Solute carrier transporter superfamily member SLC16A1 is a potential prognostic biomarker and associated with immune infiltration in skin cutaneous melanoma

SLC7A11 in hepatocellular carcinoma: potential mechanisms, regulation, and clinical significance

Exploring novel early detection biomarkers and developing more efficacious treatments remain pressing tasks in the current research landscape for hepatocellular carcinoma (HCC). Morphologically and molecularly separate from apoptosis, cell death, and autophagy, ferroptosis is a recently discovered, unique, controlled form of cell death. SLC7A11 (also known as xCT) represents a subunit of the cystine-glutamate antiporter (also known as system Xc(-)). A growing body of research suggests that induction of ferroptosis through SLC7A11 can effectively eliminate hepatocellular carcinoma (HCC) cells, particularly those exhibiting resistance to alternative forms of cell death. Thus, targeting ferroptosis via SLC7A11 may become a new direction for the design of therapeutic strategies for HCC. Although many research articles have investigated the possible roles of SLC7A11 in HCC, a study that summarizes the main findings, including the regulators and mechanisms of action of SLC7A11 in HCC is not available. Therefore, we present a comprehensive overview of the functions of ferroptosis, particularly SLC7A11, in the identification, development, and management of HCC in this review. In addition, we discuss how this knowledge can be translated into treatment by providing a systemic therapy in advanced HCC using sorafenib, the first-line drug targeting multiple kinases and SLC7A11. We further dissect the possible barriers as well as the corresponding solutions and provide insights on how to navigate effective treatment using this knowledge.

Quantifying the impact of immunotherapy on RNA dynamics in cancer

BACKGROUND

Checkpoint inhibitor (CPI) immunotherapies have provided durable clinical responses across a range of solid tumor types for some patients with cancer. Nonetheless, response rates to CPI vary greatly between cancer types. Resolving intratumor transcriptomic changes induced by CPI may improve our understanding of the mechanisms of sensitivity and resistance.

METHODS

We assembled a cohort of longitudinal pre-therapy and on-therapy samples from 174 patients treated with CPI across six cancer types by leveraging transcriptomic sequencing data from five studies.

RESULTS

Meta-analyses of published RNA markers revealed an on-therapy pattern of immune reinvigoration in patients with breast cancer, which was not discernible pre-therapy, providing biological insight into the impact of CPI on the breast cancer immune microenvironment. We identified 98 breast cancer-specific correlates of CPI response, including 13 genes which are known IO targets, such as toll-like receptors TLR1, TLR4, and TLR8, that could hold potential as combination targets for patients with breast cancer receiving CPI treatment. Furthermore, we demonstrate that a subset of response genes identified in breast cancer are already highly expressed pre-therapy in melanoma, and additionally we establish divergent RNA dynamics between breast cancer and melanoma following CPI treatment, which may suggest distinct immune microenvironments between the two cancer types.

CONCLUSIONS

Overall, delineating longitudinal RNA dynamics following CPI therapy sheds light on the mechanisms underlying diverging response trajectories, and identifies putative targets for combination therapy.

Identification of key biomarkers in ischemic stroke: single-cell sequencing and weighted co-expression network analysis

PURPOSE

At present, there is a lack of accurate early diagnostic markers for ischemic stroke.

METHODS

By using dimensionality reduction cluster analysis, differential expression analysis, weighted co-expression network analysis, protein-protein interaction network analysis, cell heterogeneity and key pathogenic genes were identified in ischemic stroke. Immunomicroenvironment analysis was used to explore the immune landscape and immune associations of key genes in ischemic stroke. The analysis platform we use is R software (version 4.0.5). PCR experiments were used to verify the expression of key genes.

RESULTS

Single cell sequencing data in ischemic stroke can be annotated as fibroblast cells, pre-B cell CD34, neutrophils cells, bone marrow (BM), keratinocytes, macrophage, neurons and mesenchymal stem cells (MSC). By the intersection of differential expression analysis and WGCNA analysis, 385 genes were obtained. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that these genes were highly correlated with multiple functions and pathways. Protein-protein interaction network analysis revealed that MRPS11 and MRPS12 were key genes, both of which were down-regulated in ischemic stroke. The Pseudo-time series analysis found that the expression of MRPS12 decreased gradually with the differentiation of pre-B cell CD34 cells in ischemic stroke, suggesting that the downregulation of MRPS12 expression may play an important role in ischemic stroke. At last, PCR showed that MRPS11 and MRPS12 were significantly down-regulated in peripheral blood of patients with ischemic stroke.

CONCLUSIONS

Our study provides a reference for the study of pathogenesis and key targets of ischemic stroke.

Integrating multiple machine learning methods to construct glutamine metabolism-related signatures in lung adenocarcinoma

Background

Glutamine metabolism (GM) is known to play a critical role in cancer development, including in lung adenocarcinoma (LUAD), although the exact contribution of GM to LUAD remains incompletely understood. In this study, we aimed to discover new targets for the treatment of LUAD patients by using machine learning algorithms to establish prognostic models based on GM-related genes (GMRGs).

Methods

We used the AUCell and WGCNA algorithms, along with single-cell and bulk RNA-seq data, to identify the most prominent GMRGs associated with LUAD. Multiple machine learning algorithms were employed to develop risk models with optimal predictive performance. We validated our models using multiple external datasets and investigated disparities in the tumor microenvironment (TME), mutation landscape, enriched pathways, and response to immunotherapy across various risk groups. Additionally, we conducted in vitro and in vivo experiments to confirm the role of LGALS3 in LUAD.

Results

We identified 173 GMRGs strongly associated with GM activity and selected the Random Survival Forest (RSF) and Supervised Principal Components (SuperPC) methods to develop a prognostic model. Our model's performance was validated using multiple external datasets. Our analysis revealed that the low-risk group had higher immune cell infiltration and increased expression of immune checkpoints, indicating that this group may be more receptive to immunotherapy. Moreover, our experimental results confirmed that LGALS3 promoted the proliferation, invasion, and migration of LUAD cells.

Conclusion

Our study established a prognostic model based on GMRGs that can predict the effectiveness of immunotherapy and provide novel approaches for the treatment of LUAD. Our findings also suggest that LGALS3 may be a potential therapeutic target for LUAD.

Solute carrier-related signature for assessing prognosis and immunity in patients with clear-cell renal cell carcinoma

Background

Clear-cell renal cell carcinoma (ccRCC) is the most common malignant kidney cancer. However, the tumor microenvironment and crosstalk involved in metabolic reprogramming in ccRCC are not well-understood.

Methods

We used The Cancer Genome Atlas to obtain ccRCC transcriptome data and clinical information. The E-MTAB-1980 cohort was used for external validation. The GENECARDS database contains the first 100 solute carrier (SLC)-related genes. The predictive value of SLC-related genes for ccRCC prognosis and treatment was assessed using univariate Cox regression analysis. An SLC-related predictive signature was developed through Lasso regression analysis and used to determine the risk profiles of patients with ccRCC. Patients in each cohort were separated into high- and low-risk groups based on their risk scores. The clinical importance of the signature was assessed through survival, immune microenvironment, drug sensitivity, and nomogram analyses using R software.

Results

SLC25A23, SLC25A42, SLC5A1, SLC3A1, SLC25A37, SLC5A6, SLCO5A1, and SCP2 comprised the signatures of the eight SLC-related genes. Patients with ccRCC were separated into high- and low-risk groups based on the risk value in the training and validation cohorts; the high-risk group had a significantly worse prognosis (p < 0.001). The risk score was an independent predictive indicator of ccRCC in the two cohorts according to univariate and multivariate Cox regression (p < 0.05). Analysis of the immune microenvironment showed that immune cell infiltration and immune checkpoint gene expression differed between the two groups (p < 0.05). Drug sensitivity analysis showed that compared to the low-risk group, the high-risk group was more sensitive to sunitinib, nilotinib, JNK-inhibitor-VIII, dasatinib, bosutinib, and bortezomib (p < 0.001). Survival analysis and receiver operating characteristic curves were validated using the E-MTAB-1980 cohort.

Conclusions

SLC-related genes have predictive relevance in ccRCC and play roles in the immunological milieu. Our results provide insight into metabolic reprogramming in ccRCC and identify promising treatment targets for ccRCC.

Comprehensive analysis of pan-cancer reveals the potential of SLC16A1 as a prognostic and immunological biomarker

SLC16A1 plays an important role in the development of multiple cancer types. Pan-cancer analysis may have significant impacts on the exploration of the relationship between SLC16A1 gene expression, prognosis and the molecular mechanisms of tumorigenesis. In this study, through the analysis of TCGA and GEO datasets, we explored the expression level and survival prognosis of SLC16A1 in pan-cancer, and further explored the differences in SLC16A1 gene mutation, methylation, and phosphorylation between tumor and normal tissues. In addition, we focused on the biological function of this gene and the relationship between the prognosis and immune infiltration by immune infiltration analysis and enrichment analysis, in order to evaluate the diagnostic and prognostic significance of SLC16A1 in carcinomas. The study found that SLC16A1 was highly expressed in 14 kinds of tumors, and there were statistically significant differences in the prognosis of 9 tumors. The phosphorylation level of S467 increased in OV, RCC, and UCEC. There was a statistically negative correlation between the CD8+ T-cell infiltration level and the SLC16A1 expression in HNSC, LUSC, SARC, TGCT, and KIRC. The cancer-related fibroblasts were positively correlated with SLC16A1 expression in BLCA, BRCA, KIRC, KIRP, PAAD, PCPG, and THCA. The enrichment analysis indicated that the tumorigenesis mechanism of this gene was mainly related to "glycolysis and glucose metabolism synthesis." SLC16A1 was a promising prognostic and immunological biomarker in pan-cancer.

Integration of clinical and spatial data to explore lipid metabolism-related genes for predicting prognosis and immune microenvironment in gliomas

Lipid metabolism is crucial to tumor growth and immune microenvironment as well as drug sensitivity in glioma. Identifying prognostic indicators of glioma and elucidating the mechanisms of glioma progression are critical for improving the prognosis of glioma patients. In this study, we investigated the role and prognostic value of metabolism-related genes in glioma by integrative analysis of datasets from GEO, CGGA, and TCGA. Based on clinical data and transcriptome data, we found that the expression pattern of three major pathways related to lipid metabolism is fatty acidhigh-phospholipidhigh-triglyceridelow, which is associated with better prognosis and immune infiltration. The genes involved in these three pathways were used to generate a prognostic model, which showed high stability and efficiency in the test set and validation set. The spatial transcriptome of glioma patients revealed that the microenvironment of the regions with high expression of risk genes CAV1 and SCD is in a state of hypoxia, EMT, and cell cycle arrest, and thus can be used as markers of metabolic reprogramming in the tumor microenvironment. In the high-risk group, M0 macrophages and M1 macrophages were significantly enriched, and the risk score was significantly correlated with gene mutation and methylation of risk genes. We further performed drug sensitivity screening corresponding to different risk genes. This study provided novel insights into the differential immune microenvironment with different expression patterns of metablism-related genes and highlighted the spatial and temporal synergy of tumor progression and metabolic reprogramming.

The hsa_circ_0000276-ceRNA regulatory network and immune infiltration in cervical cancer

BACKGROUND

Our previous studies have confirmed that miR-154-5p can regulate pRb expression, and thus, play a tumor suppressor role in HPV16 E7-induced cervical cancer. However, its upstream molecules have not been elucidated in the progression of cervical cancer. This study aimed to explore the role of the miR-154-5p upstream molecule, hsa_circ_0000276 in cervical cancer development and its possible mechanisms of action.

METHODS

We detected differences in whole transcriptome expression profiles of cervical squamous carcinoma and tissues adjacent to cervical cancer tissues from patients using microarray technology to predict circular RNAs (circRNAs) with binding sites to miR-154-5p. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to detect the expression of hsa_circ_0000276 (which had the strongest binding capacity to miR-154 and was selected as the target molecule) in cervical cancer tissues, followed by in vitro functional assays. Downstream microRNAs (miRNAs) and mRNAs of hsa_circ_0000276 were identified using transcriptome microarray data and databases, while the protein-protein interaction networks were obtained using STRING. A competing endogenous RNA (ceRNA) network centered on hsa_circ_0000276 was constructed using Cytoscape and GO and KEGG databases. Abnormal expression and prognosis of critical downstream molecules were analyzed using gene databases and molecular experiments. qRT-PCR and western blot analysis was performed to verify the expression of candidate genes.

RESULTS

We identified 4,001 differentially expressed circRNAs between HPV16-positive cervical squamous carcinoma and benign cervical tissues and 760 circRNAs targeting miR-154-5p, including hsa_circ_0000276. hsa_circ_0000276 and miR-154-5p directly bound, and hsa_circ_0000276 was upregulated, in cervical precancerous lesions and cervical cancer tissues and cells. Silencing hsa_circ_0000276 inhibited G1/S transition and cell proliferation and promoted apoptosis in SiHa and CaSki cells. Bioinformatics analysis showed that the hsa_circ_0000276 ceRNA network included 17 miRNAs and seven mRNAs, and downstream molecules of hsa_circ_0000276 were upregulated in cervical cancer tissues. These downstream molecules were associated with a poor prognosis and affected cervical cancer-associated immune infiltration. Of these, expression of CD47, LDHA, PDIA3, and SLC16A1 was downregulated in sh_hsa_circ_0000276 cells.

CONCLUSIONS

Our findings show that hsa_circ_0000276 exerts cancer-promoting effects in cervical cancer and is an underlying biomarker for cervical squamous cell carcinoma.

Exploring the role of sphingolipid-related genes in clinical outcomes of breast cancer

Background

Despite tremendous advances in cancer research, breast cancer (BC) remains a major health concern and is the most common cancer affecting women worldwide. Breast cancer is a highly heterogeneous cancer with potentially aggressive and complex biology, and precision treatment for specific subtypes may improve survival in breast cancer patients. Sphingolipids are important components of lipids that play a key role in the growth and death of tumor cells and are increasingly the subject of new anti-cancer therapies. Key enzymes and intermediates of sphingolipid metabolism (SM) play an important role in regulating tumor cells and further influencing clinical prognosis.

Methods

We downloaded BC data from the TCGA database and GEO database, on which we performed in depth single-cell sequencing analysis (scRNA-seq), weighted co-expression network analysis, and transcriptome differential expression analysis. Then seven sphingolipid-related genes (SRGs) were identified using Cox regression, least absolute shrinkage, and selection operator (Lasso) regression analysis to construct a prognostic model for BC patients. Finally, the expression and function of the key gene PGK1 in the model were verified by in vitro experiments.

Results

This prognostic model allows for the classification of BC patients into high-risk and low-risk groups, with a statistically significant difference in survival time between the two groups. The model is also able to show high prediction accuracy in both internal and external validation sets. After further analysis of the immune microenvironment and immunotherapy, it was found that this risk grouping could be used as a guide for the immunotherapy of BC. The proliferation, migration, and invasive ability of MDA-MB-231 and MCF-7 cell lines were dramatically reduced after knocking down the key gene PGK1 in the model through cellular experiments.

Conclusion

This study suggests that prognostic features based on genes related to SM are associated with clinical outcomes, tumor progression, and immune alterations in BC patients. Our findings may provide insights for the development of new strategies for early intervention and prognostic prediction in BC.

FNBP4 is a Potential Biomarker Associated with Cuproptosis and Promotes Tumor Progression in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that lacks an efficient therapeutic approach because of its elusive molecular mechanisms. This study aimed to investigate the biological function and potential mechanism of formin-binding protein 4 (FNBP4) in HCC.

Methods

FNBP4 expression in tissues and cells were detected by quantitative real-time PCR (qRT‒PCR), Western blot, and immunohistochemistry (IHC). The Kaplan-Meier method was used to explore the correlation between the FNBP4 expression and clinical survival. MTT, EdU incorporation, colony formation, and Transwell assays were performed to evaluate the function of FNBP4 in cell proliferation and migration in vitro. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used to explore the potential mechanism of FNBP4. The prognostic risk signature and nomogram were constructed to demonstrate the prognostic value of FNBP4.

Results

We found that FNBP4 was upregulated in patients with HCC and associated with poor overall survival (OS). Furthermore, knockdown of FNBP4 inhibited the proliferation and migration in HCC cells. Then, we performed a KEGG pathway analysis of the coexpressed genes associated with FNBP4 and found that FNBP4 may be associated with tumor-related signaling pathways and cuproptosis. We verified that FNBP4 could cause cell cycle progression and inactivation of the hippo signaling pathway. A prognostic risk signature containing three FNBP4-related differentially expressed cuproptosis regulators (DECRs) was established and can be used as an independent risk factor to evaluate the prognosis of patients with HCC. In addition, a nomogram including a risk score and clinicopathological factors was used to predict patient survival probabilities.

Conclusion

FNBP4, as a potential biomarker associated with cuproptosis, promotes HCC cell proliferation and metastasis. We provide a new potential strategy for HCC treatment by targeting FNBP4.

Integrating single-cell RNA-seq and bulk RNA-seq to construct prognostic signatures to explore the role of glutamine metabolism in breast cancer

BACKGROUND

Although breast cancer (BC) treatment has entered the era of precision therapy, the prognosis is good in the case of comprehensive multimodal treatment such as neoadjuvant, endocrine, and targeted therapy. However, due to its high heterogeneity, some patients still cannot benefit from conventional treatment and have poor survival prognoses. Amino acids and their metabolites affect tumor development, alter the tumor microenvironment, play an increasingly obvious role in immune response and regulation of immune cell function, and are involved in acquired and innate immune regulation; therefore, amino acid metabolism is receiving increasing attention.

METHODS

Based on public datasets, we carried out a comprehensive transcriptome and single-cell sequencing investigation. Then we used 2.5 Weighted Co-Expression Network Analysis (WGCNA) and Cox to evaluate glutamine metabolism-related genes (GRGs) in BC and constructed a prognostic model for BC patients. Finally, the expression and function of the signature key gene SNX3 were examined by in vitro experiments.

RESULTS

In this study, we constituted a risk signature to predict overall survival (OS) in BC patients by glutamine-related genes. According to our risk signature, BC patients can obtain a Prognostic Risk Signature (PRS), and the response to immunotherapy can be further stratified according to PRS. Compared with traditional clinicopathological features, PRS demonstrated robust prognostic power and accurate survival prediction. In addition, altered pathways and mutational patterns were analyzed in PRS subgroups. Our study sheds some light on the immune status of BC. In in vitro experiments, the knockdown of SNX3, an essential gene in the signature, resulted in a dramatic reduction in proliferation, invasion, and migration of MDA-MB-231 and MCF-7 cell lines.

CONCLUSION

We established a brand-new PRS consisting of genes associated with glutamine metabolism. It expands unique ideas for the diagnosis, treatment, and prognosis of BC.

Apprising Diagnostic and Prognostic Biomarkers in Cutaneous Melanoma—Persistent Updating

The incidence of melanoma, a very aggressive skin cancer, has increased over the past few decades. Although there are well-established clinical, dermoscopic and histopathological criteria, the diagnosis is often performed late, which has important implications on the patient’s clinical outcome. Unfortunately, melanoma is one of the most challenging tumors to diagnose because it is a heterogeneous neoplasm at the clinical, histopathological, and molecular level. The use of reliable biomarkers for the diagnosis and monitoring of disease progression is becoming a standard of care in modern medicine. In this review, we discuss the latest studies, which highlight findings from the genomics, epitranscriptomics, proteomics and metabolomics areas, pointing out different genes, molecules and cells as potential diagnostic and prognostic biomarkers in cutaneous melanoma.

Integrated Analysis of Genomic and Transcriptomic Profiles Identified the Role of GTP Binding Protein-4 (GTPBP4) in Breast Cancer

Purpose: To explore the significance of GTP-binding protein 4 (GTPBP4) in breast cancer.

Methods: Firstly, GTPBP4 expression analysis was performed in TIMER and UALCAN databases. Subsequently, the TCGA cohort and multiple Gene Expression Omnibus Cohorts were used as validation for GTPBP4 expression. Besides, we also evaluated the diagnostic value of GTPBP4 in TCGA Cohort and multiple GEO Cohorts. The predictive effect of GTPBP4 in breast cancer was then assessed using survival analysis. Then we look at the role of GTPBP4 in the immune milieu and create a Nomogram to help patients with breast cancer understand their prognosis. Finally, in vitro tests were carried out to look at GTPBP4 expression and function in breast cancer cell lines.

Results: GTPBP4 is an independent breast cancer prognostic factor that is upregulated in the disease (p < 0.05). Enrichment analysis showed that GTPBP4 was associated with multiple functions and pathways. In addition, GTPBP4 is associated with a variety of immune cell types (p < 0.05). PCR assay showed that GTPBP4 expression was up-regulated in breast cancer cell lines. The activity, migration, and proliferation of breast cancer cells were considerably reduced after GTPBP4 knockdown in the CCK-8, Transwell, and Scratch assays.

Conclusions: Our research discovered a new breast cancer biomarker that can be used as a guide for breast cancer diagnosis and treatment.

Single-Cell Sequencing Analysis Based on Public Databases for Constructing a Metastasis-Related Prognostic Model for Gastric Cancer

Background

Although incidences of gastric cancer have decreased in recent years, the disease remains a significant danger to human health. Lack of early symptoms often leads to delayed diagnosis of gastric cancer, so that many patients miss the opportunity for surgery. Treatment for advanced gastric cancer is often limited. Immunotherapy, targeted therapy, and the mRNA vaccine have all emerged as potentially viable treatments for advanced gastric cancer. However, our understanding of the immune microenvironment of gastric cancer is far from sufficient; now is the time to explore this microenvironment.

Methods

In our study, using TCGA dataset and the GEO dataset GSE62254, we performed in-depth transcriptome and single-cell sequencing analyses based on public databases. We analyzed differential gene expressions of immune cells in metastatic and nonmetastatic gastric cancer and constructed a prognostic model of gastric cancer patients based on these differential gene expressions. We also screened candidate vaccine genes for gastric cancer.

Results

This prognostic model can accurately predict the prognosis of gastric cancer patients by dividing them into high-risk and low-risk groups. In addition to this, we identified a candidate vaccine gene for gastric cancer: PTPN6.

Conclusions

Our study could provide new ideas for the treatment of gastric cancer.

Transcriptome Analysis of Solute Carrier-Associated Genes in Hepatocellular Carcinoma: Friend or Foe?

Hepatocellular carcinoma (HCC) is one of the most common types of cancer, and its treatment remains difficult. Since the early symptoms of HCC are not obvious, many HCC patients are already at an advanced stage of the disease at the time of diagnosis. Although current targeted therapy and immunotherapy have been initially effective in HCC patients, several patients have shown low response rates or developed drug resistance, which leads to tumor progression and even death. Hence, there is an urgent need for new biomarkers to guide the prognosis and treatment of HCC. In our study, a prognostic signature consisting of nine SLC genes was constructed in HCC by comprehensive analysis. By calculating risk scores, HCC patients could be divided into high-risk and low-risk groups, with the high-risk group having a significantly poorer prognosis. In addition, we found a hub gene, SLC7A11, which is a robust prognostic marker of HCC. In conclusion, our study can serve as a reference for the prognostic evaluation and treatment of HCC.

Construction and Validation of a Novel Pyroptosis-Related Gene Signature to Predict the Prognosis of Uveal Melanoma

Uveal melanoma is the most common primary intraocular tumor with a poor prognosis. Currently, treatment for UVM is limited, and the development of drug resistance and tumor recurrence are common. Therefore, it is important to identify new prognostic biomarkers of UVM and explore their role in the tumor microenvironment. Pyroptosis is a way of cell programmed death, and related research is in full throttle. However, the role of pyroptosis in UVM is unclear. In this study, we constructed the prognosis model of pyroptosis-related genes of UVM. This model can accurately guide the prognosis of UVM, and different groups differ in immune infiltration. We further verified our results in cell experiments. To some extent, our study can provide new ideas for the diagnosis and treatment of UVM.

Prognostic Value of SLC16A3(MCT4) in Lung Adenocarcinoma and Its Clinical Significance

Background

Currently, lung adenocarcinoma is the most common form of lung cancer. Although the pathogenesis of lung adenocarcinoma is progressing rapidly, the mortality rate of lung adenocarcinoma is still high. Therefore, it is necessary to search for a new biomarker to guide the prognosis of lung adenocarcinoma.

Methods

The significance of SLC16A3 in lung adenocarcinoma was investigated by multi-database analysis. GEPIA, UALCAN, TIMER, Cbioportal, and R software were used for research.

Results

Our study found that SLC16A3 was highly expressed in lung adenocarcinoma and was associated with poor prognosis. Further studies have shown that SLC16A3 is involved in some metabolic pathways. Not only that, SLC16A3 is associated with immune cell infiltration and tumor mutation burden (TMB).

Conclusion

SLC16A3 has good prognostic significance in lung adenocarcinoma, based on which to explore treatment options may improve the prognosis of patients.

A Novel Pyroptosis-Related lncRNA Signature for Predicting the Prognosis of Skin Cutaneous Melanoma

Purpose

To construct a prognosis model of melanoma based on pyroptosis related genes.

Methods

Melanoma RNA-sequencing data was downloaded from TCGA. First, the lnRNAs related to pyroptosis were obtained through Pearson correlation analysis. Then, the prognosis model of pyroptosis related genes was constructed by Cox regression and Lasso regression. Melanoma patients were divided into high-risk and low-risk groups by risk score, and the differences in prognosis and immune microenvironment between the two groups were explored.

Results

We found that the high-risk group had a significantly poorer prognosis, and different groups differed in immune infiltration, m6A methylation, and immune checkpoint.

Conclusion

Our prognostic model can provide a reference for the study of pyroptosis in melanoma cells and provide a new idea for melanoma treatment.

Pan-cancer analysis and single-cell analysis revealed the role of ABCC5 transporter in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common subtype of liver cancer. Many patients with hepatocellular carcinoma are diagnosed at an advanced stage because the early symptoms are not obvious. For advanced hepatocellular carcinoma, immunotherapy and targeted therapy seem to be a promising direction. Finding a new prognostic marker for hepatocellular carcinoma and exploring its role in the immune microenvironment is of great value. ABCC transporters have previously been associated with drug resistance in hepatocellular tumors, but the exact mechanism remains unclear. Here, we conducted a study on ABCC5 in HCC and found that the expression of ABCC5 was up-regulated in HCC and was associated with poor prognosis. Further exploration revealed that ABCC5 was associated with immune infiltration of hepatocellular carcinoma. Single-cell analysis revealed a potential relationship between ABCC5 and immune cell differentiation. Therefore, it is significant to continue to explore the role of ABCC5 in hepatocellular carcinoma.

A pan-cancer analysis revealed the role of the SLC16 family in cancer

Cancer is one of the serious diseases that endanger human health and bring a heavy burden to world economic development. Although the current targeted therapy and immunotherapy have achieved initial results, the emergence of drug resistance shows that the existing research is far from enough. In recent years, the tumor microenvironment has been found to be an important condition for tumor development and has profound research value. The SLC16 family is a group of monocarboxylic acid transporters involved in cancer metabolism and the formation of the tumor microenvironment. However, there have been no generalized cancer studies in the SLC16 family. In this study, we conducted a pan-cancer analysis of the SLC16 family. The results showed that multiple members of the SLC16 family could be used as prognostic indicators for many tumors, and were associated with immune invasion and tumor stem cells. Therefore, the SLC16 family has extensive exploration value in the future.