Analyzing and validating the prognostic value and mechanism of colon cancer immune microenvironment

Prognostic Significance of CLDN1, INHBA, and CXCL12 in Colon Adenocarcinoma: A Multi-Omics and Single-Cell Approach

Background/Objectives: Colon adenocarcinoma (COAD), the most prevalent form of colorectal cancer, remains a leading cause of cancer-related mortality. Advances in various treatments for COAD have significantly improved treatment outcomes. However, therapeutic limitations persist, highlighting the need for personalized strategies driven by novel biomarkers. The aim was to identify key hub genes that could be potential biomarkers of COAD using comprehensive bioinformatic analyses. Methods: Differentially expressed genes (DEGs) and co-DEGs were identified from COAD gene expression datasets. Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were performed. Hub genes were extracted from protein-protein interaction (PPI) networks and validated epigenetically using microRNA (miRNA) and DNA methylation datasets. Their expression patterns were further examined via single-cell RNA sequencing (scRNA-seq) and immune cell infiltration analysis. Prognostic relevance was assessed based on tumor metastasis and survival outcomes. Results: Gene expression profiling identified 118 co-DEGs, with GO and KEGG pathway analyses revealing significant pathway enrichment. PPI network analysis pinpointed 27 key co-DEGs. Epigenetic profiling indicated that both miRNA interference and DNA methylation regulate CLDN1, INHBA, and CXCL12 expression levels. scRNA-seq analysis showed elevated CLDN1 expression in epithelial cells and INHBA in myeloid cells, and reduced CXCL12 expression in stromal cells. Prognostic analysis further demonstrated that CLDN1 and INHBA are significantly associated with poor COAD outcomes. Conclusions: We identified some potential prognostic biomarkers for patients with COAD. Further experimental validation is required to translate these findings into precision medicine for COAD.

Discovery of host genetic factors through multi-locus GWAS against toxoplasmosis in sheep: addressing one health perspectives

Toxoplasma gondii stands as one of the most successful pathogens, capable of infecting nearly all warm-blooded species. It is estimated that up to 50% of human population might harbor Toxoplasmosis infections. One of the primary transmission routes is the consumption of tissue cysts from infected farm animals used for food production. Thus, controlling Toxoplasmosis in farm animals is of vital importance for human health and food safety. Selective breeding in farm animals, where available, could complement classical control measures like biosecurity measures, vaccination, and test-and-cull methods. This multidisciplinary approach will make the eradication of Toxoplasmosis more effective. For this purpose, we conducted four multi-locus genome-wide association (GWA) approaches to identify the polygenic factors underlying innate resistance to Toxoplasma gondii in naturally infected sheep. Our findings indicate that 16 single nucleotide polymorphisms (SNPs), exhibiting varying degrees of statistical power, play a significant role in host immunity against T. gondii infection. We propose the genes containing these SNPs or located within 100 ± Kb of them (PLSCR5, EPHA3, DGKB, IL12B, CGA, WDR64, TMEM158, CLMP, and SIAE) as potential candidate genes. This study represents the first exploration of host genetic factors against Toxoplasmosis in livestock, utilizing the ovine paradigm as its foundation.

Identification of M1 macrophage infiltration-related genes for immunotherapy in Her2-positive breast cancer based on bioinformatics analysis and machine learning

Over the past several decades, there has been a significant increase in the number of breast cancer patients. Among the four subtypes of breast cancer, Her2-positive breast cancer is one of the most aggressive breast cancers. In this study, we screened the differentially expressed genes from The Cancer Genome Atlas-Breast cancer database and analyzed the relationship between immune cell infiltration and differentially expressed genes using weighted gene co-expression network analysis. By constructing a module-trait relationships heatmap, the red module, which had the highest correlation value with M1 macrophages, was selected. Twenty hub genes were selected based on a protein-protein interaction network. Then, four overlapping M1 macrophage infiltration-related genes (M1 MIRGs), namely CCDC69, PPP1R16B, IL21R, and FOXP3, were obtained using five machine-learning algorithms. Subsequently, nomogram models were constructed to predict the incidence of Her2-positive breast cancer patients. The outer datasets and receiver operating characteristic curve analysis were used to validate the accuracy of the four M1 MIRGs and nomogram models. The average value of the area under the curve for the nomogram models was higher than 0.75 in both the training and testing sets. After that, survival analysis showed that higher expression of CCDC69, PPP1R16B, and IL21R were associated with overall survival of Her2-positive breast cancer patients. The expression of CCDC69 and PPP1R16B could lead to more benefits than the expression of IL21R and FOXP3 for immunotherapy. Lastly, we conducted immunohistochemistry staining to validate the aforementioned results. In conclusion, we found four M1 MIRGs that may be helpful for the diagnosis, prognosis, and immunotherapy of Her2-positive breast cancer.

Construction and significance of a breast cancer prognostic model based on cuproptosis-related genotyping and lncRNAs

BACKGROUND/PURPOSE

Cuproptosis may play a significant role in breast cancer (BC). We aimed to investigate the prognostic impact of cuproptosis-related lncRNAs in BC.

METHODS

Consensus clustering analysis categorized TCGA-BRCA samples into 3 clusters, followed by survival and immune analyses of the 3 clusters. LASSO-COX analysis was performed on cuproptosis-related lncRNAs differentially expressed in BC to construct a BC prognostic model. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) enrichment, immune, and drug prediction analyses were performed on the high-risk and low-risk groups. Cell experiments were conducted to analyze the results of drug prediction and two cuproptosis-related lncRNAs (AC104211.1 and LINC01863).

RESULTS

Significant differences were observed in survival outcomes and immune infiltration levels among the three clusters (p < 0.05). The validation of the model showed significant differences in survival outcomes between the high-risk and low-risk groups in both the training and validation sets (p < 0.05). Differential mRNAs between the two groups were significantly enriched in the Neuroactive ligand-receptor interaction and cAMP signaling pathway. Additionally, significant differences were found in immune infiltration levels, human leukocyte antigen (HLA) expression, Immunophenoscore (IPS) scores, and Tumor Immune Dysfunction and Exclusion (TIDE) scores between the two groups (p < 0.05). Drug prediction and corresponding cell experimental results showed that Trametinib, 5-fluorouracil, and AICAR significantly inhibited the viability of MCF-7 cells (p < 0.05). AC104211.1 and LINC01863 were found to impact the proliferation of BC cells.

CONCLUSION

The risk-scoring model obtained in this study may serve as a robust prognostic biomarker, potentially aiding in clinical decision-making for BC patients.

Construction and Validation of a T Cell Exhaustion-Related Prognostic Signature in Cholangiocarcinoma

Objective: T cell exhaustion (TEX) is a critical determinant of immune resistance. This study was performed to investigate the key genes linked to TEX in cholangiocarcinoma (CCA) and construct a TEX-associated gene signature to forecast the prognosis of patients with CCA. Methods: Based on the expression data acquired from the E-MTAB-6389 dataset, the TEX-related modules and module genes were identified using weighted coexpression network analysis (WGCNA). Subsequently, a TEX-related prognostic signature was built by using the univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. The immune cell infiltration in each CCA sample was evaluated using the single-sample gene set enrichment analysis (ssGSEA) package, followed by single-cell RNA sequencing (scRNA-seq) analysis. Furthermore, the expression of TEX-related genes in the gene signature was experimentally validated in CCA cells by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) and western blot analysis. Results: A total of 15 TEX-associated modules and 23 module genes were identified. Then, a four-gene signature related to TEX was established, containing Palladin, Cytoskeletal Associated Protein (PALLD), Member RAS Oncogene Family (RAB31), ADAM Metallopeptidase With Thrombospondin Type 1 Motif 2 (ADAMTS2), and WISP1, which could predict prognosis of patients with CCA. Moreover, neutrophils, endothelial cells, B cells, and T cells exhibited significant infiltration in CCA samples, and these four TEX-related genes were both significantly positively correlated with T cells, endothelial cells, and B cells while negatively correlated with neutrophils. Moreover, a total of 13 cell types were annotated after scRNA-seq analysis. Notably, RAB31 was mainly highly expressed in monocytes, macrophages, DC2 (Dendritic Cells 2), and DC3 (Dendritic Cells 3), and PALLD, ADAMTS2, and WISP1 were mainly overexpressed in fibroblasts. Furthermore, experimental validation revealed that the expression levels of PALLD, RAB31, ADAMTS2, and WISP1 were consistent with the trend results of bioinformatics analysis. Conclusion: A prognostic signature was developed by four TEX-related genes, including PALLD, RAB31, ADAMTS2, and WISP1, which might be a powerful predictor for the prognosis of patients with CCA. These TEX-related genes were related to the infiltration of neutrophils, endothelial cells, B cells, and T cells in CCA.

Significance of Ribonucleoside-diphosphate Reductase Subunit M2 in Lung Adenocarcinoma

INTRODUCTION

The Ribonucleoside-diphosphate Reductase subunit M2 (RRM2) is known to be overexpressed in various cancers, though its specific functional implications remain unclear. This aims to elucidate the role of RRM2 in the progression of Lung Adenocarcinoma (LUAD) by exploring its involvement and potential impact.

METHODS

RRM2 data were sourced from multiple databases to assess its diagnostic and prognostic significance in LUAD. We evaluated the association between RRM2 expression and immune cell infiltration, analyzed its function, and explored the effects of modulating RRM2 expression on LUAD cell characteristics through laboratory experiments.

RESULTS

RRM2 was significantly upregulated in LUAD tissues and cells compared to normal counterparts (p < 0.05), with rare genetic alterations noted (approximately 2%). This overexpression clearly distinguished LUAD from normal tissue (area under the curve (AUC): 0.963, 95% confidence intervals (CI): 0.946-0.981). Elevated RRM2 expression was significantly associated with adverse clinicopathological characteristics and poor prognosis in LUAD patients. Furthermore, a positive association was observed between RRM2 expression and immune cell infiltration. Pathway analysis revealed a critical connection between RRM2 and the cell cycle signaling pathway within LUAD. Targeting RRM2 inhibition effectively suppressed LUAD cell proliferation, migration, and invasion while promoting apoptosis. This intervention also modified the expression of several crucial proteins, including the downregulation of CDC25A, CDC25C, RAD1, Bcl-2, and PPM1D and the upregulation of TP53 and Bax (p < 0.05).

CONCLUSION

Our findings highlight the potential utility of RRM2 expression as a biomarker for diagnosing and predicting prognosis in LUAD, shedding new light on the role of RRM2 in this malignancy.

The T cell-mediated tumor killing patterns revealed tumor heterogeneous and proposed treatment recommendation in ovary cancer

BACKGROUND

Immune checkpoint inhibitors (ICIs) have greatly improved cancer treatment, but the role of genes related to T cell-mediated tumor killing (TTK) sensitivity in ovarian cancer (OV) is unclear.

METHODS

This study analyzed 1367 OV patients and 11 independent cohorts. The unsupervised clustering was conducted to identify three tumor subtypes based on genes that regulate tumor cell sensitivity to TTK (GSTTKs). The biological characteristics, genetic variations, immunological landscape, and therapeutic evaluation for each subtype were further explored.

RESULTS

Patients were divided into three reproducible subtypes based on 61 GSTKKs associated with prognosis. C1 was likely to be an invasive subtype with the worst prognosis and highly unstable genome. C2 might be an immune-active subtype with the best prognosis, high immune infiltration and preferable response to immunotherapy. C3 might be a metabolic subtype, resistant to immunotherapy, but sensitive to drug therapy. Following an extensive exploration into a variety of distinct molecular features between the three subtypes, the results suggested that C2 patients were considered to derive significant efficacy from immunotherapy. For C1 and C3 patients, chemotherapy might be an ideal treatment strategy.

CONCLUSIONS

In this study, three GSTKKs-based subtypes were identified by assessing TTK patterns in OV. These new insights further improved our understanding of GSTTKs and might refine clinical treatment strategies for OV patients.

Systemic inflammatory response in colorectal cancer is associated with tumour mismatch repair and impaired survival

The systemic inflammatory response (SIR), defined as elevated levels of circulating C-reactive protein (CRP), is an important predictor of impaired survival in colorectal cancer. The aim of this study was to explore the prognostic role of SIR and its association with tumour mismatch repair status and the immune response. Immune activity profiles of mononuclear cells isolated from CRC tissues and blood in the U-CAN exploration cohort (n = 69), were analysed by flow cytometry. In the U-CAN validation cohort (n = 257), T-helper cells (T-bet+), cytotoxic T cells (CD8+), regulatory T cells (FoxP3+), B cells (CD20+), and macrophages (CD68+) were analysed by multispectral imaging. Microsatellite instability was determined using five mononucleotide-repeat microsatellite markers. Patients with high CRP levels (> 10 mg/l) were significantly more often diagnosed with high-grade tumours and tumours exhibiting microsatellite instability. However, some patients with high CRP levels were found to have microsatellite-stable tumours. Furthermore, high CRP levels were associated with specific tumour immune traits including an augmented macrophage response and were significantly linked to poorer cancer-specific survival, particularly in patients with microsatellite-stable tumours. In conclusion, our findings suggest an interplay between SIR and mismatch repair status in CRC prognosis which needs to be further explored.

Identification and validation of a novel prognostic signature and key genes related to development of anaplastic thyroid carcinoma

BACKGROUND

Anaplastic thyroid carcinoma (ATC) is a rare but the most aggressive type of thyroid carcinoma. Nevertheless, limited advances were made to reduce mortality and improve survival over the last decades. Therefore, identifying novel diagnostic biomarkers and therapeutic targets for ATC patients is still needed.

MATERIALS AND METHODS

RNA sequencing data and corresponding clinical features were available from GEO and TCGA databases. We integrated WGCNA and PPI network analysis to identify hub genes associated with ATC development, and RT-qPCR was employed for data verification. Univariate and LASSO Cox regression analyses were used to generate prognostic signatures.

RESULTS

Based on PPI and WGCNA, 6 hub genes were identified, namely KIF2C, PBK, TOP2A, CDK1, KIF20A, and ASPM, which play vital roles in ATC development. Subsequently, RT-qPCR experiments showed that most of these genes were significantly upregulated in CAL-62 cells compared to Nthy-ori 3-1 cells. Moreover, a prognostic signature featuring GPSM2, FGF5, ASXL3, CYP4B1, CLMP, and DUXAP9 was generated, which was also verified by RT-qPCR results and proved as an independent predictor of poorer prognosis of ATC. Additionally, a nomogram incorporating the risk score and clinicopathological parameters was further constructed for accurate prediction of 1-, 3- and 5-year survival probabilities of ATC.

CONCLUSIONS

Our study identified 6 key genes critical to ATC development and constructed a prognostic signature. These findings provide reliable biomarkers and a relatively comprehensive tumorigenesis profile of ATC, which may inform future strategies for clinical diagnosis and pharmaceutical design.

Pan-cancer analysis and single-cell analysis reveals FAM110B as a potential target for survival and immunotherapy

Background: FAM110B belongs to the family that has a 110 sequence similarity (FAM110) and is located in the centrosome and mitotic spindle. FAM110B has been linked to tumor cell growth in earlier research. Uncertainty exists regarding FAM110B's function within the tumor microenvironment is unclear as well as pan-cancer. Methods: In order to assess the variation in FAM110B expression within normal and pan-cancer tissues, we combined the TCGA and GTEx databases. The cBioPortal database and the GSCALite platform were used to examine the variation in genome and methylation alteration of FAM110B. Cox regression, Kaplan-Meier, and SangerBox were employed to examine the clinical features and prognosis of FAM110B and pan-cancer. The purpose of the correlational research was to investigate the associations within immunerelated genes, tumor mutation burden, microsatellite instability, immune-related genes, and immunological checkpoints and FAM110B expression. ESTIMATE, EPIC, QUANTISEQ, and MCPCOUNTER methods were used to calculate the interaction among FAM110B expression as well as the tumor immune microenvironment. The immunoinfiltration and function of FAM110B were analyzed by single-cell databases (TISCH and CancerSEA). Finally, we evaluated the sensitivity of FAM110B to small-molecule medications through GDSC and CTRP databases. Results: The transcription and protein expression of FAM110B varies significantly throughout cancer types, and this has predictive value for the prognosis of some tumors; including brain lower grade glioma (LGG), stomach adenocarcinoma (STAD), pancreatic adenocarcinoma (PAAD), etc. In the tumor microenvironment, the expression level of FAM110B was associated with immune cell infiltration, immune checkpoint immune regulatory genes, tumor mutational burden, and microsatellite fragility to a certain extent. Conclusion: This work investigates the possibility of utility of FAM110B as a marker to forecast pan-cancer immunotherapy response, providing a theoretical basis for cancer therapy.

Development of prognostic signatures and risk index related to lipid metabolism in ccRCC

Background

Clear cell renal cell carcinoma (ccRCC) is a metabolic disorder characterized by abnormal lipid accumulation in the cytoplasm. Lipid metabolism-related genes may have important clinical significance for prognosis prediction and individualized treatment.

Methods

We collected bulk and single-cell transcriptomic data of ccRCC and normal samples to identify key lipid metabolism-related prognostic signatures. qPCR was used to confirm the expression of signatures in cancer cell lines. Based on the identified signatures, we developed a lipid metabolism risk score (LMRS) as a risk index. We explored the potential application value of prognostic signatures and LMRS in precise treatment from multiple perspectives.

Results

Through comprehensive analysis, we identified five lipid metabolism-related prognostic signatures (ACADM, ACAT1, ECHS1, HPGD, DGKZ). We developed a risk index LMRS, which was significantly associated with poor prognosis in patients. There was a significant correlation between LMRS and the infiltration levels of multiple immune cells. Patients with high LMRS may be more likely to respond to immunotherapy. The different LMRS groups were suitable for different anticancer drug treatment regimens.

Conclusion

Prognostic signatures and LMRS we developed may be applied to the risk assessment of ccRCC patients, which may have potential guiding significance in the diagnosis and precise treatment of ccRCC patients.

To explore the prognostic characteristics of colon cancer based on tertiary lymphoid structure-related genes and reveal the characteristics of tumor microenvironment and drug prediction

In order to construct a prognostic evaluation model of TLS features in COAD and better realize personalized precision medicine in COAD. Colon adenocarcinoma (COAD) is a common malignant tumor of the digestive system. At present, there is no effective prognostic marker to predict the prognosis of patients. Tertiary lymphoid structure (TLS) affects cancer progression by regulating immune microenvironment. Mining COAD biomarkers based on TLS-related genes helps to improve the prognosis of patients. In order to construct a prognostic evaluation model of TLS features in COAD and better realize personalized precision medicine in COAD. The mRNA expression data and clinical information of COAD and adjacent tissues were downloaded from the Cancer Genome Atlas database. The differentially expressed TLS-related genes of COAD relative to adjacent tissues were obtained by differential analysis. TLS gene co-expression analysis was used to mine genes highly related to TLS, and the intersection of the two was used to obtain candidate genes. Univariate, LASSO, and multivariate Cox regression analysis were performed on candidate genes to screen prognostic markers to construct a risk assessment model. The differences of immune characteristics were evaluated by ESTIMATE, ssGSEA and CIBERSORT in high and low risk groups of prognostic model. The difference of genomic mutation between groups was evaluated by tumor mutation burden score. Screening small molecule drugs through the GDSC library. Finally, a nomogram was drawn to evaluate the clinical value of the prognostic model. Seven TLS-related genes ADAM8, SLC6A1, PAXX, RIMKLB, PTH1R, CD1B, and MMP10 were screened to construct a prognostic model. Survival analysis showed that patients in the high-risk group had significantly lower overall survival rates. Immune microenvironment analysis showed that patients in the high-risk group had higher immune indicators, indicating higher immunity. The genomic mutation patterns of the high-risk and low-risk groups were significantly different, especially the KRAS mutation frequency was significantly higher in the high-risk group. Drug sensitivity analysis showed that the low-risk group was more sensitive to Erlotinib, Savolitinib and VE _ 822, which may be used as a potential drug for COAD treatment. Finally, the nomogram constructed by pathological features combined with RiskScore can accurately evaluate the prognosis of COAD patients. This study constructed and verified a TLS model that can predict COAD. More importantly, it provides a reference standard for guiding the prognosis and immunotherapy of COAD patients.

MUC16: clinical targets with great potential

Mucin 16 (MUC16) is a membrane-bound mucin that is abnormally expressed or mutated in a variety of diseases, especially tumors, while being expressed in normal body epithelium. MUC16 and its extracellular components are often important cancer-related biomarkers. Abnormal expression of MUC16 promotes tumor progression through mesenchymal protein, PI3K/AKT pathway, JAK2/STAT3 pathway, ERK/FBW7/c-Myc, and other mechanisms, and plays an important role in the occurrence and development of tumors. In addition, MUC16 also helps tumor immune escape by inhibiting T cells and NK cells. Many drugs and trials targeting MUC16 have been developed, and MUC16 may be a new direction for future treatments. In this paper, the mechanism of action of MUC16 in the development of cancer, especially in the immune escape of tumor, is introduced in detail, indicating the potential of MUC16 in clinical treatment.

Knockdown of ADAM8 inhibits the proliferation, migration, invasion, and tumorigenesis of renal clear cell carcinoma cells to enhance the immunotherapy efficacy

The current study performed bioinformatics and in vitro and in vivo experiments to explore the effects of ADAM8 on the malignant behaviors and immunotherapeutic efficacy of renal clear cell carcinoma (ccRCC) Cells. The modular genes most associated with immune cells were screened. Then, prognostic risk models were constructed by univariate COX analysis, LASSO regression analysis and multivariate COX analysis, and their diagnostic value was determined. The correlation between tumor mutation load (TMB) scores and the prognosis of ccRCC patients was clarified. Finally, six key genes (ABI3, ADAM8, APOL3, MX2, CCDC69, and STAC3) were analyzed for immunotherapy efficacy. Human and mouse ccRCC cell lines and human proximal tubular epithelial cell lines were used for in vitro cell experiments. The effect of ADAM8 overexpression or knockdown on tumor formation and survival in ccRCC cells was examined by constructing subcutaneous transplanted tumor model. Totally, 636 Black module genes were screened as being most associated with immune cell infiltration. Six genes were subsequently confirmed for the construction of prognostic risk models, of which ABI3, APOL3 and CCDC69 were low-risk factors, while ADAM8, MX2 and STAC3 were high-risk factors. The constructed risk model based on the identified six genes could accurately predict the prognosis of ccRCC patients. Besides, TMB was significantly associated with the prognosis of ccRCC patients. Furthermore, ABI3, ADAM8, APOL3, MX2, CCDC69 and STAC3 might play important roles in treatment concerning CTLA4 inhibitors or PD-1 inhibitors or combined inhibitors. Finally, we confirmed that ADAM8 could promote the proliferation, migration and invasion of ccRCC cells through in vitro experiments, and further found that in in vivo experiments, ADAM8 knockdown could inhibit tumor formation in ccRCC cells, improve the therapeutic effect of anti-PD1, and prolong the survival of mice. Our study highlighted the alleviative role of silencing ADAM8 in ccRCC patients.

A cuproptosis-related gene expression signature predicting clinical prognosis and immune responses in intrahepatic cholangiocarcinoma detected by single-cell RNA sequence analysis

BACKGROUND

Cholangiocarcinoma represents a malignant neoplasm originating from the hepatobiliary tree, with a subset of tumors developing inside the liver. Intrahepatic cholangiocarcinomas (ICC) commonly exhibit an asymptomatic presentation, rendering both diagnosis and treatment challenging. Cuproptosis, an emerging regulated cell death pathway induced by copper ions, has garnered attention recently. As cancer cells show altered copper metabolism and comparatively higher copper needs, cuproptosis may play a role in the development of ICC. However, studies investigating this possibility are currently lacking.

METHODS

Single-cell and bulk RNA sequence data were analyzed, and correlations were established between the expression of cuproptosis-related molecules and ICC patient survival. Genes with predicting survival were used to create a CUPT score using Cox and LASSO regression and tumor mutation burden (TMB) analysis. The CIBERSORT software was employed to characterize immune cell infiltration within the tumors. Furthermore, immune infiltration prediction, biological function enrichment, and drug sensitivity analyses were conducted to explore the potential implications of the cuproptosis-related signature. The effects of silencing solute carrier family 39 member 4 gene (SLC39A4) expression using siRNA were investigated using assays measuring cell proliferation, colony formation, and cell migration. Key genes of cuproptosis were detected by western blotting.

RESULTS

The developed CUPT score divided patients into high and low CUPT score groups. Those with a low score had significantly better prognosis and longer survival. In contrast, high CUPT scores were associated with worse clinical outcomes and significantly higher TMB. Comparisons of the two groups also indicated differences in the immune infiltrate present in the tumors. Finally, we were able to identify 95 drugs potentially affecting the cuproptosis pathway. Some of these might be effective in the treatment of ICC. The in vitro experiments revealed that suppressing the expression of SLC39A4 in ICC cell lines resulted in reduced cell proliferation, colony formation, and cell migration. It also led to an increase in cell death and the upregulation of key genes associated with cuproptosis, namely ferredoxin 1 (FDX1) and dihydrolipoyl transacetylase (DLAT). These findings strongly suggest that this cuproptosis-associated molecule may play a pivotal role in the development and metastasis of ICC.

CONCLUSIONS

Changes in the expression of a cuproptosis-related gene signature can predict the clinical prognosis of ICC with considerable accuracy. This supports the notion that cuproptosis influences the diversity and complexity of the immune microenvironment, mutational landscape, and biological behavior of ICC. Understanding this pathway better may hold promise for the development of innovative strategies in the management of this disease.

Single-cell transcriptomic profiling reveals immune cell heterogeneity in acute myeloid leukaemia peripheral blood mononuclear cells after chemotherapy

PURPOSE

Acute myeloid leukaemia (AML) is a heterogeneous disease characterised by the rapid clonal expansion of abnormally differentiated myeloid progenitor cells residing in a complex microenvironment. However, the immune cell types, status, and genome profile of the peripheral blood mononuclear cell (PBMC) microenvironment in AML patients after chemotherapy are poorly understood. In order to explore the immune microenvironment of AML patients after chemotherapy, we conducted this study for providing insights into precision medicine and immunotherapy of AML.

METHODS

In this study, we used single-cell RNA sequencing (scRNA-seq) to analyse the PBMC microenvironment from five AML patients treated with different chemotherapy regimens and six healthy donors. We compared the cell compositions in AML patients and healthy donors, and performed gene set enrichment analysis (GSEA), CellPhoneDB, and copy number variation (CNV) analysis.

RESULTS

Using scRNA-seq technology, 91,772 high quality cells of 44,950 PBMCs from AML patients and 46,822 PBMCs from healthy donors were classified as 14 major cell clusters. Our study revealed the sub-cluster diversity of T cells, natural killer (NK) cells, monocytes, dendritic cells (DCs), and haematopoietic stem cell progenitors (HSC-Prog) in AML patients under chemotherapy. NK cells and monocyte-DCs showed significant changes in transcription factor expression and chromosome copy number variation (CNV). We also observed significant heterogeneity in CNV and intercellular interaction networks in HSC-Prog cells.

CONCLUSION

Our results elucidated the PBMC single-cell landscape and provided insights into precision medicine and immunotherapy for treating AML.

CXADR-Like Membrane Protein Regulates Colonic Epithelial Cell Proliferation and Prevents Tumor Growth

BACKGROUND & AIMS

CXADR-like membrane protein (CLMP) is structurally related to coxsackie and adenovirus receptor. Pathogenic variants in CLMP gene have been associated with congenital short bowel syndrome, implying a role for CLMP in intestinal development. However, the contribution of CLMP to regulating gut development and homeostasis is unknown.

METHODS

In this study, we investigated CLMP function in the colonic epithelium using complementary in vivo and in vitro approaches, including mice with inducible intestinal epithelial cell (IEC)-specific deletion of CLMP (ClmpΔIEC), intestinal organoids, IECs with overexpression, or loss of CLMP and RNA sequencing data from individuals with colorectal cancer.

RESULTS

Loss of CLMP enhanced IEC proliferation and, conversely, CLMP overexpression reduced proliferation. Xenograft experiments revealed increased tumor growth in mice implanted with CLMP-deficient colonic tumor cells, and poor engraftment was observed with CLMP-overexpressing cells. ClmpΔIEC mice showed exacerbated tumor burden in an azoxymethane and dextran sulfate sodium-induced colonic tumorigenesis model, and CLMP expression was reduced in human colorectal cancer samples. Mechanistic studies revealed that CLMP-dependent regulation of IEC proliferation is linked to signaling through mTOR-Akt-β-catenin pathways.

CONCLUSIONS

These results reveal novel insights into CLMP function in the colonic epithelium, highlighting an important role in regulating IEC proliferation, suggesting tumor suppressive function in colon cancer.

High expression of CCDC69 is correlated with immunotherapy response and protective effects on breast cancer

BACKGROUND

As a molecule controlling the assembly of central spindles and recruitment of midzone component, coiled-coil domain-containing protein 69 (CCDC69) plays an important role in multiple cancers. Currently, the relationships between CCDC69 and immune infiltration or immunotherapy in breast cancer remain unclear.

METHODS

The expression and prognostic significance of CCDC69 in breast cancer were comprehensively analyzed by quantitative real-time PCR, immunohistochemical staining and various databases. The data source of differentially expressed genes, gene set enrichment analysis, and immune cell infiltration analysis came from The Cancer Genome Atlas (TCGA) database. Single-cell analysis based on IMMUcan database was used. The protein-protein interaction network was developed applying STRING, Cytoscape, CytoHubba, and GeneMANIA. TISIDB was employed in analyzing the CCDC69 co-expressed immune related genes. The correlations between CCDC69 and immunotherapy or immune-related scores were analyzed by CAMOIP and TISMO. Ctr-db was also used to conduct drug sensitivity analysis.

RESULTS

The mRNA of CCDC69 was downregulated in breast cancer tissues compared with normal tissues. Higher CCDC69 expression was associated with a better breast cancer prognosis. Enrichment analysis showed that the co-expression genes of CCDC69 were mainly related to immune-related pathways. The expression of CCDC69 was found to be positively correlated with multiple tumor-suppression immune infiltration cells, especially T cells and dendritic cells. Meanwhile, high CCDC69 expression can predict better immunotherapy responses when compared with low CCDC69 expression. After the interferon-gamma treatment, the CCDC69 expression was elevated in vitro. CCDC69 expression was a reliable predictor for the response status of two therapeutic strategies in breast cancer.

CONCLUSIONS

Our research revealed the clinical significance of CCDC69 in breast cancer and validated the critical roles of CCDC69 in the tumor immune infiltration and immunotherapy responses.

Biological functions and molecular subtypes regulated by miR-142-3p in colon cancer

MicroRNA-142-3p (miR-142-3p) has been reported to be implicated in colon cancer; however, the possible regulatory mechanisms and molecular subtypes regulated by miR-142-3p have not been fully elucidated. This study aimed to investigate the biological functions and regulatory mechanism of miR-142-3p in colon cancer. The expression level of miR-142-3p in colon cancer was analyzed based on the mRNA and miRNA expression datasets of colon cancer retrieved from The Cancer Genome Atlas. Target genes of miR-142-3p were also predicted. Based on these target genes, the functions and subtypes of miR-142-3p were investigated. The metabolic and tumor-related pathways, immune microenvironment, and target gene expression between the 2 subtypes were analyzed. MiR-142-3p was upregulated in tumor tissues, and its high expression indicated a poor prognosis. A total of 39 target genes were predicted, which were significantly involved in autophagy- and metabolism-related functions and pathways. Based on these target genes, the colon cancer samples were clustered into 2 subtypes. There were 35 metabolism-related pathways that were significantly different between the 2 clusters. The immune and stromal scores in cluster 2 were higher than those in cluster 1, whereas the tumor purity of cluster 2 was significantly lower than that of cluster 1. TP53INP2 expression in cluster 2 was higher than that in cluster 1. MiR-142-3p may promote colon cancer progression via autophagy- and metabolism-related pathways. MiR-142-3p may be served as a candidate target for the treatment of colon cancer.

Combination therapy with antibody‑drug conjugate RC48 (disitamab vedotin) and zimberelimab (PD‑1 inhibitor) successfully controlled recurrent HER2‑positive breast cancer resistant to trastuzumab emtansine: A case report

Options for later-line therapy are limited for patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer who have exhibited resistance to several systemic treatments. Antibody drug conjugates (ADCs) and immune checkpoint inhibitors are novel approaches for HER2-positive breast cancer, but few reports have been published regarding the efficacy of their combinations, particularly in patients with prior ADC failure. The present report describes a case of recurrent metastatic HER2-positive breast cancer, which responded poorly to several perioperative systemic therapies, including chemotherapies, HER2-targeted antibodies, small molecule inhibitors and trastuzumab emtansine (an ADC), along with post-surgical radiotherapy. Following failure of front-line therapies for recurrent cancer located in the chest wall, combination treatment with another HER2-targeted ADC, disitamab vedotin (120 mg), and zimberelimab (240 mg), a fully humanized anti-programmed cell death protein-1 (PD-1) antibody, administered intravenously every 2 weeks, was initiated. The tumor lesions improved slightly after two cycles of treatment and shrunk markedly, and almost disappeared at the end of the sixth cycle of therapy. The patient is still in remission at present. The present findings suggest the potential efficacy of HER2-targeted ADCs combined with PD-1 inhibitors for patients with HER2-positive breast cancer, including those resistant to prior HER2-targeted ADCs.

Exploration of novel clusters and prognostic value of immune‑related signatures and identify HAMP as hub gene in colorectal cancer

Immune checkpoint inhibitors currently serve an important role in prolonging patients' overall survival. However, the prognostic signatures of immune checkpoint inhibitors in colorectal cancer (CRC) remain uncertain and more knowledge on the genetic characteristics of colorectal cancer is needed. Patients with CRC from The Cancer Genome Atlas were classified into high-immunity group and low-immunity group based on median scores from single-sample gene set enrichment analysis using the GSVA package. We explored immune status by immune scores, stromal scores and tumor purity scores in ESTIMATE package and surveyed the difference of immune cells distribution with CIBERSORT package. Eighteen genes were selected using the LASSO Cox regression method and a prognostic risk model was constructed. Compared with patients in the low-risk group, those in the high-risk group had a significantly shorter survival time. For assessment of the prognostic validity of the risk model, receiver operating characteristic curves with areas under the curve of 0.769, 0.774 and 0.771 for 1, 3 and 5 years respectively. Differences in molecular mechanisms between high- and low-risk groups were analyzed using the clusterProfiler package. Tumor Immune Dysfunction and Exclusion data were downloaded and analyzed. The top 5 enriched pathways in the high-risk group involved 'calcium signaling', 'dilated cardiomyopathy', 'extracellular matrix receptor interaction', 'hypertrophic cardiomyopathy' and 'neuroactive ligand receptor interaction'. HAMP was identified as a hub gene, which was highly expressed in tumor samples. The results of the present study indicate that the prognostic model based on both immune-related genes and HAMP has the potential to support personalized treatment.

Identification of fibroblast-related genes based on single-cell and machine learning to predict the prognosis and endocrine metabolism of pancreatic cancer

Background

Single-cell sequencing technology has become an indispensable tool in tumor mechanism and heterogeneity studies. Pancreatic adenocarcinoma (PAAD) lacks early specific symptoms, and comprehensive bioinformatics analysis for PAAD contributes to the developmental mechanisms.

Methods

We performed dimensionality reduction analysis on the single-cell sequencing data GSE165399 of PAAD to obtain the specific cell clusters. We then obtained cell cluster-associated gene modules by weighted co-expression network analysis and identified tumorigenesis-associated cell clusters and gene modules in PAAD by trajectory analysis. Tumor-associated genes of PAAD were intersected with cell cluster marker genes and within the signature module to obtain genes associated with PAAD occurrence to construct a prognostic risk assessment tool by the COX model. The performance of the model was assessed by the Kaplan-Meier (K-M) curve and the receiver operating characteristic (ROC) curve. The score of endocrine pathways was assessed by ssGSEA analysis.

Results

The PAAD single-cell dataset GSE165399 was filtered and downscaled, and finally, 17 cell subgroups were filtered and 17 cell clusters were labeled. WGCNA analysis revealed that the brown module was most associated with tumorigenesis. Among them, the brown module was significantly associated with C11 and C14 cell clusters. C11 and C14 cell clusters belonged to fibroblast and circulating fetal cells, respectively, and trajectory analysis showed low heterogeneity for fibroblast and extremely high heterogeneity for circulating fetal cells. Next, through differential analysis, we found that genes within the C11 cluster were highly associated with tumorigenesis. Finally, we constructed the RiskScore system, and K-M curves and ROC curves revealed that RiskScore possessed objective clinical prognostic potential and demonstrated consistent robustness in multiple datasets. The low-risk group presented a higher endocrine metabolism and lower immune infiltrate state.

Conclusion

We identified prognostic models consisting of APOL1, BHLHE40, CLMP, GNG12, LOX, LY6E, MYL12B, RND3, SOX4, and RiskScore showed promising clinical value. RiskScore possibly carries a credible clinical prognostic potential for PAAD.

Transcriptome analysis identification of A-to-I RNA editing in granulosa cells associated with PCOS

Background

Polycystic ovary syndrome (PCOS) is a complex, multifactor disorder in women of reproductive age worldwide. Although RNA editing may contribute to a variety of diseases, its role in PCOS remains unclear.

Methods

A discovery RNA-Seq dataset was obtained from the NCBI Gene Expression Omnibus database of granulosa cells from women with PCOS and women without PCOS (controls). A validation RNA-Seq dataset downloaded from the European Nucleotide Archive Databank was used to validate differential editing. Transcriptome-wide investigation was conducted to analyze adenosine-to-inosine (A-to-I) RNA editing in PCOS and control samples.

Results

A total of 17,395 high-confidence A-to-I RNA editing sites were identified in 3,644 genes in all GC samples. As for differential RNA editing, there were 545 differential RNA editing (DRE) sites in 259 genes with Nucleoporin 43 (NUP43), Retinoblastoma Binding Protein 4 (RBBP4), and leckstrin homology-like domain family A member 1 (PHLDA) showing the most significant three 3'-untranslated region (3'UTR) editing. Furthermore, we identified 20 DRE sites that demonstrated a significant correlation between editing levels and gene expression levels. Notably, MIR193b-365a Host Gene (MIR193BHG) and Hook Microtubule Tethering Protein 3 (HOOK3) exhibited significant differential expression between PCOS and controls. Functional enrichment analysis showed that these 259 differentially edited genes were mainly related to apoptosis and necroptosis pathways. RNA binding protein (RBP) analysis revealed that RNA Binding Motif Protein 45 (RBM45) was predicted as the most frequent RBP binding with RNA editing sites. Additionally, we observed a correlation between editing levels of differential editing sites and the expression level of the RNA editing enzyme Adenosine Deaminase RNA Specific B1 (ADARB1). Moreover, the existence of 55 common differentially edited genes and nine differential editing sites were confirmed in the validation dataset.

Conclusion

Our current study highlighted the potential role of RNA editing in the pathophysiology of PCOS as an epigenetic process. These findings could provide valuable insights into the development of more targeted and effective treatment options for PCOS.

Identification of a novel MSI-related ceRNA network for predicting the prognosis and immunotherapy response of gastric cancer

BACKGROUND

Mounting evidence has underscored the pivotal role of the competitive endogenous RNA (ceRNA) regulatory networks among various cancers. However, the behavior characteristics and complexity of the ceRNA network in Gastric cancer (GC) remains unclear. In this study, we aimed to clarify a Microsatellite instability (MSI)-related ceRNA regulatory network and identify potential prognostic markers associated with GC.

METHODS AND RESULTS

We extracted transcriptome data of GC patients from The Cancer Genome Atlas (TCGA) and identified differentially expressed lncRNAs, miRNAs and mRNAs based on MSI status. A hub ceRNA network including 1 lncRNAs (MIR99AHG), 2 miRNAs and 26 mRNAs specific to MSI was established in GC. We further constructed a prognostic model with seven target mRNAs by Lasso Cox regression, which yielded AUC values of 0.76. The prognostic model was further validated in an external independent dataset that integrated three GEO datasets. The characterization of immune cell infiltration and immunotherapy effects between high-risk and low-risk groups were then analyzed. Immune cell infiltration was significantly different between high- and low-risk groups based on risk scores. GC patients with lower risk scores correlated with better immune checkpoint inhibitor therapy (ICI) response. We further validated the expression and regulatory relationship of the ceRNA network in vitro experiments, and also confirmed the relationship between MIR99AHG and PD-L1.

CONCLUSIONS

Our research provides in-depth insights on the role of MSI-related ceRNA in GC and the prognosis and ICIs therapy response of GC patients can be assessed by the risk model based on MSI-related ceRNA network.

FAM family gene prediction model reveals heterogeneity, stemness and immune microenvironment of UCEC

Background: Endometrial cancer (UCEC) is a highly heterogeneous gynecologic malignancy that exhibits variable prognostic outcomes and responses to immunotherapy. The Familial sequence similarity (FAM) gene family is known to contribute to the pathogenesis of various malignancies, but the extent of their involvement in UCEC has not been systematically studied. This investigation aimed to develop a robust risk profile based on FAM family genes (FFGs) to predict the prognosis and suitability for immunotherapy in UCEC patients. Methods: Using the TCGA-UCEC cohort from The Cancer Genome Atlas (TCGA) database, we obtained expression profiles of FFGs from 552 UCEC and 35 normal samples, and analyzed the expression patterns and prognostic relevance of 363 FAM family genes. The UCEC samples were randomly divided into training and test sets (1:1), and univariate Cox regression analysis and Lasso Cox regression analysis were conducted to identify the differentially expressed genes (FAM13C, FAM110B, and FAM72A) that were significantly associated with prognosis. A prognostic risk scoring system was constructed based on these three gene characteristics using multivariate Cox proportional risk regression. The clinical potential and immune status of FFGs were analyzed using CiberSort, SSGSEA, and tumor immune dysfunction and rejection (TIDE) algorithms. qRT-PCR and IHC for detecting the expression levels of 3-FFGs. Results: Three FFGs, namely, FAM13C, FAM110B, and FAM72A, were identified as strongly associated with the prognosis of UCEC and effective predictors of UCEC prognosis. Multivariate analysis demonstrated that the developed model was an independent predictor of UCEC, and that patients in the low-risk group had better overall survival than those in the high-risk group. The nomogram constructed from clinical characteristics and risk scores exhibited good prognostic power. Patients in the low-risk group exhibited a higher tumor mutational load (TMB) and were more likely to benefit from immunotherapy. Conclusion: This study successfully developed and validated novel biomarkers based on FFGs for predicting the prognosis and immune status of UCEC patients. The identified FFGs can accurately assess the prognosis of UCEC patients and facilitate the identification of specific subgroups of patients who may benefit from personalized treatment with immunotherapy and chemotherapy.

Regulatory network and targeted interventions for CCDC family in tumor pathogenesis

CCDC (coiled-coil domain-containing) is a coiled helix domain that exists in natural proteins. There are about 180 CCDC family genes, encoding proteins that are involved in intercellular transmembrane signal transduction and genetic signal transcription, among other functions. Alterations in expression, mutation, and DNA promoter methylation of CCDC family genes have been shown to be associated with the pathogenesis of many diseases, including primary ciliary dyskinesia, infertility, and tumors. In recent studies, CCDC family genes have been found to be involved in regulation of growth, invasion, metastasis, chemosensitivity, and other biological behaviors of malignant tumor cells in various cancer types, including nasopharyngeal carcinoma, lung cancer, colorectal cancer, and thyroid cancer. In this review, we summarize the involvement of CCDC family genes in tumor pathogenesis and the relevant upstream and downstream molecular mechanisms. In addition, we summarize the potential of CCDC family genes as tumor therapy targets. The findings discussed here help us to further understand the role and the therapeutic applications of CCDC family genes in tumors.

Comprehensive analysis of novel cancer prediction genes and tumor microenvironment infiltration in colon cancer

BACKGROUND

Colon cancer with high incidence and mortality is a severe public health problem. As an emerging therapy, immunotherapy has played an active clinical role in tumor treatment, but only a small number of patients respond.

METHODS

By univariate Cox regression analysis of 165 novel cancer prediction genes (NCPGs), 29 NCPGs related to prognosis were screened. Based on these 29 NCPGs and 336 differentially expressed genes, we constructed two colon cancer subgroups and three gene clusters and analyzed prognosis, activation pathways, and immune infiltration characteristics under various modification patterns. Then each patient was scored and divided into high or low NCPG_score groups. A comprehensive evaluation between NCPG_score and clinical characteristics, tumor microenvironment (TME), tumor somatic mutations, and the potential for immunotherapy was conducted.

RESULTS

Patients with high NCPG_score were characterized by high tumor mutation burden and high microsatellite instability and were more suitable for immunotherapy.

CONCLUSIONS

This study screened 29 NCPGs as independent prognostic markers in colon cancer patients, demonstrating their TME, clinicopathological features, and potential roles in immunotherapy, helping to assess prognosis and guiding more personalized immunotherapy.

The IgSF Cell Adhesion Protein CLMP and Congenital Short Bowel Syndrome (CSBS)

The immunoglobulin-like cell adhesion molecule CLMP is a member of the CAR family of cell adhesion proteins and is implicated in human congenital short-bowel syndrome (CSBS). CSBS is a rare but very severe disease for which no cure is currently available. In this review, we compare data from human CSBS patients and a mouse knockout model. These data indicate that CSBS is characterized by a defect in intestinal elongation during embryonic development and impaired peristalsis. The latter is driven by uncoordinated calcium signaling via gap junctions, which is linked to a reduction in connexin43 and 45 levels in the circumferential smooth muscle layer of the intestine. Furthermore, we discuss how mutations in the CLMP gene affect other organs and tissues, including the ureter. Here, the absence of CLMP produces a severe bilateral hydronephrosis-also caused by a reduced level of connexin43 and associated uncoordinated calcium signaling via gap junctions.

Risk scoring based on DNA methylation-driven related DEGs for colorectal cancer prognosis with systematic insights

Colorectal cancer is a common malignant tumor of the digestive tract. Despite advances in diagnostic techniques and medications. Its prognosis remains challenging. DNA methylation-driven related circulating tumor cells have attracted enormous interest in diagnosing owing to their non-invasive nature and early recognition properties. However, the mechanism through which risk biomarkers act remains elusive. Here, we designed a risk model based on differentially expressed genes, DNA methylation, robust, and survival-related factors in the framework of Cox regression. The model has satisfactory performance and is independently verified by an external and isolated dataset in terms of C-index value, ROC, and tROC. The model was applied to Colorectal cancer patients who were subsequently divided into high- and low-risk groups. Functional annotations, genomic alterations, tumor immune environment, and drug sensitivity were analyzed. We observed that up-regulated genes are associated with epithelial cell differentiation and MAPK signaling pathways. The down-regulated genes are related to IL-7 signaling and apoptosis-induced DNA fragmentation. Interestingly, the immune system was inhibited in high-risk groups. High-frequency mutation genes tend to co-occur. High-risk score patients are related to copy number amplification events. To address the challenges, we suggested eleven and twenty-one drugs that are sensitive to low- and high-risk patients. Finally, an artificial neural network was provided to evaluate the immunotherapeutic efficiency. Taken together, the findings demonstrated that our risk score model is robust and reliable for evaluating the prognosis with novel diagnostic and treatment targets. It also yields benefits for the treatment and provides unique insights into developing therapeutic strategies.

A Case of Complete Remission in Proficient Mismatch Repair (pMMR) Advanced Colon Cancer Treated with Sintilimab and XELOX

Introduction

Colorectal cancer (CRC) is the 3rd most common malignant tumors after breast cancer and lung cancer, accounting for 9.4% of patients. Some patients had distant metastasis at the time of diagnosis without surgery opportunity. It is particularly important to prolong patient survival and improve quality of life.

Patient Concerns

A 73-year-old female was admitted with discomfort over 2 months. Enlarged lymph nodes in the left supraclavicular fossa were observed in chest computed tomography (CT). Enhanced abdominal CT showed thickening of the right colon wall with multiple metastatic lymph nodes in the abdomen. Colonoscopy showed ileocecal mass and pathology showed moderately and poorly differentiated adenocarcinoma. Physical examination showed a 2*2 cm lymph node could be touched in the left supraclavicular fossa. The patient was diagnosed advanced colon cancer by the histopathological examination and imaging findings. Actually, it is hardly to resect radically.

Intervention

Sintilimab combined with XELOX was initiated. Two period of treatment after initial therapy, laparoscopic radical resection of right colon cancer was performed successfully.

Outcomes

After conversion treatment, the enlarged lymph nodes and primary tumor were significantly reduced. The patient was discharged successfully three weeks after surgery. Both specimen and 14 lymph nodes dissected showed no malignancy in pathology. Tumor regression grading (TRG) is 0, which indicate complete regression with no residual tumor cells including lymph nodes. The patient obtained a pathological complete response (pCR).

Lessons

The patient achieved a great therapeutic benefit with the above-mentioned chemotherapy in this case. The case provides a potential reference for pMMR CRC patients treating with immune checkpoint inhibitors (ICIs).

Deciphering the Role of Melatonin-Related Signatures in Tumor Immunity and the Prognosis of Clear Cell Renal Cell Carcinoma

Methods

Adopting multiomics data from TCGA and other public datasets, we analysed the expression, mutation, and prognostic evaluation in multiple cancers. ccRCC patients were categorized into two subgroups by an unsupervised cluster algorithm: melatonin-pattern cancer subtype 1 (MPCS1) and subtype 2 (MPCS2). We then explored the immune microenvironment, immune therapy response, and tumor metabolic pathways between the two subtypes. The clinical characteristics, genomic mutation landscape, and molecular inhibitor response were further investigated. Finally, a melatonin regulator-related prognostic model was constructed to predict patient prognosis in ccRCC.

Results

We found that melatonin regulators were dysregulated depending on distinct cancer types, which were associated with genomic variation. The two subtypes indicated different clinical characteristics and biological processes in ccRCC. MPCS2, an aggressive subtype, led an advanced clinical stage and poorer survival of ccRCC patients. The activated oncogenic signaling pathway and metabolic signatures were responsible for cancer progression in the MPCS2 subtype. The MPCS2 subgroup suggested a higher tumor mutational burden and immune dysfunction state, resulting in a lower response to immunotherapy. The copy number variations of MPCS2 were significantly more frequent than those of MPCS1. In addition, the two subgroups exhibited distinct drug responsiveness, with MPCS2 being less responsive to multiple drugs. Finally, we established a subtype biomarker-based prognostic risk model that exhibited satisfactory performance in ccRCC patients.

Conclusion

Melatonin regulator-related features could remodel functional pathways and the tumor immune microenvironment through genomic mutations and pathway regulation. Melatonin regulator-associated molecular subtypes enhance the understanding of the molecular characteristics of renal cancer and can guide clinical treatment. Activating the melatonergic system axis may improve the effect of immunotherapy for ccRCC.

Whole genome sequencing of Malaysian colorectal cancer patients reveals specific druggable somatic mutations

The incidences of colorectal cancer (CRC) are continuously increasing in some areas of the world, including Malaysia. In this study, we aimed to characterize the landscape of somatic mutations using the whole-genome sequencing approach and identify druggable somatic mutations specific to Malaysian patients. Whole-genome sequencing was performed on the genomic DNA obtained from 50 Malaysian CRC patients' tissues. We discovered the top significantly mutated genes were APC, TP53, KRAS, TCF7L2 and ACVR2A. Four novel, non-synonymous variants were identified in three genes, which were KDM4E, MUC16 and POTED. At least one druggable somatic alteration was identified in 88% of our patients. Among them were two frameshift mutations in RNF43 (G156fs and P192fs) predicted to have responsive effects against the Wnt pathway inhibitor. We found that the exogenous expression of this RNF43 mutation in CRC cells resulted in increased cell proliferation and sensitivity against LGK974 drug treatment and G1 cell cycle arrest. In conclusion, this study uncovered our local CRC patients' genomic landscape and druggable alterations. It also highlighted the role of specific RNF43 frameshift mutations, which unveil the potential of an alternative treatment targeting the Wnt/β-Catenin signalling pathway and could be beneficial, especially to Malaysian CRC patients.

HuR-dependent expression of Wisp1 is necessary for TGFβ-induced cardiac myofibroblast activity

Cardiac fibrosis is regulated by the activation and phenotypic switching of quiescent cardiac fibroblasts to active myofibroblasts, which have extracellular matrix (ECM) remodeling and contractile functions which play a central role in cardiac remodeling in response to injury. Here, we show that expression and activity of the RNA binding protein HuR is increased in cardiac fibroblasts upon transformation to an active myofibroblast. Pharmacological inhibition of HuR significantly blunts the TGFβ-dependent increase in ECM remodeling genes, total collagen secretion, in vitro scratch closure, and collagen gel contraction in isolated primary cardiac fibroblasts, suggesting a suppression of TGFβ-induced myofibroblast activation upon HuR inhibition. We identified twenty-four mRNA transcripts that were enriched for HuR binding following TGFβ treatment via photoactivatable ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP). Eleven of these HuR-bound mRNAs also showed significant co-expression correlation with HuR, αSMA, and periostin in primary fibroblasts isolated from the ischemic-zone of infarcted mouse hearts. Of these, WNT1-inducible signaling pathway protein-1 (Wisp1; Ccn4), was the most significantly associated with HuR expression in fibroblasts. Accordingly, we found Wisp1 expression to be increased in cardiac fibroblasts isolated from the ischemic-zone of mouse hearts following ischemia/reperfusion, and confirmed Wisp1 expression to be HuR-dependent in isolated fibroblasts. Finally, addition of exogenous recombinant Wisp1 partially rescued myofibroblast-induced collagen gel contraction following HuR inhibition, demonstrating that HuR-dependent Wisp1 expression plays a functional role in HuR-dependent MF activity downstream of TGFβ. In conclusion, HuR activity is necessary for the functional activation of primary cardiac fibroblasts in response to TGFβ, in part through post-transcriptional regulation of Wisp1.

Comprehensive Multiomic Analysis Identified TUBA1C as a Potential Prognostic Biological Marker of Immune-Related Therapy in Pan-Cancer

TUBA1C is correlated with an unfavourable prognosis and the infiltration of immune cells in several cancers. However, its function as a significant biomarker for the prognosis of immunotherapy in pan-cancer remains unclear. This study aims at assessing the role of TUBA1C in pan-cancer at multiple levels, including mutations, gene expression, methylation, m6A methylation, and immune cell infiltration levels. Data retrieved from major public databases, such as TCGA, GEO, GTEx, GSCA, CancerSEA, HPA, and RNAactDrugs, revealed that TUBA1C expression was high in 33 cancer types. Survival analysis revealed that TUBA1C was a poor prognostic factor for 12 tumour types, and mutations, CNVs, and methylation affected the prognosis of some cancer types. Furthermore, TUBA1C was found to be related to immune-related genes, immune cell infiltration, and the immune microenvironment. In addition, the sensitivity of 10 anticancer drugs was associated with high TUBA1C expression. Therefore, TUBA1C may serve as a viable prognostic biomarker for immunotherapy of pan-cancer.

Identification of Specific Cervical Cancer Subtypes and Prognostic Gene Sets in Tumor and Nontumor Tissues Based on GSVA Analysis

Background

Cervical cancer is the fourth common cancer among women. Its prognosis needs our more attention. Our purpose was to identity new prognostic gene sets to help other researchers develop more effective treatment for cervical cancer patients and improve the prognosis of patients.

Methods

We used gene set variation analysis (GSVA) to calculate the enrichment scores of gene sets and identified three subtypes of cervical cancer through the Cox regression model, k-means clustering algorithm, and nonnegative matrix factorization method (NMF). Chi-square test was utilized to test whether a certain clinical characteristic is different among divided subtypes. We further screened the prognostic gene sets using differential analysis, univariate Cox regression analysis, and least absolute shrinkage and selection operator (LASSO) regression. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to analyze which pathways and function the genes from screened gene sets enriched. Search Tool for the Retrieval of Interacting Genes (STRING) was used to draw the protein-protein interaction network, and Cytoscape was used to visualize the hub genes of protein-protein interaction network.

Results

We identified three novel subtypes of cervical cancer in The Cancer Genome Atlas (TCGA) samples and validated in Gene Expression Omnibus (GEO) samples. There were significant variations between the three subtypes in histological type, T stage, M stage, and N stage. T_GSE36888_UNTREATED_VS_IL2_TREATED_STAT5_AB_KNOCKIN_TCELL_2H_UP and N_HALLMARK_ANGIOGENESIS were screened prognostic gene sets. The prognostic model was as follows: riskScore = T_GSE36888_UNTREATED_VS_IL2_TREATED_STAT5_AB_KNOCKIN_TCELL_2H_UP^∗ 2.617 + N_HALLMARK_ANGIOGENESIS^∗ 4.860. Survival analysis presented that in these two gene sets, high enrichment scores were all significantly related to worse overall survival. The hub genes from T gene set included CXCL1, CXCL2, CXCL8, ALDOA, TALDO1, LDHA, CCL4, FCAR, FCER1G, SAMSN1, LILRB1, SH3PXD2B, PPM1N, PKM, and FKBP4. As for N gene sets, the hub genes included ITGAV, PTK2, SPP1, THBD, and APOH.

Conclusions

Three novel subtypes and two prognostic gene sets were identified. 15 hub genes for T gene set and 5 hub genes for N gene set were discovered. Based on these findings, we can develop more and more effective treatments for cervical cancer patients. Based on the gene enriched pathways, we can development specific drugs targeting the pathways.

Leader gene identification for digestive system cancers based on human subcellular location and cancer-related characteristics in protein-protein interaction networks

Stomach, liver, and colon cancers are the most common digestive system cancers leading to mortality. Cancer leader genes were identified in the current study as the genes that contribute to tumor initiation and could shed light on the molecular mechanisms in tumorigenesis. An integrated procedure was proposed to identify cancer leader genes based on subcellular location information and cancer-related characteristics considering the effects of nodes on their neighbors in human protein-protein interaction networks. A total of 69, 43, and 64 leader genes were identified for stomach, liver, and colon cancers, respectively. Furthermore, literature reviews and experimental data including protein expression levels and independent datasets from other databases all verified their association with corresponding cancer types. These final leader genes were expected to be used as diagnostic biomarkers and targets for new treatment strategies. The procedure for identifying cancer leader genes could be expanded to open up a window into the mechanisms, early diagnosis, and treatment of other cancer types.

The potential value of cuprotosis (copper-induced cell death) in the therapy of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for 75% of the total incidence of renal cancer, and every year the number of morbidity and mortality increases, posing a serious threat to public health. The current main treatment methods for kidney cancer include drug-targeted therapy and immunotherapy. Although there are many treatment options for kidney cancer, they all have limitations, including drug resistance, unsatisfied long-term benefits, and adverse effects. Therefore, it is crucial to identify more effective therapeutic targets. As a newly discovered mechanism of cell death, copper-induced cell death (cuprotosis) is closely related to changes in cell metabolism, particularly in copper metabolism. Current studies have shown that the key signaling pathway of cuprotosis, the FDX1 (Ferredoxin 1)-LIAS (Lipoic Acid Synthetase) axis, plays an important role in the regulation of cellular oxidative stress, which can directly affect cell survival via inducing or promoting cancer cell death. Therefore, we speculated that this regulatory cell death mechanism might serve as a potential therapeutic target for the clinical treatment of renal cancer. To test this, we first performed a pan-cancer analysis based on cuprotosis-related genomic and transcriptomic levels to reveal the expression of cuprotosis in cancer. Next, GSVA-clustering analysis was performed with data from the Cancer Genome Atlas (TCGA) cohort, and the cohort was divided into three clusters according to the gene enrichment levels of cuprotosis marker genes. In addition, we analyzed the potential of using cuprotosis in clinical treatment from multiple perspectives, including chemotherapeutic drug susceptibility test, immune target inhibition treatment responsiveness, and histone modification. Combining the results of multi-omics analysis, we focused on the feasibility of this novel regulatory cell death mechanism in ccRCC treatment and further constructed a prognostic model. Finally, we verified our results by integrating the patient's gene expression information and radiomics information. Our study provides new insights into the development and clinical application of targeting cuprotosis pathway.

New Potential Immune Biomarkers in the Era of Precision Medicine: Lights and Shadows in Colorectal Cancer

Genetic alterations in CRC have shown a negative predictive and prognostic role in specific target therapies. The onset of immunotherapy has also undergone remarkable therapeutic innovation, although limited to a small subgroup of patients, the MSI-H/dMMR, which represents only 5% of CRC. Research is moving forward to identify whether other biomarkers can predict response to ICIs, despite various limitations regarding expression and identification methods. For this purpose, TMB, LAG3, and PD-L1 expression have been retrospectively evaluated in several solid tumors establishing the rationale to design clinical trials with concurrent inhibition of LAG3 and PD-1 results in a significant advantage in PFS and OS in advanced melanoma patients. Based on these data, there are clinical trials ongoing in the CRC as well. This review aims to highlight what is already known about genetic mutations and genomic alterations in CRC, their inhibition with targeted therapies and immune checkpoints inhibitors, and new findings useful to future treatment strategies.

[MUC16: The Novel Target for Tumor Therapy]

Mucin16 (MUC16), also known as carbohydrate antigen 125 (CA125), is a glycoprotein antigen that can be recognized by the monoclonal antibody OC125 detected from epithelial ovarian carcinoma antigen by Bast et al in 1981. CA125 is not present in normal ovarian tissue but is usually elevated in the serum of epithelial ovarian carcinoma patients. CA125 is the most commonly used serologic biomarker for the diagnosis and recurrence monitoring of epithelial ovarian carcinoma. MUC16 is highly expressed in varieties of tumors. MUC16 can interact with galectin-1/3, mesothelin, sialic acid-binding immunoglobulin-type lectins-9 (Siglec-9), and other ligands. MUC16 plays an important role in tumor genesis, proliferation, migration, invasion, and tumor immunity through various signaling pathways. Besides, therapies targeting MUC16 have some significant achievements. Related preclinical studies and clinical trials are in progress. MUC16 may be a potential novel target for tumor therapy. This article will review the mechanism of MUC16 in tumor genesis and progression, and focus on the research actuality of MUC16 in tumor therapy. This article also provides references for subsequent tumor therapy studies targeting MUC16.
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Construction and validation of an immune-related LncRNA prognostic model for hepatocellular carcinoma

Herein, based on mRNA data from TCGA database, hepatocellular carcinoma (HCC) samples were subjected to a single-sample Gene Set Enrichment Analysis (ssGSEA). Then, HCC samples were finally classified into high-, middle-, and low-immunity groups using K-means consensus clustering (K = 3) according to ssGSEA scores. After the tumor microenvironment of HCC patients was further analyzed using ESTIMATE algorithm, the results indicated high immune score, stromal score, ESTIMATE score and low tumor purity in high-immunity group. HLA family genes and PD-L1(CD274) were remarkably highly expressed in high-immunity group. Immune-related lncRNAs were required by analyzing differentially expressed genes in high- and low-immunity groups. Differential expression analysis was undertaken on HCC samples, with normal samples as the control. After immune-related lncRNAs and differentially expressed lncRNAs were intersected, 321 differentially expressed immune-related lncRNAs were acquired. Later, the prognostic model based on immune-related lncRNAs was obtained following the Cox regression analysis of previous samples. According to the riskScore, the samples in TCGA-LIHC were divided into high- and low-risk groups. Kaplan-Meier survival analysis, ROC curve, and independence analysis confirmed that the immune-related lncRNAs prognostic model was an important factor independent from clinical characteristics. We further analyzed the difference in immune microenvironment and mutational landscapes in both risk groups. Prominent differences were shown in multiple immunity-related gene sets and immune cells in both groups. The mutation rate of TP53 in high-risk group was much higher than the low-risk one. All these conclusions offered references to prognostic evaluations and personalized treatments for patients with HCC.

N6-methyladenosine methylation modification patterns reveal immune profiling in pancreatic adenocarcinoma

BACKGROUND

Several studies have revealed that N6-methyladenosine (m6A) regulation is involved in various biological processes and cancer progression. Nevertheless, the potential effects of m6A modifications in the tumor immune microenvironment (TIME) and on immune regulation in pancreatic adenocarcinoma (PAAD) remains unclear.

METHODS

A consensus clustering algorithm was used to identify different m6A modification patterns and construct an m6A-associated gene signature based on 23 m6A regulators in PAAD. The CIBERSORT and ssGSEA algorithms were used to estimate the components of the immune cells in each sample. The PCA algorithm was used to develop the m6Ascore system for the evaluation of m6A modification patterns in each sample.

RESULTS

Two m6A modification patterns with different biological properties and prognoses were identified in 176 PAAD patient samples. The features of TIME between the two patterns were similar, with two definite immune phenotypes: immune-inflamed and immune-excluded. Based on the m6A phenotype-associated signature genes, we constructed an m6Ascore system to investigate the m6A modification pattern of each sample, profile the dissection of physiological processes, immune infiltration, clinical prognosis, immunotherapy, and genetic variation. Patients with low m6Ascore scores had better clinical outcomes, enhanced immune infiltration, and lower expression of immunotherapeutic drug targets, such as CD274 and PDCD1LG2. Further research indicated that the m6Ascore and tumor mutation burden were significantly correlated, and patients with low m6Ascore had higher mutation rates in SMAD4 and TTN. Moreover, TNFRSF21 was significantly upregulated in PAAD tumor tissues and cell lines. Lower expression of TNFRSF21 had a prominent advantage in survival and was correlated with a low level of immune infiltration. PAAD samples with different TNFRSF21 expression levels showed significantly distinct sensitivities to chemotherapeutic agents.

CONCLUSIONS

This study revealed that m6A modification patterns could play an important role in the diversity and complexity of TIME, and the m6Ascore system could serve as an independent and powerful prognostic biomarker and is latently related to PAAD immunotherapies. Quantitative determination of m6A modification patterns in individual patients will be instrumental in mapping the TIME landscape and further optimizing precision immunotherapy.

NIBAN1, Exploring its Roles in Cell Survival Under Stress Context

Cell survival must quickly activate specific mechanisms that enable to detect changes in the cellular microenvironment. The impact of these cell alteration has direct consequences on cellular homeostasis. Cellular stress, as well as its regulation and implication, has been studied in different pathologies. In this sense, the alteration in NIBAN1 expression seems to act in response to different cellular disturbances. Over the years, the knowledge of NIBAN1 functions has improved, demonstrating its important cell roles, favoring the cell survival under stress context. In response to the disturbances, NIBAN1 seems to be involved in the decision-making process between cell survival and death. The increase in NIBAN1 expression has been related to cellular mechanisms that seek to minimize the damage caused to cellular homeostasis. In this review, the main biological insights attributed to the NIBAN1 gene in different cellular contexts and its role as a mediator of cellular stress are discussed.

Identification of Potential Biomarkers for Progression and Prognosis of Bladder Cancer by Comprehensive Bioinformatics Analysis

Background. Bladder cancer (BLCA) is a highly malignant tumor that develops in the urinary system. Identification of biomarkers in progression and prognosis is crucial for the treatment of BLCA. BLCA-related differentially expressed genes (DEGs) were authenticated by screening the DEGs and weighted gene coexpression network analysis (WGCNA). LASSO and SVM-RFE algorithms were utilized to screen the feature genes in BLCA. Survival analysis was performed using the Kaplan–Meier curve provided by the ‘survival' R package. The BLCA samples were clustered by hclust based on the immune score matrix calculated by the single-sample GSEA (ssGSEA) algorithm. The immune, stromal, and ESTIMATE scores of each BLCA patient were calculated by applying the ESTIMATE algorithm. ssGSEA was conducted to explore the function of characteristic genes in BLCA. The expression of characteristic genes in clinical cancer tissue, and the pericancerous tissue of BLCA patients was verified using qRT-PCR assays. A total of 189 BLCA-related DEGs were identified. Fourteen feature genes were defined by LASSO and SVM-RFE algorithms. Five characteristic genes, including SMYD2, GAPDHP1, ATP1A2, CILP, and THSD4, were related to the OS of BLCA. The correlation analysis of five characteristic genes and clinicopathological factors showed that five genes played a role in the progression of BLCA. Additionally, the expression of five characteristic genes in clinical cancer tissues and pericarcinomatous tissues from BLCA patients was verified by qRT-PCR, which was consistent with the result from the public database. Finally, we discovered five prognostic genes linked to BLCA progression, which might serve as a theoretical basis for prognosis and treatment targets for BLCA patients.

The Comparable Microenvironment Shared by Colorectal Adenoma and Carcinoma: An Evidence of Stromal Proteomics

Tumor microenvironment (TME) is a key factor involved in cancer development and metastasis. In the TME of colorectal cancer (CRC), the gene expression status of stromal tissues could influence the CRC process from normal to adenoma then carcinoma; however, the expression status at the protein level has not yet been well evaluated. A total of 22 CRC patients were recruited for this study, and the tissue regions corresponding with adjacent, adenoma, and carcinoma were carefully excised by laser capture microdissection (LCM), including a patient with adenoma and carcinoma. The individual proteomes of this cohort were implemented by high-resolution mass spectrometer under data-independent acquisition (DIA) mode. A series of informatic analysis was employed to statistically seek the proteomic characteristics related with the stroma at different stages of CRC. The identified proteins in the colorectal stromal tissues were much less than and almost overlapped with that in the corresponding epithelial tissues; however, the patterns of protein abundance in the stroma were very distinct from those in the epithelium. Although qualitative and quantitative analysis delineated the epithelial proteins specifically typified in the adjacent, adenoma, and carcinoma, the informatics in the stroma led to another deduction that such proteomes were only divided into two patterns, adjacent- and adenoma/carcinoma-dependent. The comparable proteomes of colorectal adenoma and carcinoma were further confirmed by the bulk preparation- or individual LCM-proteomics. The biochemical features of the tumor stromal proteomes were characterized as enrichment of CD4+ and CD8+ T cells, upregulated pathways of antigen presentation, and enhancement of immune signal interactions. Finally, the features of lymphoid lineages in tumor stroma were verified by tissue microarray (TMA). Based on the proteomic evidence, a hypothesis was raised that in the colorectal tissue, the TME of adenoma and carcinoma were comparable, whereas the key elements driving an epithelium from benign to malignant were likely decided by the changes of genomic mutations or/and expression within it.

TCGA database analysis of the tumor mutation burden and its clinical significance in colon cancer

Background

Colon cancer is one of the most common malignant tumors, with high rates of incidence and death. The tumor mutational burden (TMB), which is characterized by microsatellite instability, has been becoming a powerful predictor which can show tumor behavior and response to immunotherapy.

Methods

In this study, we analyzed 437 mutation data of colon cancer samples obtained from The Cancer Genome Atlas (TCGA) and divided patients into low- and high-TMB groups according to the TMB value. Then we identified differentially-expressed genes (DEGs), conducted immune cell infiltration and survival analyses between groups.

Results

The higher TMB of the patients with colon cancer predicts a poorer prognosis. Functional analysis was performed to assess the prognostic value of the top 30 core genes. The CIBER-SORT algorithm was used to investigate the correlation between the immune cells and TMB subtypes. An immune prognosis model was constructed to screen out immune genes related to prognosis, and the tumor immunity assessment resource (TIMER) was then used to determine the correlation between gene expression and the abundance of tumor-infiltrating immune cell subsets in colon cancer. We observed that APC, TP53, TTN, KRAS, MUC16, SYNE1, PIK3CA have higher somatic mutations. DEGs enrichment analysis showed that they are involved in the regulation of neuroactive ligand-receptor interaction, the Cyclic adenosine monophosphate (cAMP) signaling pathway, the calcium signaling pathway, and pantothenate and Coenzyme A (CoA) biosynthesis. The difference in the abundance of various white blood cell subtypes showed that Cluster of Differentiation 8 (CD8) T cells (P=0.008), activated CD4 memory T cells (P=0.019), M1 macrophages (P=0.002), follicular helper T cells (P=0.034), activated Natural killer (NK cell) cells (P=0.017) increased remarkably, while M0 macrophages significantly reduced (P=0.025). The two immune model genes showed that secretin (SCT) was negatively correlated with survival, while Guanylate cyclase activator 2A (GUCA2A) was positively correlated.

Conclusions

This study conducted a systematically comprehensive analysis of the prediction and clinical significance of TMB in colon cancer in identification, monitoring, and prognosis of colon cancer, and providing reference information for immunotherapy.

Recognition of DNA Methylation Molecular Features for Diagnosis and Prognosis in Gastric Cancer

Background: The management of gastric cancer (GC) still lacks tumor markers with high specificity and sensitivity. The goal of current research is to find effective diagnostic and prognostic markers and to clarify their related mechanisms.

Methods: In this study, we integrated GC DNA methylation data from publicly available datasets obtained from TCGA and GEO databases, and applied random forest and LASSO analysis methods to screen reliable differential methylation sites (DMSs) for GC diagnosis. We constructed a diagnostic model of GC by logistic analysis and conducted verification and clinical correlation analysis. We screened credible prognostic DMSs through univariate Cox and LASSO analyses and verified a prognostic model of GC by multivariate Cox analysis. Independent prognostic and biological function analyses were performed for the prognostic risk score. We performed TP53 correlation analysis, mutation and prognosis analysis on eleven-DNA methylation driver gene (DMG), and constructed a multifactor regulatory network of key genes.

Results: The five-DMS diagnostic model distinguished GC from normal samples, and diagnostic risk value was significantly correlated with grade and tumor location. The prediction accuracy of the eleven-DMS prognostic model was verified in both the training and validation datasets, indicating its certain potential for GC survival prediction. The survival rate of the high-risk group was significantly lower than that of the low-risk group. The prognostic risk score was an independent risk factor for the prognosis of GC, which was significantly correlated with N stage and tumor location, positively correlated with the VIM gene, and negatively correlated with the CDH1 gene. The expression of CHRNB2 decreased significantly in the TP53 mutation group of gastric cancer patients, and there were significant differences in CCDC69, RASSF2, CHRNB2, ARMC9, and RPN1 between the TP53 mutation group and the TP53 non-mutation group of gastric cancer patients. In addition, CEP290, UBXN8, KDM4A, RPN1 had high frequency mutations and the function of eleven-DMG mutation related genes in GC patients is widely enriched in multiple pathways.

Conclusion: Combined, the five-DMS diagnostic and eleven-DMS prognostic GC models are important tools for accurate and individualized treatment. The study provides direction for exploring potential markers of GC.

Identification and validation of a novel zinc finger protein-related gene-based prognostic model for breast cancer

Background

Breast invasive carcinoma (BRCA) is a commonly occurring malignant tumor. Zinc finger proteins (ZNFs) constitute the largest transcription factor family in the human genome and play a mechanistic role in many cancers' development. The prognostic value of ZNFs has yet to be approached systematically for BRCA.

Methods

We analyzed the data of a training set from The Cancer Genome Atlas (TCGA) database and two validation cohort from GSE20685 and METABRIC datasets, composed of 3,231 BRCA patients. After screening the differentially expressed ZNFs, univariate Cox regression, LASSO, and multiple Cox regression analysis were performed to construct a risk-based predictive model. ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and gene set enrichment analyses (GSEA) were utilized to assess the potential relations among the tumor immune microenvironment and ZNFs in BRCA.

Results

In this study, we profiled ZNF expression in TCGA based BRCA cohort and developed a novel prognostic model based on 14 genes with ZNF relations. This model was composed of high and low-score groups for BRCA classification. Based upon Kaplan-Meier survival curves, risk-status-based prognosis illustrated significant differences. We integrated the 14 ZNF-gene signature with patient clinicopathological data for nomogram construction with accurate 1-, 3-, and 5-overall survival predictive capabilities. We then accessed the Genomics of Drug Sensitivity in Cancer database for therapeutic drug response prediction of signature-defined BRCA patient groupings for our selected TCGA population. The signature also predicts sensitivity to chemotherapeutic and molecular-targeted agents in high- and low-risk patients afflicted with BRCA. Functional analysis suggested JAK STAT, VEGF, MAPK, NOTCH TOLL-like receptor, NOD-like receptor signaling pathways, apoptosis, and cancer-based pathways could be key for ZNF-related BRCA development. Interestingly, based on the results of ESTIMATE, ssGSEA, and GSEA analysis, we elucidated that our ZNF-gene signature had pivotal regulatory effects on the tumor immune microenvironment for BRCA.

Conclusion

Our findings shed light on the potential contribution of ZNFs to the pathogenesis of BRCA and may inform clinical practice to guide individualized treatment.

Comprehensive Analysis of the Prognostic Value and Immune Infiltrates of the Three-m5C Signature in Colon Carcinoma

Background

The 5-methylcytosine (m5C) is one of the important forms of RNA post modification, and its regulatory mechanism in tumors has received increasing attention. However, its potential role in colorectal cancer remains unclear.

Materials and Methods

Here, we systematically investigated the genetic variation and prognostic value of the 14 m5c RNA methylation regulators in colon cancer. The prognostic risk score was constructed using three m5C regulators, which was verified in the GSE17536 (N=177), GSE41258 (N=248) and GSE38832 (N=122) datasets.

Results

The risk score developed from the three-m5C signature represents an independent prognostic factor, which can accurately predict the prognosis of patients with colon cancer in multiple datasets. The cytokine–cytokine receptor interaction and chemokine signaling pathway were significantly enriched in the low-risk score group. Further analysis showed that the three-m5C signature was related to tumor immune microenvironment (TIME), affecting the abundance of tumor-infiltrating immune cells. Especially, patients with low risk score had higher immune score than those with high risk score. In addition, gene set enrichment analysis (GSEA) confirmed that all three regulatory factors are associated with the MAPK/p38 signaling pathway.

Conclusion

In conclusion, our study illustrates that the three-m5C signature may be involved in the regulation of colon cancer immune microenvironment in synergy with the MAPK signaling pathway. Therefore, further studying the three-m5C signature regulatory mechanisms might provide promising targets for improving the responsiveness of colon cancer to immunotherapy.

Network analysis identifies DAPK3 as a potential biomarker for lymphatic invasion and colon adenocarcinoma prognosis

Colon adenocarcinoma is a prevalent malignancy with significant mortality. Hence, the identification of molecular biomarkers with prognostic significance is important for improved treatment and patient outcomes. Clinical traits and RNA-Seq of 551 patient samples in the UCSC Toil Recompute Compendium of The Cancer Genome Atlas TARGET and Genotype Tissue Expression project datasets (primary_site = colon) were used for weighted gene co-expression network analysis to reveal the association between gene networks and cancer cell invasion. One module, containing 151 genes, was significantly correlated with lymphatic invasion, a histopathological feature of higher risk colon cancer. DAPK3 (death-associated protein kinase 3) was identified as the pseudohub of the module. Gene ontology identified gene enrichment related to cytoskeletal organization and apoptotic signaling processes, suggesting modular involvement in tumor cell survival, migration, and epithelial-mesenchymal transformation. Although DAPK3 expression was reduced in patients with colon cancer, high expression of DAPK3 was significantly correlated with greater lymphatic invasion and poor overall survival.

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WCGNA reveals a gene module linked to lymphatic invasion in colon adenocarcinoma

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DAPK3 is a pseudohub gene with differential expression in colon cancer

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Gene ontology identified relationships to cytoskeletal organization and apoptosis

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DAPK3 was correlated with lymphatic invasion and poor overall survival

Identification of two immune subtypes in osteosarcoma based on immune gene sets

Osteosarcoma (OS) is a highly aggressive cancer with poor prognosis, which mainly occurs in teenagers. Recent studies have shown that tumor-infiltrating immune cells play an important role in the progression of OS. In the present study, we identified two immune subtypes of OS (referred to as high and low immune cell infiltration subtypes, respectively) based on immune-related gene sets using TARGET and GEO cohort datasets. Elevated immune scores, increased stromal scores, decreased tumor purities, and higher infiltration of CD8 + T cells and M1 macrophages were observed for the high immune cell infiltration subtype. Moreover, the high immune cell infiltration subtype was characterized by high expression of immune checkpoint molecules. Gene set enrichment analysis showed that "B cell receptor signaling pathway" and "T cell receptor signaling pathway" gene sets were enriched in the high immune cell infiltration subtype. In addition, patients in the high immune cell infiltration subtype had better prognosis than patients in the low immune cell infiltration subtype. Furthermore, differentially expressed genes were screened according to the two OS subtypes and a risk model was generated by multivariate Cox regression analysis to predict the prognosis of OS patients. These results in this study showed that OS patients could be divided into two immune subtypes and offered a novel two-gene risk signature to predict the prognosis of patients with OS.