Pan-cancer RNA-seq data stratifies tumours by some hallmarks of cancer

SCGB1A1 as a novel biomarker and promising therapeutic target for the management of HNSCC

Head and neck cancer (HNC) is the sixth most common type of cancer worldwide, and head and neck squamous cell carcinoma (HNSCC) accounts for 90% of HNC cases. Furthermore, HNSCC accounts for 400,000 cancer-associated deaths worldwide each year. However, at present there is an absence of a versatile biomarker that can be used for diagnosis, prognosis evaluation and as a therapeutic target for HNSCC. In the present study, bioinformatics analysis was used to assess the relationship between hub genes and the clinical features of patients with HNSCC. The findings from the bioinformatics analysis were then verified using clinical samples and in vitro experiments. A total of 51 overlapping genes were identified from the intersection of differentially expressed genes and co-expressed genes. The top 10 hub genes were obtained from a protein-protein interaction network of overlapping genes. Among the hub genes, only secretoglobin family 1A member 1 (SCGB1A1) was significantly associated with both overall and disease-free survival. Specifically, upregulated SCGB1A1 expression levels were associated with prolonged overall and disease-free survival. Moreover, the SCGB1A1 expression levels were negatively correlated with drug sensitivity. Notably, it was demonstrated that SCGB1A1 was involved in tumor immunoreaction by affecting the infiltration of cells and checkpoint regulation of immune cells. Additionally, it was shown that SCGB1A1 regulated multiple key cancer-related signaling pathways, including extracellular matrix receptor interaction, transforming growth factor-β and tumor metabolism signaling pathways. Based on the results of the present study, SCGB1A1 may serve as a novel biomarker for predicting the diagnosis, prognosis and therapeutic effectiveness of certain drugs in patients with HNSCC. Moreover, SCGB1A1 may serve as a potential therapeutic target for the management of HNSCC.

TPD52 is a Potential Prognostic Biomarker and Correlated with Immune Infiltration: A Pan-cancer Analysis

BACKGROUND

Some tumors have a poor prognosis regarding TPD52 (tumor protein D52). This study aims to explore TPD52's role in the cancer process from a pan-cancer perspective.

METHODS

A pan-cancer analysis was conducted to investigate how TPD52 may be involved in cancer as well as its association with prognosis.

RESULTS

A variety of human cancers express TPD52 abnormally and correlate with clinical stage. There was a significant association between low expression of TPD52 and poor survival in BRCA, KIRP, LAML, LIHC, UCEC, and UVM. TPD52 alterations were most frequently amplified in pan-cancer. The co-occurrence of 10 genes alterations was found in the TPD52 altered group. There was a significant association between TPD52 expression and MSI in four cancer types and TMB in twelve cancer types. There was a significant correlation between TPD52 expression and immunerelated cell infiltration. A significant correlation was found between TPD52 expression in many tumor types and 8 immune checkpoint genes. There were signaling pathways involved in pan-cancer caused by TPD52, including endocytosis, Fc gamma Rmediated phagocytosis, and so on. TPD52 may be involved in chemotherapy and chemoresistance.

CONCLUSION

The TPD52 gene may be important for human cancer treatment.

Comprehensive analysis of TLX2 in pan cancer as a prognostic and immunologic biomarker and validation in ovarian cancer

T cell leukemia homeobox 2 (TLX2) plays an important role in some tumors. Bioinformatics and experimental validation represent a useful way to explore the mechanisms and functions of TLX2 gene in the cancer disease process from a pan cancer perspective. TLX2 was aberrantly expressed in pan cancer and cell lines and correlated with clinical stage. High TLX2 expression was significantly associated with poor overall survival in COAD, KIRC, OC, and UCS. The greatest frequency of TLX2 alterations in pan cancer was amplification. Alterations of NXF2B, MSLNL, PCGF1, INO80B-WBP1, LBX2-AS1, MRPL53, LBX2, TTC31, WDR54, and WBP1 co-occurred in the TLX2 alteration group. PFS was significantly shorter in the TLX2-altered group (n = 6) compared to the TLX2-unaltered group (n = 400). Methylation levels of TLX2 were high in 17 tumors. TLX2 expression was associated with MSI in seven tumors and TMB in five tumors. TLX2 expression was associated with immune infiltration and immune checkpoint genes. TLX2 may be associated with some pathways and chemoresistance. We constructed a possible competing endogenous RNA (ceRNA) network of LINC01010/miR-146a-5p/TLX2 in OC. TLX2 expression was significantly upregulated in ovarian cancer cell lines compared to ovarian epithelial cell lines. Aberrant expression of TLX2 in pan cancer may promote tumorigenesis and progression through different mechanisms. TLX2 may represent an important therapeutic target for human cancers.

Promoting proliferation and tumorigenesis of breast cancer: KCND2's significance as a prognostic factor

In recent years, the potassium voltage-gated channel subfamily D (KCND) channels, particularly KCND2 (also known as Kv4.2), have been suggested to play a role in a variety of cancers, but their role in breast cancer has not yet been revealed. We analyzed RNA sequencing data from The Cancer Genome Atlas database and the Genotype-Tissue Expression database to investigate the differential expression of KCND2 in breast cancer and normal breast tissue. In addition, we leveraged GO and KEGG analysis techniques to gain a better understanding of the potential functional enrichment of 500 genes related to KCND2. Our findings were validated using collected tissue samples and clinical data from hospitals showed that KCND2 is a crucial independent factor in the prognosis of breast cancer patients. The higher the expression of KCND2, the shorter the survival time of breast cancer patients. Colony formation assay confirmed that KCND2 promotes the proliferation of breast cancer cells, whereas transwell assay and wound healing assay verified that KCND2 promoted breast cancer invasion and migration. In addition, 5-Ethynyl-2'-deoxyuridine (EdU) and flow cytometry revealed that KCND2 affected the cycle changes of breast cancer cells and contributed to the G1/S phase transition of breast cancer cells. Overall, our study demonstrates that KCND2 holds a promising potential as a significant target for breast cancer diagnosis and therapy.

MESP1-knockdown inhibits the proliferation and epithelial mesenchymal transition of hepatocellular carcinoma and enhances the tumor-suppressive effect of 5-fluorouracil

Primary liver hepatocellular carcinoma (HCC) is the third most deadly malignancy worldwide,in part, because it is often diagnosed at an advanced stage. Thus, molecular markers are needed to aid in the early diagnosis and treatment of HCC. Expression of abnormal mesoderm posterior-1 (MESP1) promotes tumorigenesis; however,its role in the regulation of HCC proliferation, apoptosis,and invasion is unknown. Here,we analyzed data in The Cancer Genome Atlas (TCGA)and Genotype Tissue Expression (GTEx) databases on the pan-cancer expression of MESP1 and its relationship with clinical characteristics and prognosis of patients with HCC. The expression of MESP1 was measured in 48 HCC tissues using immunohistochemical staining,and the results were correlated with clinical stage, tumor differentiation, tumor size,and metastasis. MESP1 expression was downregulated using small interfering RNA (siRNA) in the HCC cell lines HepG2 and Hep3B,and cell viability, proliferation,cell cycle, apoptosis,and invasion were analyzed. Finally,we also evaluated the tumor suppression effect of MESP1 downregulation combined with 5-fluorouracil (5-FU) treatment. Our results showed that MESP1 is a pan-oncogene associated with poor prognosis in patients with HCC. siRNA-induced downregulation of MESP1 expression in HepG2 and Hep3B cells exhibited downregulation of β-catenin and GSK3β expression 48h after transfection, along with an increase in apoptosis rate, arrest in the G1-S phase,and a decrease in mitochondrial membrane potential. Moreover,the expression levels of c-Myc, PARP1, bcl2, Snail1, MMP9, and immune checkpoint genes (TIGIT, CTLA4,LAG3,CD274,and PDCD1) were downregulated, while those of caspase3 and E-cadherin were upregulated. Tumor cells also showed decreased migration ability. Furthermore, siRNA interference of MESP1 expression combined with 5-FU-treatment of HCC cells significantly enhanced the G1-S phase block and apoptosis. MESP1 showed an aberrant high expression in HCC and was associated with poor clinical outcomes; therefore, MESP1 may be a potential target for the diagnosis and treatment of HCC.

A model based on immune-related lncRNA pairs and its potential prognostic value in immunotherapy for melanoma

A model based on long non-coding RNA (lncRNA) pairs independent of expression quantification was constructed to evaluate prognosis melanoma and response to immunotherapy in melanoma. RNA sequencing data and clinical information were retrieved and downloaded from The Cancer Genome Atlas and the Genotype-Tissue Expression databases. We identified differentially expressed immune-related lncRNAs (DEirlncRNAs), matched them, and used least absolute shrinkage and selection operator and Cox regression to construct predictive models. The optimal cutoff value of the model was determined using a receiver operating characteristic curve and used to categorize melanoma cases into high-risk and low-risk groups. The predictive efficacy of the model with respect to prognosis was compared with that of clinical data and ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data). Then, we analyzed the correlations of risk score with clinical characteristics, immune cell invasion, anti-tumor, and tumor-promoting activities. Differences in survival, degree of immune cell infiltration, and intensity of anti-tumor and tumor-promoting activities were also evaluated in the high- and low-risk groups. A model based on 21 DEirlncRNA pairs was established. Compared with ESTIMATE score and clinical data, this model could better predict outcomes of melanoma patients. Follow-up analysis of the model's effectiveness showed that patients in the high-risk group had poorer prognosis and were less likely to benefit from immunotherapy compared with those in the low-risk group. Moreover, there were differences in tumor-infiltrating immune cells between the high-risk and low-risk groups. By pairing the DEirlncRNA, we constructed a model to evaluate the prognosis of cutaneous melanoma independent of a specific level of lncRNA expression.

Landscape of costimulatory molecule signature in breast cancer and its prognostic significance

Background

Breast cancer (BRCA) is the most common malignant tumor in the world. Because of its substantial heterogeneity, its clinical treatment is faced with various problems. Only a small number of patients can benefit from the treatment of immune checkpoint inhibitor (ICI). Costimulatory molecule signature (CMS) plays an essential role in T cell activation and antitumor immune response. Previous studies found that CMS is associated with prognosis-related immune response markers, suggesting that CMS may be a potential therapeutic target. However, the research on their function in BRCA subtype is still inadequate. Our study aims to analyze CMS in BRCA and establish an effective prognostic model.

Methods

We extracted 1,222 messenger RNA (mRNA) samples of 1,110 patients registered in the BRCA cohort of The Cancer Genome Atlas (TCGA), including 1,109 tumor tissue mRNA samples and 113 standard tissue samples for model construction and verification. The prognostic significance was determined by least absolute shrinkage and selection operator (LASSO)-Cox proportional hazard regression, which showed that the overall survival (OS) of the high-risk group was shorter than that of the low group (P<0.01).

Results

Although the CMS prognostic model can predict the prognosis well, the receiver operating characteristic (ROC) prediction results were unsatisfactory. The reason for this may be the heteromorphism of BRCA, so we divided the cases into four subtypes according to the PAM50 (PAM50Call_RNAseq) in clinical information. The same method was used to construct the model in the four subtypes and verify the effect of each subtype prognostic model.

Conclusions

The results showed that the submodels constructed in this study can be used to evaluate the prognosis of each subtype.

Transforming RNA-Seq gene expression to track cancer progression in the multi-stage early to advanced-stage cancer development

BACKGROUND

Cancer progression can be tracked by gene expression changes that occur throughout early-stage to advanced-stage cancer development. The accumulated genetic changes can be detected when gene expression levels in advanced-stage are less variable but show high variability in early-stage. Normalizing advanced-stage expression samples with early-stage and clustering of the normalized expression samples can reveal cancers with similar or different progression and provide insight into clinical and phenotypic patterns of patient samples within the same cancer.

OBJECTIVE

This study aims to investigate cancer progression through RNA-Seq expression profiles across the multi-stage process of cancer development.

METHODS

RNA-sequenced gene expression of Diffuse Large B-cell Lymphoma, Lung cancer, Liver cancer, Cervical cancer, and Testicular cancer were downloaded from the UCSC Xena database. Advanced-stage samples were normalized with early-stage samples to consider heterogeneity differences in the multi-stage cancer progression. WGCNA was used to build a gene network and categorized normalized genes into different modules. A gene set enrichment analysis selected key gene modules related to cancer. The diagnostic capacity of the modules was evaluated after hierarchical clustering.

RESULTS

Unnormalized RNA-Seq gene expression failed to segregate advanced-stage samples based on selected cancer cohorts. Normalization with early-stage revealed the true heterogeneous gene expression that accumulates across the multi-stage cancer progression, this resulted in well segregated cancer samples. Cancer-specific pathways were enriched in the normalized WGCNA modules. The normalization method was further able to stratify patient samples based on phenotypic and clinical information. Additionally, the method allowed for patient survival analysis, with the Cox regression model selecting gene MAP4K1 in cervical cancer and Kaplan-Meier confirming that upregulation is favourable.

CONCLUSION

The application of the normalization method further enhanced the accuracy of clustering of cancer samples based on how they progressed. Additionally, genes responsible for cancer progression were discovered.

Stabilized COre gene and Pathway Election uncovers pan-cancer shared pathways and a cancer-specific driver

Approaches systematically characterizing interactions via transcriptomic data usually follow two systems: (i) coexpression network analyses focusing on correlations between genes and (ii) linear regressions (usually regularized) to select multiple genes jointly. Both suffer from the problem of stability: A slight change of parameterization or dataset could lead to marked alterations of outcomes. Here, we propose Stabilized COre gene and Pathway Election (SCOPE), a tool integrating bootstrapped least absolute shrinkage and selection operator and coexpression analysis, leading to robust outcomes insensitive to variations in data. By applying SCOPE to six cancer expression datasets (BRCA, COAD, KIRC, LUAD, PRAD, and THCA) in The Cancer Genome Atlas, we identified core genes capturing interaction effects in crucial pan-cancer pathways related to genome instability and DNA damage response. Moreover, we highlighted the pivotal role of CD63 as an oncogenic driver and a potential therapeutic target in kidney cancer. SCOPE enables stabilized investigations toward complex interactions using transcriptome data.

Comprehensive Analysis of DMRT3 as a Potential Biomarker Associated with the Immune Infiltration in a Pan-Cancer Analysis and Validation in Lung Adenocarcinoma

Doublesex and Mab-3 related Transcription Factor 3 (DMRT3) is associated with the prognosis of some tumors. It is possible to explore the role of DMRT3 in the cancer process using bioinformatic approaches and experimental validation. We comprehensively explored the clinical and immunological characteristics of DMRT3. The DMRT3 expression is abnormal in human cancers and correlates with clinical staging. A high DMRT3 expression is significantly associated with poor overall survival (OS) in KIRC, KIRP, LUAD, and UCEC. Amplification was the greatest frequency of the DMRT3 alterations in pan-cancer. The OS was significantly lower in the DMRT3 altered group than in the DMRT3 unaltered group (P = 0.0276). The DMRT3 expression was significantly associated with MSI in three cancer types and TMB in six cancer types. The DMRT3 expression was significantly correlated with the level of the immune cell infiltration and the immune checkpoint genes. The DMRT3 was involved in some pathways in pan-cancer. DMRT3 may play a role in chemotherapy and may be associated with chemoresistance. A ceRNA network of KCNQ1OT1/miR-335-5p/DMRT3 was constructed in LUAD. DMRT3 was significantly upregulated in the LUAD cell lines. DMRT3 was aberrantly expressed in pan-cancer and may promote tumorigenesis and progression via different mechanisms. DMRT3 can be used as a therapeutic target to treat cancer in humans.

Non-coding ribonucleic acid-mediated CAMSAP1 upregulation leads to poor prognosis with suppressed immune infiltration in liver hepatocellular carcinoma

Liver hepatocellular carcinoma (LIHC) is well-known for its unfavorable prognosis due to the lack of reliable diagnostic and prognostic biomarkers. Calmodulin-regulated spectrin-associated protein 1 (CAMSAP1) is a non-centrosomal microtubule minus-end binding protein that regulates microtubule dynamics. This study aims to investigate the specific role and mechanisms of CAMSAP1 in LIHC. We performed systematical analyses of CAMSAP1 and demonstrated that differential expression of CAMSAP1 is associated with genetic alteration and DNA methylation, and serves as a potential diagnostic and prognostic biomarker in some cancers, especially LIHC. Further evidence suggested that CAMSAP1 overexpression leads to adverse clinical outcomes in advanced LIHC. Moreover, the AC145207.5/LINC01748-miR-101–3p axis is specifically responsible for CAMSAP1 overexpression in LIHC. In addition to the previously reported functions in the cell cycle and regulation of actin cytoskeleton, CAMSAP1-related genes are enriched in cancer- and immune-associated pathways. As expected, CAMSAP1-associated LIHC is infiltrated in the suppressed immune microenvironment. Specifically, except for immune cell infiltration, it is significantly positively correlated with immune checkpoint genes, especially CD274 (PD-L1), and cancer-associated fibroblasts. Prediction of immune checkpoint blockade therapy suggests that these patients may benefit from therapy. Our study is the first to demonstrate that besides genetic alteration and DNA methylation, AC145207.5/LINC01748-miR-101-3p-mediated CAMSAP1 upregulation in advanced LIHC leads to poor prognosis with suppressed immune infiltration, representing a potential diagnostic and prognostic biomarker as well as a promising immunotherapy target for LIHC.

Analysis of the prognostic, diagnostic and immunological role of HSP90α in malignant tumors

Heat shock protein 90α (HSP90α) encoded by the HSP90AA1 gene, is the stress inducible isoform of the molecular chaperone HSP90, and was demonstrated as a promising hallmark to diagnose, prognosis in malignant tumors. This study is to evaluate the value of HSP90α in diagnosis, prognosis and immunotherapy of malignant tumors by investigating the expression of HSP90α in plasma of various tumors and analyzing the expression of HSP90α at gene and protein levels via pan-cancer database. We founded that levels of HSP90α in malignant tumors groups were significantly higher than healthy controls in serum. Pan-cancer analysis showed that HSP90AA1 was highly expressed in 27 of 33 tumors, but low in individual cancers (such as renal malignancies). The plasma HSP90α level was positively correlated with the stage of malignant tumor, but there was no significant difference between HSP90AA1 and the stage of most tumors. Cox regression analysis showed that HSP90AA1 expression was significantly correlated with OS in only 6 of the 32 cancers, including LIHC, KIRC, HNSC, LUAD, BRCA and MESO. Up-regulation of HSP90AA1 in most tumors was positively correlated with PDCD1LG2 and CD274 immune checkpoint genes. T cell CD8+ was positively correlated with HSP90AA1 in COAD, DLBC and UVM, and negatively correlated with HSP90AA1 in ESCA, GBM, HNSC, KIRC, KIRP, UCEC and STAD. The AUC of HSP90α are generally high in different tumor groups, which indicated its diagnostic value in malignant tumors. In conclusion, serum HSP90α in patients with malignant tumor is generally elevated, which is of positive significance as an independent diagnosis and combined diagnosis. However, we found that the expression level of HSP90AA1 gene in most tumors was not completely consistent with the serum level, and even down-regulated in some tumors. Plasma levels can be used as biomarkers of poor prognosis in some tumors, but it cannot be used as a biomarker for poor prognosis of all tumors, and more in-depth studies are needed.

Prognostic and Immunological Role of PPP1R14A as a Pan-Cancer Analysis Candidate

Despite emerging evidence revealing the remarkable roles of protein phosphatase 1 regulatory inhibitor subunit 14A (PPP1R14A) in cancer tumorigenesis and progression, no pan-cancer analysis is available. A comprehensive investigation of the potential carcinogenic mechanism of PPP1R14A across 33 tumors using bioinformatic techniques is reported for the first time. PPP1R14A is downregulated in major malignancies, and there is a significant correlation between the PPP1R14A expression and the prognosis of patients. The high expression of PPP1R14A in most cases was associated with poor overall survival (OS), disease-specific survival (DSS), and progress-free interval (PFI) across patients with various malignant tumors, including adrenocortical carcinoma (ACC) and bladder urothelial carcinoma (BLCA), indicated through pan-cancer survival analysis. Receiver operating characteristic (ROC) analysis subsequently exhibited that the molecule has high reference significance in diagnosing a variety of cancers. The frequency of PPP1R14A genetic changes including genetic mutations and copy number alterations (CNAs) in uterine carcinosarcoma reached 16.07%, and these alterations brought misfortune to the survival and prognosis of cancer patients. In addition, methylation within the promoter region of PPP1R14A DNA was enhanced in a majority of cancers. Downregulated phosphorylation levels of phosphorylation sites including S26, T38, and others in most cases took place in several tumors, such as breast cancer and colon cancer. PPP1R14A remarkably correlated with the levels of infiltrating cells and immune checkpoint genes. Our research on the carcinogenic effect of PPP1R14A in different tumors is comprehensively summarized and analyzed and provides a theoretical basis for future therapeutic and immunotherapy strategies.

Identifying common transcriptome signatures of cancer by interpreting deep learning models

Background

Cancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely between tumor types, but common gene signatures that relate to core cancer pathways have also been identified. It is not clear, however, whether there exist additional sets of genes or transcriptomic features that are less well known in cancer biology but that are also commonly deregulated across several cancer types.

Results

Here, we agnostically identify transcriptomic features that are commonly shared between cancer types using 13,461 RNA-seq samples from 19 normal tissue types and 18 solid tumor types to train three feed-forward neural networks, based either on protein-coding gene expression, lncRNA expression, or splice junction use, to distinguish between normal and tumor samples. All three models recognize transcriptome signatures that are consistent across tumors. Analysis of attribution values extracted from our models reveals that genes that are commonly altered in cancer by expression or splicing variations are under strong evolutionary and selective constraints. Importantly, we find that genes composing our cancer transcriptome signatures are not frequently affected by mutations or genomic alterations and that their functions differ widely from the genes genetically associated with cancer.

Conclusions

Our results highlighted that deregulation of RNA-processing genes and aberrant splicing are pervasive features on which core cancer pathways might converge across a large array of solid tumor types.

Supplementary Information

The online version contains supplementary material available at (10.1186/s13059-022-02681-3).

PCMT1 Is a Potential Prognostic Biomarker and Is Correlated with Immune Infiltrates in Breast Cancer

Background

Protein-L-isoaspartate (D-aspartate) O-methyltransferase (PCMT1) is involved in the occurrence and development of a variety of malignant tumors. However, the prognostic value of PCMT1 in breast cancer remains unclear.

Methods

Based on the Cancer Genome Atlas database, we assessed the correlation between the expression of PCMT1 and prognosis, immune invasion, and tumor mutation burden in a variety of cancers. The expression level, mutation, immune correlation, and coexpression of PCMT1 in breast cancer were studied using the following databases: UALCAN database, Human Protein Atlas database, cBioPortal database, TIMER database, and LinkedOmics database. Kaplan–Meier Plotter was used for survival analysis. Receiver operating characteristic (ROC) curves and nomograms were drawn using the R software package. P < 0.05 was considered statistically significant.

Results

Pancancer analysis showed that PCMT1 is highly expressed in a variety of cancers and is significantly related to the prognosis of a variety of cancers. PCMT1 is significantly related to the tumor mutation burden of a variety of cancers. PCMT1 is significantly high in breast cancer, and it is significantly related to the abundance of immune infiltration. Survival analysis revealed that high PCMT1 expression is significantly associated with shorter overall survival (OS), relapse-free survival (RFS), and postprogression survival (PPS) in breast cancer patients. ROC curves and nomograms verify the effectiveness of PCMT1 as a prognostic biomarker for breast cancer.

Conclusions

PCMT1 can be used as a potential prognostic biomarker of breast cancer, and it is significantly related to the abundance of breast cancer immune infiltration.

miRNA-Mediated Low Expression of EPHX3 Is Associated with Poor Prognosis and Tumor Immune Infiltration in Head and Neck Squamous Cell Carcinomas

The aim of this study was to explore the regulatory role of epoxide hydrolase 3 (EPHX3) in head and neck squamous cell carcinoma (HNSCC) and to analyze its bioinformatic function, as well as, to screen and predict the miRNAs that can regulate EPHX3 expression in HNSCC. We examined the expression profile and prognostic potential of EPHX3 in TCGA and GTEX databases and performed functional enrichment analysis of EPHX3 using string database. Subsequently, we analyzed the regulatory role of miRNAs on EPHX3, including expression analysis, correlation analysis, and survival analysis. In addition, we also used TIMER to investigate the relationship among EPHX3 expression level, immune checkpoints, and immune infiltration in HNSCC. The results of data analysis after TGCA showed that EPHX3 is a key regulator of tumorigenesis in 13 cancers and can be used as a marker of poor prognosis in HNSCC patients. Bioinformatics analysis revealed that miR-4713-3p is a key miRNA of EPHX3 in HNSCC. Together, our findings indicate that EPHX3 exerts its anticancer effects by suppressing tumor immune checkpoint expression and immune cell infiltration. Overall, our data uncovered miRNA-mediated EPHX3 downregulation as a contributor to poor HNSCC prognosis and reduced tumor immune infiltration.

Mapk14 is a Prognostic Biomarker and Correlates with the Clinicopathological Features and Immune Infiltration of Colorectal Cancer

Background: Colorectal cancer (CRC) is one of the most common gastrointestinal tumors, ranking in the top 5 of all common tumors in terms of incidence and mortality. However, the mechanisms driving the evolution of colorectal cancer remain unclear. Therefore, we investigated the association between Mapk14 expression and clinicopathological and tumor-infiltrating immune cells.

Methods: In this study, we collected CRC patient data from The Cancer Genome Atlas (TCGA), compared the expression level in CRC and normal colorectal tissue using the Wilcoxon rank sum test and assessed the relationship between Mapk14 and clinicopathological features using the Welch one-way ANOVA test. Kaplan-Meier and timeROC GSE17537 datasets were obtained from the Gene Expression Omnibus (GEO) dataset to assess the prognostic impact of the Mapk14 gene on colorectal cancer. Second, we further explored the methylation level of Mapk14 and its influencing factors. Single-cell sequencing of Mapk14 in the tumor immune microenvironment (TIME) was analyzed using the GSE108989 dataset. Further analyses based on the TIMER method were performed to assess the correlation between Mapk14 and tumor immune infiltration, immune checkpoints, tumor mutational load and microsatellite instability. Finally, the results of the bioinformatics analysis were verified by an immunohistochemical analysis.

Results: The results showed that the expression of Mapk14 was upregulated in CRC tumor tissues compared with normal colorectal tissues and the high expression of Mapk14 was associated with poor clinicopathological features and poor prognoses in the CRC array. In addition, cg05798012 and cg25375420 of Mapk14 are the main DNA methylation sites affecting OS. Single-cell sequencing of the tumor immune microenvironment showed that the abundance and cell state of dysfunctional T cells changed greatly. Importantly, the abnormal overexpression of Mapk14 in colorectal cancer is related to the level of immune infiltration of immune cells (including CD8⁺ T cells, neutrophils, dendritic cells, B cells, CD4⁺ T cells, and macrophages). The high expression of Mapk14 was significantly correlated with immune checkpoints (including SIGLEC15, TIGIT, LAG3, CTLA4 and PDCDILG2), while the high expression of Mapk14 was negatively correlated with TMB and MSI but mostly positively correlated with drug sensitivity. Finally, the immunohistochemical results confirmed that the clinical stage (Ⅰ, Ⅱ, Ⅲ and Ⅳ) and M stage (M0 and M1) affected the abnormally high expression of Mapk14.

Conclusion: A comprehensive bioinformatics study and experimental validation revealed that Mapk14 could serve as a novel prognostic biomarker associated with immune infiltration and pharmacotherapy and may represent a potential therapeutic target for the treatment of CRC.

Construction and Clinical Translation of Causal Pan-Cancer Gene Score Across Cancer Types

Pan-cancer strategy, an integrative analysis of different cancer types, can be used to explain oncogenesis and identify biomarkers using a larger statistical power and robustness. Fine-mapping defines the casual loci, whereas genome-wide association studies (GWASs) typically identify thousands of cancer-related loci and not necessarily have a fine-mapping component. In this study, we develop a novel strategy to identify the causal loci using a pan-cancer and fine-mapping assumption, constructing the CAusal Pan-cancER gene (CAPER) score and validating its performance using internal and external validation on 1,287 individuals and 985 cell lines. Summary statistics of 15 cancer types were used to define 54 causal loci in 15 potential genes. Using the Cancer Genome Atlas (TCGA) training set, we constructed the CAPER score and divided cancer patients into two groups. Using the three validation sets, we found that 19 cancer-related variables were statistically significant between the two CAPER score groups and that 81 drugs had significantly different drug sensitivity between the two CAPER score groups. We hope that our strategies for selecting causal genes and for constructing CAPER score would provide valuable clues for guiding the management of different types of cancers.

Pancancer Analysis of Neurovascular-Related NRP Family Genes as Potential Prognostic Biomarkers of Bladder Urothelial Carcinoma

Background

Neurovascular-related genes have been implicated in the development of cancer. Studies have shown that a high expression of neuropilins (NRPs) promotes tumourigenesis and tumour malignancy.

Method

A multidimensional bioinformatics analysis was performed to examine the relationship between NRP genes and prognostic and pathological features, tumour mutational burden (TMB), microsatellite instability (MSI), and immunological features based on public databases and find the potential prognostic value of NRPs in pancancer.

Results

Survival analysis revealed that a low NRP1 expression in adrenocortical carcinoma (ACC), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), low-grade glioma (LGG), and stomach adenocarcinoma (STAD) was associated with poor prognosis. A high NRP2 expression in bladder urothelial carcinoma (BLCA), kidney renal papillary cell carcinoma (KIRP), and mesothelioma (MESO) was associated with poor prognosis. Moreover, NRP1 and NRP2 were associated with TMB and MSI. Subsequent analyses showed that NRP1 and NRP2 were correlated with immune infiltration and immune checkpoints. Genome-wide association analysis revealed that the NRP1 expression was strongly associated with kidney renal clear cell carcinoma (KIRC), whereas the NRP2 expression was closely associated with BLCA. Ultimately, NRP2 was found to be involved in the development of BLCA.

Conclusions

Neurovascular-related NRP family genes are significantly correlated with cancer prognosis, TME, and immune infiltration, particularly in BLCA.

Establishing a consensus for the hallmarks of cancer based on gene ontology and pathway annotations

BACKGROUND

The hallmarks of cancer provide a highly cited and well-used conceptual framework for describing the processes involved in cancer cell development and tumourigenesis. However, methods for translating these high-level concepts into data-level associations between hallmarks and genes (for high throughput analysis), vary widely between studies. The examination of different strategies to associate and map cancer hallmarks reveals significant differences, but also consensus.

RESULTS

Here we present the results of a comparative analysis of cancer hallmark mapping strategies, based on Gene Ontology and biological pathway annotation, from different studies. By analysing the semantic similarity between annotations, and the resulting gene set overlap, we identify emerging consensus knowledge. In addition, we analyse the differences between hallmark and gene set associations using Weighted Gene Co-expression Network Analysis and enrichment analysis.

CONCLUSIONS

Reaching a community-wide consensus on how to identify cancer hallmark activity from research data would enable more systematic data integration and comparison between studies. These results highlight the current state of the consensus and offer a starting point for further convergence. In addition, we show how a lack of consensus can lead to large differences in the biological interpretation of downstream analyses and discuss the challenges of annotating changing and accumulating biological data, using intermediate knowledge resources that are also changing over time.

Clinical Impact of Tumor-Infiltrating Lymphocytes and PD-L1-Positive Cells as Prognostic and Predictive Biomarkers in Urological Malignancies and Retroperitoneal Sarcoma

Simple Summary

Two host-dependent biological characteristics, “avoiding immune destruction” and “tumor-promoting inflammation” have been added to cancer hallmarks in 2011. The interaction and cross-talk among tumor cells and several immune cells in a tumor microenvironment are dynamic and complex processes. The purpose of this review is to discuss the prognostic impact of tumor-infiltrating lymphocytes and predictive biomarkers for immune checkpoint inhibitors in four urological solid tumors, the urothelial carcinoma, renal cell carcinoma, prostate cancer, and retroperitoneal sarcoma, through summarizing the findings of observation studies and clinical trials.

Abstract

Over the past decade, an “immunotherapy tsunami”, more specifically that involving immune checkpoint inhibitors (ICIs), has overtaken the oncological field. The interaction and cross-talk among tumor cells and several immune cells in the tumor microenvironment are dynamic and complex processes. As immune contexture can vary widely across different types of primary tumors and tumor microenvironments, there is still a significant lack of clinically available definitive biomarkers to predict patient response to ICIs, especially in urogenital malignancies. An increasing body of evidence evaluating urological malignancies has proven that tumor-infiltrating lymphocytes (TILs) are a double-edged sword in cancer. There is an urgent need to shed light on the functional heterogeneity in the tumor-infiltrating immune system and to explore its prognostic impact following surgery and other treatments. Notably, we emphasized the difference in the immunological profile among urothelial carcinomas arising from different primary origins, the bladder, renal pelvis, and ureter. Significant differences in the density of FOXP3-positive TILs, CD204-positive tumor-infiltrating macrophages, PD-L1-positive cells, and colony-stimulating factors were observed. This review discusses two topics: (i) the prognostic impact of TILs and (ii) predictive biomarkers for ICIs, to shed light on lymphocyte migration in four solid tumors, the urothelial carcinoma, renal cell carcinoma, prostate cancer, and retroperitoneal sarcoma.

Alternative splicing of leptin receptor overlapping transcript in osteosarcoma

IMPACT STATEMENT

Osteosarcoma (OS, also known as osteogenic sarcoma) is the most common primary malignancy of bone in children and adolescents. The molecular mechanisms of OS are extremely complicated and its molecular mediators remain to be elucidated. We sequenced total RNA from 18 OS bone samples (paired normal-tumor biopsies). We found statistically significant (FDR <0.05) 26 differentially expressed transcript variants of LEPROT gene with different expressions in normal and tumor samples. These findings contribute to the understanding of molecular mechanisms of OS development and provide encouragement to pursue further research.

Quantitative Analysis of Differential Expression of HOX Genes in Multiple Cancers

Transcription factors encoded by Homeobox (HOX) genes play numerous key functions during early embryonic development and differentiation. Multiple reports have shown that mis-regulation of HOX gene expression plays key roles in the development of cancers. Their expression levels in cancers tend to differ based on tissue and tumor type. Here, we performed a comprehensive analysis comparing HOX gene expression in different cancer types, obtained from The Cancer Genome Atlas (TCGA), with matched healthy tissues, obtained from Genotype-Tissue Expression (GTEx). We identified and quantified differential expression patterns that confirmed previously identified expression changes and highlighted new differential expression signatures. We discovered differential expression patterns that are in line with patient survival data. This comprehensive and quantitative analysis provides a global picture of HOX genes' differential expression patterns in different cancer types.

Pan-cancer RNA-seq data stratifies tumours by some hallmarks of cancer

Numerous genetic and epigenetic alterations cause functional changes in cell biology underlying cancer. These hallmark functional changes constitute potentially tissue-independent anticancer therapeutic targets. We hypothesized that RNA-Seq identifies gene expression changes that underly those hallmarks, and thereby defines relevant therapeutic targets. To test this hypothesis, we analysed the publicly available TCGA-TARGET-GTEx gene expression data set from the University of California Santa CruzToil recompute project using WGCNA to delineate co-correlated 'modules' from tumour gene expression profiles and functional enrichment of these modules to hierarchically cluster tumours. This stratified tumours according to T cell activation, NK-cell activation, complement cascade, ATM, Rb, angiogenic, MAPK, ECM receptor and histone modification signalling. These correspond to the cancer hallmarks of avoiding immune destruction, tumour-promoting inflammation, evading growth suppressors, inducing angiogenesis, sustained proliferative signalling, activating invasion and metastasis, and genome instability and mutation. This approach did not detect pathways corresponding to the cancer enabling replicative immortality, resisting cell death or deregulating cellular energetics hallmarks. We conclude that RNA-Seq stratifies tumours along some, but not all, hallmarks of cancer and, therefore, could be used in conjunction with other analyses collectively to inform precision therapy.