single-cell RNA-sequencing(scRNA-seq) data. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analyses were run to construct a prognostic signature, follow by delineation of risk groups, and external validation. Analyses of ESTIMAT, immune function, Tumor Immune Dysfunction and Exclusion (TIDE) scores, Immune cell Proportion Score (IPS), and immune checkpoint genes between high- and low-risk groups were performed, and then analyses of drug sensitivity to screen for sensitive anticancer drugs in high-risk groups. A total of 45 candidate NRGs were identified, of which PLTP, EREG, CD68, CD69, PLAUR, and CYP27A1 were considered to be significantly associated with prognosis in LUAD and were used to construct a prognostic signature. Correlation analysis showed significant differences in the immune landscape between high- and low-risk groups. In addition, our prognostic signature was important for predicting drug sensitivity in the high-risk group. Our study screened for NRGs in LUAD and constructed a novel and effective signature, revealing the immune landscape and providing more appropriate guidance protocols in LUAD treatment.

YY1 regulates the proliferation and invasion of triple-negative breast cancer via activating PLAUR

It is well-established that breast cancer is a highly prevalent malignancy among women, emphasizing the need to investigate mechanisms underlying its pathogenesis and metastasis. In this study, the Gene Expression Omnibus (GEO) database was utilized to conduct differential expression analysis in breast cancer and adjacent tissues. Upregulated genes were selected for prognostic analysis of breast cancer. The expression of urokinase plasminogen activator receptor (uPAR), also known as PLAUR, was assessed using RT-qPCR and western blot. Immunofluorescence staining was employed to determine PLAUR localization. Various cellular processes were analyzed, including proliferation, migration, invasion, apoptosis, and cell cycle. Bioinformatics analysis was used to predict transcription factors of PLAUR, which were subsequently validated in a double luciferase reporter gene experiment. Rescue experiments confirmed the impact of PLAUR on the proliferation, apoptosis, and migration of MDA-MB-231 cells. Furthermore, the effects of PLAUR were evaluated in an orthotopic tumor transplantation and lung metastasis nude mouse model. Our findings substantiated the critical involvement of PLAUR in the progression of triple-negative breast cancer (TNBC) in vitro and among TNBC patients with a poor prognosis. Additionally, we demonstrated Yin Yang-1 (YY1) as a notable transcriptional regulator of PLAUR, whose activation could transcriptionally enhance the proliferation and invasion capabilities of TNBC cells. We also identified the downstream mechanism of PLAUR associated with PLAU, focal adhesion kinase (FAK), and AKT. Overall, these findings offer a novel perspective on PLAUR as a potential therapeutic target for TNBC.

A novel stratification framework based on anoikis-related genes for predicting the prognosis in patients with osteosarcoma

Background

Anoikis resistance is a prerequisite for the successful development of osteosarcoma (OS) metastases, whether the expression of anoikis-related genes (ARGs) correlates with OS prognosis remains unclear. This study aimed to investigate the feasibility of using ARGs as prognostic tools for the risk stratification of OS.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provided transcriptome information relevant to OS. The GeneCards database was used to identify ARGs. Differentially expressed ARGs (DEARGs) were identified by overlapping ARGs with common differentially expressed genes (DEGs) between OS and normal samples from the GSE16088, GSE19276, and GSE99671 datasets. Anoikis-related clusters of patients were obtained by consistent clustering, and gene set variation analysis (GSVA) of the different clusters was completed. Next, a risk model was created using Cox regression analyses. Risk scores and clinical features were assessed for independent prognostic values, and a nomogram model was constructed. Subsequently, a functional enrichment analysis of the high- and low-risk groups was performed. In addition, the immunological characteristics of OS samples were compared between the high- and low-risk groups, and their sensitivity to therapeutic agents was explored.

Results

Seven DEARGs between OS and normal samples were obtained by intersecting 501 ARGs with 68 common DEGs. BNIP3 and CXCL12 were significantly differentially expressed between both clusters (P<0.05) and were identified as prognosis-related genes. The risk model showed that the risk score and tumor metastasis were independent prognostic factors of patients with OS. A nomogram combining risk score and tumor metastasis effectively predicted the prognosis. In addition, patients in the high-risk group had low immune scores and high tumor purity. The levels of immune cell infiltration, expression of human leukocyte antigen (HLA) genes, immune response gene sets, and immune checkpoints were lower in the high-risk group than those in the low-risk group. The low-risk group was sensitive to the immune checkpoint PD-1 inhibitor, and the high-risk group exhibited lower inhibitory concentration values by 50% for 24 drugs, including AG.014699, AMG.706, and AZD6482.

Conclusion

The prognostic stratification framework of patients with OS based on ARGs, such as BNIP3 and CXCL12, may lead to more efficient clinical management.