TMB: a promising immune-response biomarker, and potential spearhead in advancing targeted therapy trials

Pan-cancer exploration of PNO1: A prospective prognostic biomarker with ties to immune infiltration

The partner of NOB1 homolog (PNO1) is an RNA-binding protein that participates in ribosome biogenesis and protein modification. The functions of this molecule are largely unknown in cancers, particularly breast cancer. We employed bioinformatics methods to probe the putative oncogenic functions of PNO1 based on expression profiles and clinical data from the cancer genome atlas (TCGA), genotype-tissue expression project (GTEx), human protein atlas (HPA), cancer cell line encyclopedia (CCLE), UALCAN, drug sensitivity in cancer (GDSC) and UCSC XENA databases. Our analyses revealed that PNO1 was overexpressed in 31 malignancies, which excluded kidney chromophobe (KICH) and acute myeloid leukemia (LAML). Prognostic assessments have demonstrated that high PNO1 expression was significantly correlated with poor overall and disease-specific survival in various cancers. The promoter methylation level of PNO1 is significantly decreased in breast invasive carcinoma (BRCA), head and neck squamous cell carcinoma (HNSC), kidney renal papillary cell carcinoma (KIRP), prostate adenocarcinoma (PRAD), thyroid carcinoma (THCA) and uterine corpus endometrial carcinoma (UCEC). Furthermore, inhibition of PNO1 decreased the viability, migration and invasion of breast cancer cells, and these results were confirmed by mouse xenograft models of breast cancer. In addition, we discovered that tumor microenvironment (TME), immune infiltration, and chemotherapy sensitivity were influenced by PNO1 expression. Concordantly, our analyses revealed a significant positive correlation between PNO1 and programmed cell death ligand 1 (PD-L1) expression across breast carcinoma samples. In conclusion, these findings indicate that PNO1 could act as a promising prognostic biomarker and adjunct diagnostic indicator, because it affects tumor growth and invasion. Our study offers valuable new perspectives on the oncogenic role of PNO1 in various types of cancers.

Different characteristics of the tumor immune microenvironment among subtypes of salivary gland cancer

AIM

Although immune checkpoint inhibitors (ICPi) for salivary gland cancer (SGC) have been investigated in clinical trials, details of the tumor immune microenvironment (TIME) remain unclear. This research aimed to elucidate the TIME of SGC and its relationship with tumor mutation burden (TMB) and to explore the rationale for the applicability of ICPi.

MATERIALS AND METHODS

We selected five pathological types, namely adenoid cystic carcinoma (ACC); adenocarcinoma, not otherwise specified (ANOS); salivary duct carcinoma (SDC); and low/high-grade mucoepidermoid carcinoma (MEClow/high). We investigated the TIME and TMB of each pathological type. TIME was evaluated by multiplexed fluorescent immunohistochemistry. TMB was measured by next-generation sequencing.

RESULTS

ACC and MEChigh showed the lowest and highest infiltration of immune effector and suppressor cells in both tumor and stroma. ANOS, SDC, and MEClow showed modest infiltration of immune effector cells in tumors. Correlation analysis showed a positive correlation between CD3+CD8+ T cells in tumor and TMB (r = 0.647). CD3+CD8+ T cells in tumors showed a positive correlation with programmed cell death-ligand 1 expression in tumor cells (r = 0.513) and a weak positive correlation with CD3+CD4+Foxp3+ cells in tumors (r = 0.399). However, no correlation was observed between CD3+CD8+ T cells and CD204+ cells in tumors (r = -0.049).

CONCLUSION

The TIME of ACC was the so-called immune desert type, which may explain the mechanisms of the poor response to ICPi in previous clinical trials. On the other hand, MEChigh was the immune-inflamed type, and this may support the rationale of ICPi for this pathological subtype.

Integrating Bulk and Single-Cell RNA-Seq Data to Identify Prognostic Features Related to Activated Dendritic Cells in Clear-Cell Renal-Cell Carcinoma

Dendritic cells (DCs) serve as key regulators in tumor immunity, with activated DCs potentiating antitumor responses through the secretion of pro-inflammatory cytokines and the expression of co-stimulatory molecules. Most current studies focus on the relationship between DC subgroups and clear-cell renal-cell carcinoma (ccRCC), but there is limited research on the connection between DCs and ccRCC from the perspective of immune activation. In this study, activated DC genes were identified in both bulk and single-cell RNA-seq data. A prognostic model related to activated DCs was constructed using univariate, multivariate Cox regression and LASSO regression. The prognostic model was validated in three external validation sets: GSE167573, ICGC, and E-MTAB-1980. The prognostic model consists of five genes, PLCB2, XCR1, IFNG, HLA-DQB2, and SMIM24. The expression of these genes was validated in tissue samples using qRT-PCR. Stratified analysis revealed that the prognostic model was able to better predict outcomes in advanced ccRCC patients. The risk scores were associated with tumor progression, tumor mutation burden, immune cell infiltration, and adverse outcomes of immunotherapy. Notably, there was a strong correlation between the expression of the five genes and the sensitivity to JQ1, a BET inhibitor. Molecular docking indicated high-affinity binding of the proteins encoded by these genes with JQ1. In conclusion, our study reveals the crucial role of activated DCs in ccRCC, offering new insights into predicting immune response, targeted therapy effectiveness, and prognosis for ccRCC patients.

Gemogenovatucel-T (Vigil): bi-shRNA plasmid-based targeted immunotherapy

We describe in this review the historical evidence leading up to the concept and design of Vigil and subsequent clinical applications including safety and efficacy in a randomized, controlled Phase IIB trial. Vigil (gemogenovatucel-T) is a unique triple function targeted immunotherapy that demonstrates preclinical and clinical systemic anticancer activity. Construction of Vigil involves harvest of autologous malignant tissue for neoantigen targeting (ideally containing clonal neoantigens) followed by a two-day process involving transfection with a plasmid to provide a permissive 'training environment' for the patient's immune system. Transfected plasmid components contain an expressive human GMCSF DNA segment to enhance anticancer immune functional response and a second component expressing bi-shRNAfurin which reduces TGFβ isomers (TGFβ1 and TGFβ2) thereby reducing cancer inhibition of the targeted immune response. Results generated to date justify advancement to confirmatory clinical trials supporting product regulatory approval.

MIS18A upregulation promotes cell viability, migration and tumor immune evasion in lung adenocarcinoma

Lung adenocarcinoma (LUAD) presents a significant global health challenge owing to its poor prognosis and high mortality rates. Despite its involvement in the initiation and progression of a number of cancer types, the understanding of the precise impact of MIS18 kinetochore protein A (MIS18A) on LUAD remains incomplete. In the present study, the role of MIS18A in LUAD was investigated by analyzing the genomic and clinical data from multiple public datasets. The expression of MIS18A was validated using reverse transcription-quantitative polymerase chain reaction, and in vitro experiments involving small interfering RNA-induced downregulation of MIS18A in lung cancer cells were conducted to further explore its impact. These findings revealed that elevated MIS18A expression in LUAD was associated with advanced clinical features and poor prognosis. Functional analysis also revealed the role of MIS18A in regulating the cell cycle and immune-related pathways. Moreover, MIS18A altered the immune microenvironment in LUAD, influencing its response to immunotherapy and drug sensitivity. The results of the in vitro experiments indicated that suppression of MIS18A expression reduced the proliferative and migratory capacities of LUAD cells. In summary, MIS18A possesses potential as a biomarker and may serve as a possible therapeutic target for LUAD, with significant implications for tumor progression by influencing both cell cycle dynamics and immune infiltration.

Pan-cancer analysis of COL15A1: an immunological and prognostic biomarker

Collagen, type XV, alpha 1 (COL15A1) belongs to the collagen superfamily, which can influence disease progression by modulating immune pathways. Although the growing number of investigations demonstrating the indispensable role of COL15A1 in the progression of certain tumors, no pan-cancer assessment of COL15A1 is accessible to date. Therefore, the available data was used to explore the role of COL15A1 in 33 types of tumors and to investigate their potential immune function. Numerous bioinformatics approaches were used to research the potential oncogenic role of COL15A1, including analysis of tumor prognosis, microsatellite instability (MSI), tumor mutational burden (TMB), single nucleotide polymorphism (SNP), drug sensitivity, immune cell infiltration, and the correlation between cancer stem cells (CSCs) and COL15A1 expression. The outcome implies that most tumors had a high expression of COL15A1, and COL15A1 manifested different relationships with prognosis in different tumors, including both positive and negative correlations. COL15A1 was also found to have a significant correlation with MSI, TMB, and immune infiltrating cells. Our study suggests that COL15A1 may serve as a prognostic marker for malignancy because of its differential expression in tissues and their function in tumor immunity.

Systematic pan-cancer analysis insights into ICAM1 as an immunological and prognostic biomarker

Intercellular adhesion molecule 1 (ICAM1) is a cell surface adhesion glycoprotein in the immunoglobulin supergene family. It is associated with several epithelial tumorigenesis processes, as well as with inflammation. However, the function of ICAM1 in the prognosis of tumor immunity is still unclear. This study aimed to examine the immune function of ICAM1 in 33 tumor types and to investigate the prognostic value of tumors. Using datasets from the Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), Cancer Cell Lines Encyclopedia (CCLE), Human Protein Atlas (HPA), and cBioPortal, we investigated the role of ICAM1 in tumors. We explored the potential correlation between ICAM1 expression and tumor prognosis, gene mutations, microsatellite instability, and tumor immune cell levels in various cancers. We observed that ICAM1 is highly expressed in multiple malignant tumors. Furthermore, ICAM1 is negatively or positively associated with different malignant tumor prognoses. The expression levels of ICAM1 were correlated with the tumor mutation burden (TMB) in 11 tumors and with MSI in eight tumors. ICAM1 is a gene associated with immune infiltrating cells, such as M1 macrophages and CD8+ T cells in gastric and colon cancer. Meanwhile, the expression of ICAM1 is associated with several immune-related functions and immune-regulation-related signaling pathways, such as the chemokine signaling pathway. Our study shows that ICAM1 can be used as a prognostic biomarker in many cancer types because of its function in tumorigenesis and malignant tumor immunity.

PCDH11X mutation as a potential biomarker for immune checkpoint therapies in lung adenocarcinoma

Immune checkpoint inhibitors (ICIs) have achieved impressive success in lung adenocarcinoma (LUAD). However, the response to ICIs varies among patients, and predictive biomarkers are urgently needed. PCDH11X is frequently mutated in LUAD, while its role in ICI treatment is unclear. In this study, we curated genomic and clinical data of 151 LUAD patients receiving ICIs from three independent cohorts. Relations between PCDH11X and treatment outcomes of ICIs were examined. A melanoma cohort collected from five published studies, a pan-cancer cohort, and non-ICI-treated TCGA-LUAD cohort were also examined to investigate whether PCDH11X mutation is a specific predictive biomarker for LUAD ICI treatment. Among the three ICI-treated LUAD cohorts, PCDH11X mutation (PCDH11X-MUT) was associated with better clinical response compared to wild-type PCDH11X (PCDH11X-WT). While in ICI-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and the non-ICI-treated TCGA-LUAD cohort, no significant differences in overall survival (OS) were observed between the PCDH11X-MUT and PCDH11X-WT groups. PCDH11X mutation was associated with increased PD-L1 expression, tumor mutation burden (TMB), neoantigen load, DNA damage repair (DDR) mutations, and hot tumor microenvironment in TCGA-LUAD cohort. Our findings suggested that the PCDH11X mutation might serve as a specific biomarker to predict the efficacy of ICIs for LUAD patients. Considering the relatively small sample size of ICI-treated cohorts, future research with larger cohorts and prospective clinical trials will be essential for validating and further exploring the role of PCDH11X mutation in the context of immunotherapy outcomes in LUAD. KEY MESSAGES: PCDH11X mutation is associated with better clinical response compared to wild type PCDH11X in three ICIs-treated LUAD cohorts. In ICIs-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and non-ICIs-treated TCGA-LUAD cohorts PCDH11X mutation is not associated with better clinical response, suggesting PCDH11X mutation might be a specific biomarker to predict the efficacy of ICIs treatment for LUAD patients. PCDH11X mutation is associated with increased PD-L1 expression, tumor mutation burden, and neoantigen load in TCGA-LUAD cohort. PCDH11X mutation is associated with hot tumor microenvironment in TCGA-LUAD cohort.

Assessing the predictive value of smoking history for immunotherapy outcomes in bladder cancer patients

Background

The therapeutic effectiveness of immune checkpoint inhibitors (ICIs) in bladder cancer varies among individuals. Identifying reliable predictors of response to these therapies is crucial for optimizing patient outcomes.

Methods

This retrospective study analyzed 348 bladder cancer patients treated with ICIs, with additional validation using data from 248 patients at our institution who underwent PD-L1 immunohistochemical staining. We examined patient smoking history, clinicopathological characteristics, and immune phenotypes. The main focus was the correlation between smoking history and immunotherapy outcomes. Multivariate logistic and Cox proportional hazard regressions were used to adjust for confounders.

Results

The study cohort comprised 348 bladder cancer patients receiving ICIs. Among them, 116 (33.3%) were never smokers, 197 (56.6%) were former smokers (median pack-years = 28), and 35 (10.1%) were current smokers (median pack-years = 40). Analysis revealed no statistically significant difference in overall survival across different smoking statuses (objective response rates were 11.4% for current smokers, 17.2% for never smokers, and 22.3% for former smokers; P = 0.142, 0.410, and 0.281, respectively). However, a notable trend indicated a potentially better response to immunotherapy in former smokers compared to current and never smokers. In the validation cohort of 248 patients from our institution, immunohistochemical analysis showed that PD-L1 expression was significantly higher in former smokers (55%) compared to current smokers (37%) and never smokers (47%). This observation underscores the potential influence of smoking history on the tumor microenvironment and its responsiveness to ICIs.

Conclusion

In conclusion, our study demonstrates the importance of incorporating smoking history in predicting the response to immunotherapy in bladder cancer patients, highlighting its role in personalized cancer treatment approaches. Further research is suggested to explore the comprehensive impact of lifestyle factors on treatment outcomes.

Comparison of target agent treatment strategies for platinum-resistant recurrent ovarian cancer: A Bayesian network meta-analysis

BACKGROUND

We aimed to compare 7 newer immunotherapies and targeted therapies for platinum-resistant relapsed ovarian cancer.

METHODS

We conducted a comprehensive search of PubMed, EMBASE, and Cochrane Library electronic databases for phase III trials involving platinum-resistant recurrent ovarian cancer (PRrOC) patients treated with immunotherapy or targeted therapy in combination with chemotherapy. The quality of the included trials was assessed using the GRADE method. The primary outcome of comparison was progression-free survival, and secondary outcomes included overall survival and safety.

RESULTS

This analysis included 7 randomized phase III controlled trials, encompassing 2485 PRrOC patients. Combining bevacizumab plus chemotherapy and lurbinectedin demonstrated statistically significant differences in progression-free survival compared to all other regimens of interest. However, no statistically significant differences were observed in the overall survival. Nivolumab and mirvetuximab exhibited fewer serious adverse events than the other regimens of interest.

CONCLUSIONS

Our findings indicate that bevacizumab combined with chemotherapy and lurbinectedin monotherapy has significant efficacy in patients with PRrOC. For patients with PRrOC who have exhausted treatment options, nivolumab and mirvetuximab may be considered as alternatives because of their better safety profiles.

Assessing personalized responses to anti-PD-1 treatment using patient-derived lung tumor-on-chip

There is a compelling need for approaches to predict the efficacy of immunotherapy drugs. Tumor-on-chip technology exploits microfluidics to generate 3D cell co-cultures embedded in hydrogels that recapitulate simplified tumor ecosystems. Here, we present the development and validation of lung tumor-on-chip platforms to quickly and precisely measure ex vivo the effects of immune checkpoint inhibitors on T cell-mediated cancer cell death by exploiting the power of live imaging and advanced image analysis algorithms. The integration of autologous immunosuppressive FAP+ cancer-associated fibroblasts impaired the response to anti-PD-1, indicating that tumors-on-chips are capable of recapitulating stroma-dependent mechanisms of immunotherapy resistance. For a small cohort of non-small cell lung cancer patients, we generated personalized tumors-on-chips with their autologous primary cells isolated from fresh tumor samples, and we measured the responses to anti-PD-1 treatment. These results support the power of tumor-on-chip technology in immuno-oncology research and open a path to future clinical validations.

GJB3: a comprehensive biomarker in pan-cancer prognosis and immunotherapy prediction

BACKGROUND

A wide range of connexins are situated between normal-normal cells, cancer-cancer cells, and cancer-normal cells. Abnormalities in connexin expression are typically accompanied by cancer development; however, no systematic studies have examined the role of Gap Junction Protein Beta 3 (GJB3) in the context of tumor progression and immunity, especially when considering a broad range of cancer types.

METHODS

In this study, data on GJB3 expression were gathered from Genotype-Tissue Expression, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas databases. Then, we analyzed the relationship between GJB3 expression and tumor characteristics. In vitro experiments using colony formation, EdU, CCK8, transwell migration assays, immunohistochemistry and western blot were performed to investigate the function of GJB3 in tumor progression of various cell lines. A drug sensitivity analysis of GJB3 was performed using the Genomics of Drug Sensitivity in Cancer database.

RESULT

Our findings demonstrate that GJB3 is widely expressed in various cancers and correlates significantly with disease stages, patient survival, immunotherapy response, and pharmaceutical guidance. Additionally, GJB3 plays a role in different cancer pathways, as well as in different immune and molecular subtypes of cancer. Co-expression of GJB3 with immune checkpoint genes was observed. Further experiments showed that knockdown of GJB3 inhibited the PI3K/AKT pathway and resulted in reduced proliferation, migration, and viability of different cancer cells.

CONCLUSION

Overall, GJB3 shows potential as a molecular biomarker and therapeutic target for various cancers, particularly lung adenocarcinomas, mesothelioma, pancreatic adenocarcinoma. Thus, GJB3 may represent a new therapeutic target for a wide range of cancers.

Characteristics of Ovarian Cancer Immune Cell Invasion and Bioinformatics to Predict the Effect of Immunotherapy

Recent studies have confirmed that tumor immune cell infiltration (ICI) is associated with sensitivity of ovarian cancer (OC) immunotherapy and disease progression of OC patients. However, studies related to immune infiltration in OC, has not been elucidated. Two algorithms are used to analyze the OC data in the TCGA and GEO databases. After combining the two data sets, the immune cell content of the sample was estimated by Cell-type Identification By Estimate Relative Subsets of RNA Transcripts (CIBERSORT method). An unsupervised consistent clustering algorithm was used to analyze ICI subtypes and their differentially expressed genes (DEGs). Two subgroups and three ICI gene clusters were identified by unsupervised consensus clustering algorithm. The ICI score was obtained by analyzing the gene characteristics through principal component analysis (PCA). The ICI score ranged from -15.8132 to 18.7211, which was associated with the prognosis of OC patients with immunotherapy. The Toll-like receptor pathway, B-cell receptor pathway, antigen processing and presentation pathway, NK-cell-mediated cytotoxicity pathway, and arginine-proline metabolism pathway were activated in the high ICI score group, suggesting that immune cells in the high ICI score group were activated, thus leading to a better prognosis in this group of patients. Patients with G3-G4 in the high ICI rating group were more sensitive to immunotherapy and had a better prognosis in patients with high tumor mutation burden (TMB). This study suggests that ICI scores can be used as a feasible auxiliary indicator for predicting the prognosis of patients with OC.

Pan-cancer analysis of SERPINE family genes as biomarkers of cancer prognosis and response to therapy

Background: Serine protease inhibitor E (SERPINE) family genes participate in the tumor growth, cancer cell survival and metastasis. However, the SERPINE family members role in the prognosis and their clinical therapeutic potentials in various human cancer types have not been elaborately explored. Methods: We preliminarily analyzed expression levels and prognostic values of SERPINE family genes, and investigated the correlation between SERPINEs expression and tumor microenvironment (TME), Stemness score, clinical characteristic, immune infiltration, tumor mutational burden (TMB), immune subtype, and drug sensitivity in pan-cancer, which based on updated public databases and integrated some bioinformatics analysis methods. In addition, we conducted the enrichment analysis of SERPINEs from DAVID and KOBAS databases. Results: SERPINE1, SERPINE2, and SERPINE3 expression were upregulated in nine cancers, twelve cancers, and six cancers, respectively. The expression of SERPINE family genes was associated with the prognosis in several cancers from The Cancer Genome Atlas (TCGA). Furthermore, SERPINE family genes expression also had a significant relation to stromal and immune scores, and RNA stemness score and DNA stemness score in pan-cancer. SERPINE1 and SERPINE2 expression significantly increased in tumor advanced stage in colon adenocarcinoma (COAD). Results showed that SERPINE1 and SERPINE2 expression were negatively related with B cells and Monocytes, respectively. SERPINE2 expression had a significantly positive relation with B cells and Macrophages. In terms of TMB, SERPINE1, SERPINE2, and SERPINE3 were found to associated with TMB in seven cancers, fourteen cancers, and four cancers, respectively. Moreover, all SERPINE gene family members were significantly correlated with immune subtypes. SERPINE1 expression had a significantly positive or negative correlation with drug sensitivity. Conclusion: The study indicated the great potential of SERPINE family genes as biomarkers for prognosis and provided valuable strategies for further investigation of SERPINE family genes as potential targets in cancer.

A tumor-infiltrating immune cells-related pseudogenes signature based on machine-learning predicts outcomes and immunotherapy responses in ovarian cancer

Previous researches have provided evidence for the significant involvement of pseudogenes in immune-related functions across different types of cancer. However, the mechanisms by which pseudogenes regulate immunity in ovarian cancer (OV) and their potential impact on clinical outcomes remain unclear. To address this gap in knowledge, our study utilized a novel computational framework to analyze a total of 491 samples from three public datasets. We employed a combination of 10 machine-learning algorithms to construct a signature known as the tumor-infiltrating immune cells-related pseudogenes signature (TIICPS). The TIICPS, consisting of 12 pseudogenes, demonstrated independent prognostic value for overall survival, surpassing conventional clinical traits, 62 published signatures, and TP53 and BRCA mutation status in three cohorts. Patients with low TIICPS exhibited heightened immune-related pathways, intricate genomic alterations, substantial immune infiltration, and greater potential for immunotherapy efficacy. Consequently, TIICPS holds promise as a predictive tool for prognosis and immunotherapy response in ovarian cancer.

Comprehensive pan-cancer investigation: unraveling the oncogenic, prognostic, and immunological significance of Abelson interactor family member 3 gene in human malignancies

Background: Abelson interactor Family Member 3 (ABI3) encodes protein that not only suppresses the ectopic metastasis of tumor cells but also hinders their migration. Although ABI3 had been found to modulate the advancement of diverse neoplasms, there is no comprehensive pan-cancer analysis of its effects. Methods: The transcriptomics data of neoplasm and normal tissues were retrieved from the Genomic Data Commons (GDC) data portal, and UCSC XENA database. To gather protein information for ABI3, Human Protein Atlas (HPA) and GeneMANIA websites were utilized. Additionally, Tumor Immune Single-cell Hub (TISCH) database was consulted to determine the primary cell types expressing ABI3 in cancer microenvironments. Univariate Cox regression approach was leveraged to evaluate ABI3's prognostic role across cancers. The Cbioportal and Gene Set Cancer Analysis (GSCA) website were leveraged to scrutinize the genomic landscape information across cancers. TIMER2.0 was leveraged to probe the immune cell infiltrations associated with ABI3 across cancers. The associations of ABI3 with immune-related genes were analyzed through Spearman correlation method. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were utilized to search associated biological pathways. The CellMiner database and molecular docking were implemented to identify potential interactions between the ABI3 protein and specific anticarcinogen. Findings: ABI3 expression and its ability to predict prognosis varied distinct tumor, with particularly high expression observed in Tprolif cells and monocytes/macrophages. Copy number variation (CNV) and methylation negatively correlated with ABI3 expression in the majority of malignancies. Corresponding mutation survival analysis indicated that the mutation status of ABI3 was strongly connected to the prognosis of LGG patients. ABI3 expression was linked to immunotherapeutic biomarkers and response in cancers. ESTIMATE and immune infiltrations analyses presented ABI3 association with immunosuppression. ABI3 was significantly correlated with immunoregulators and immune-related pathways. Lastly, prospective ABI3-targeted drugs were filtered and docked to ABI3 protein. Interpretation: Our study reveals that ABI3 acts as a robust tumor biomarker. Its functions are vital that could inhibit ectopic metastasis of tumor cells and modulate cellular adhesion and migration. The discoveries presented here may have noteworthy consequences for the creation of fresh anticancer suppressors, especially those targeting BRCA.

PHF5A is a potential diagnostic, prognostic, and immunological biomarker in pan-cancer

Studying the molecular mechanisms and regulatory functions of genes is crucial for exploring new approaches and tactics in cancer therapy. Studies have shown that the aberrant expression of PHF5A in tumors is linked to the origin and advancement of multiple cancers. However, its role in diagnosis, prognosis, and immunological prediction has not been comprehensively investigated in a pan-cancer analysis. Using several bioinformatic tools, we conducted a systematic examination of the potential carcinogenesis of PHF5A in various tumors from multiple aspects. Our analysis indicated that PHF5A expression varied between normal and tumor tissues and was linked to clinical diagnosis and prognosis in various cancers. The results confirmed a notable variation in the levels of PHF5A promoter methylation among several types of primary tumor and normal tissues and methylation of the PHF5A promoter played a guiding role in prognosis in some cancers. According to our findings, PHF5A played a critical role in tumor immunity and it might be an excellent target for anticancer immunotherapy. To sum up, PHF5A can be used in pan-cancer diagnostics, prognostics, and immunotherapy.

Pan-cancer analysis of IFN-γ with possible immunotherapeutic significance: a verification of single-cell sequencing and bulk omics research

Background

Interferon-gamma (IFN-γ), commonly referred to as type II interferon, is a crucial cytokine that coordinates the tumor immune process and has received considerable attention in tumor immunotherapy research. Previous studies have discussed the role and mechanisms associated with IFN-γ in specific tumors or diseases, but the relevant role of IFN-γ in pan-cancer remains uncertain.

Methods

TCGA and GTEx RNA expression data and clinical data were downloaded. Additionally, we analyzed the role of IFN-γ on tumors by using a bioinformatic approach, which included the analysis of the correlation between IFN-γ in different tumors and expression, prognosis, functional status, TMB, MSI, immune cell infiltration, and TIDE. We also developed a PPI network for topological analysis of the network, identifying hub genes as those having a degree greater than IFN-γ levels.

Result

IFN-γ was differentially expressed and predicted different survival statuses in a majority of tumor types in TCGA. Additionally, IFN-γ expression was strongly linked to factors like infiltration of T cells, immune checkpoints, immune-activating genes, immunosuppressive genes, chemokines, and chemokine receptors, as well as tumor purity, functional statuses, and prognostic value. Also, prognosis, CNV, and treatment response were all substantially correlated with IFN-γ-related gene expression. Particularly, the IFN-γ-related gene STAT1 exhibited the greatest percentage of SNVs and the largest percentage of SNPs in UCEC. Elevated expression levels of IFN-γ-related genes were found in a wide variety of tumor types, and this was shown to be positively linked to drug sensitivity for 20 different types of drugs.

Conclusion

IFN-γ is a good indicator of response to tumor immunotherapy and is likely to limit tumor progression, offering a novel approach for immunotherapy's future development.

TERT expression is associated with metastasis from thin primaries, exhausted CD4+ T cells in melanoma and with DNA repair across cancer entities

Telomerase reverse transcriptase (TERT) promoter mutations occur frequently in cancer, have been associated with increased TERT expression and cell proliferation, and could potentially influence therapeutic regimens for melanoma. As the role of TERT expression in malignant melanoma and the non-canonical functions of TERT remain understudied, we aimed to extend the current knowledge on the impact of TERT promoter mutations and expression alterations in tumor progression by analyzing several highly annotated melanoma cohorts. Using multivariate models, we found no consistent association for TERT promoter mutations or TERT expression with the survival rate in melanoma cohorts under immune checkpoint inhibition. However, the presence of CD4+ T cells increased with TERT expression and correlated with the expression of exhaustion markers. While the frequency of promoter mutations did not change with Breslow thickness, TERT expression was increased in metastases arising from thinner primaries. As single-cell RNA-sequencing (RNA-seq) showed that TERT expression was associated with genes involved in cell migration and dynamics of the extracellular matrix, this suggests a role of TERT during invasion and metastasis. Co-regulated genes found in several bulk tumors and single-cell RNA-seq cohorts also indicated non-canonical functions of TERT related to mitochondrial DNA stability and nuclear DNA repair. This pattern was also evident in glioblastoma and across other entities. Hence, our study adds to the role of TERT expression in cancer metastasis and potentially also immune resistance.

Pan-cancer analysis of Homeobox B9 as a predictor for prognosis and immunotherapy in human tumors

BACKGROUND

Although several animal and cell studies have described the association between HOXB9 and cancers, there is no pan-cancer investigation of HOXB9. In this article, we explored the expression levels and prognosis of HOXB9 in pan-cancer. We evaluated the correlation of HOXB9 expression level with the efficacy of immunotherapy.

METHODS

We conducted a survival analysis of HOXB9 in various types of cancer using publicly available databases. We also examined the relationship between HOXB9 expression levels and several factors including prognosis, immune infiltration, immune checkpoint genes, tumor mutational burden, microsatellite instability, mismatch repair, and DNA methylation. TIMER2.0 tool was conducted to explore the immune cell infiltrations related to HOXB9 in this analysis.

RESULTS

It was discovered through a comprehensive analysis of multiple public datasets that HOXB9 expression was highly expressed in most tumor tissues and cancer cell lines and that distinct associations exist between HOXB9 expression and tumor patient prognosis. Besides, HOXB9 expression was closely associated with immune cell infiltration and checkpoint genes in many cancers. Further, HOXB9 was associated with immune cell infiltration, TMB, MSI, MMR, and DNA methylation. It was also confirmed that HOXB9 was highly expressed in clinical GBM tissues. Experiments further revealed that knockdown of HOXB9 expression could suppress proliferation, migration, and invasion of glioma cells.

CONCLUSIONS

The results revealed that HOXB9, a robust tumor biomarker, has a significant prognostic value. HOXB9 may act as a new predictor to assess cancer prognosis and therapeutic efficacy of the immune in various cancers.

Comprehensive pan-cancer analysis of PTGES3 and its prognostic role in hepatocellular carcinoma

Introduction

PTGES3, also known as p23, is a molecule chaperone of Hsp90 that is involved in the pathogenesis of malignant tumors. Increasing studies have shown that PTGES3 plays a nonnegligible role in tumor development. However, analysis of PTGES3 in pan-cancer has not been performed yet.

Methods

We explored the role of PTGES3 in 33 types of tumors and depicted the potentialimmune-related pathways among them. Using multiple databases includingTCGA, LinkedOmics, GDSC, and TIMER, we made a comprehensive analysis to explore whether there was an interaction between PTGES3 and prognosis, DNA methylation, copy number variation (CNV), tumor mutational burden (TMB), microsatellite instability (MSI), and tumor immune microenvironment (TME).

Results

Our study revealed that PTGES3 expression level was upregulated in most cancers. PTGES3 was also associated with a positive or negative prognosis in a variety of cancers, which was mainly associated with DNA methylation, CNV, MSI, TMB, andmismatch repair-related genes. High PTGES3 expression was related to the infiltration of Th2 subsets of CD4+ T cells and immune checkpoint-related genes in most cancers, especially in hepatocellular carcinoma (HCC). Enrichment analysis demonstrated that PTGES3 was involved in cellular processes including DNA replication and spliceosome. The relationship between PTGES3 expression and HCC progression was verified at the protein level through immune histochemical analysis.

Conclusions

Our research demonstrated theprognostic predictive value of PTGES3 in a wide range of cancers, which was alsoassociated with the process of tumor immune infiltration. As a result, it suggestedthat PTGES3 was a valuable prognostic biomarker in HCC treatment.

Multi-omics integration analysis of GPCRs in pan-cancer to uncover inter-omics relationships and potential driver genes

G protein-coupled receptors (GPCRs) are the largest drug target family. Unfortunately, applications of GPCRs in cancer therapy are scarce due to very limited knowledge regarding their correlations with cancers. Multi-omics data enables systematic investigations of GPCRs, yet their effective integration remains a challenge due to the complexity of the data. Here, we adopt two types of integration strategies, multi-staged and meta-dimensional approaches, to fully characterize somatic mutations, somatic copy number alterations (SCNAs), DNA methylations, and mRNA expressions of GPCRs in 33 cancers. Results from the multi-staged integration reveal that GPCR mutations cannot well predict expression dysregulation. The correlations between expressions and SCNAs are primarily positive, while correlations of the methylations with expressions and SCNAs are bimodal with negative correlations predominating. Based on these correlations, 32 and 144 potential cancer-related GPCRs driven by aberrant SCNA and methylation are identified, respectively. In addition, the meta-dimensional integration analysis is carried out by using deep learning models, which predict more than one hundred GPCRs as potential oncogenes. When comparing results between the two integration strategies, 165 cancer-related GPCRs are common in both, suggesting that they should be prioritized in future studies. However, 172 GPCRs emerge in only one, indicating that the two integration strategies should be considered concurrently to complement the information missed by the other such that obtain a more comprehensive understanding. Finally, correlation analysis further reveals that GPCRs, in particular for the class A and adhesion receptors, are generally immune-related. In a whole, the work is for the first time to reveal the associations between different omics layers and highlight the necessity of combing the two strategies in identifying cancer-related GPCRs.

Biomarkers and factors in small cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis

OBJECTIVE

The aim of this meta-analysis was to summarize the available results of immunotherapy predictors for small cell lung cancer (SCLC) and to provide evidence-based information for their potential predictive value of efficacy.

METHODS

We searched PubMed, EMBASE, Web of Science, The Cochrane Library, and ClinicalTrials (from January 1, 1975 to November 1, 2021). The hazard ratios (HR) and its 95% confidence intervals (CIs) and tumor response rate of the included studies were extracted.

RESULTS

Eleven studies were eventually included and the pooled results showed that programmed cell death ligand 1 (PD-L1) positive: objective response rate (ORR) (relative risk [RR] = 1.39, 95% CI [0.48, 4.03], p = 0.54), with high heterogeneity (p = 0.05, I²  = 56%); disease control rate [DCR] (RR = 1.31, 95% CI [0.04, 38.57], p = 0.88), with high heterogeneity (p = 0.04, I²  = 75%); overall survival (OS) (HR = 0.89, 95% CI [0.74, 1.07], p = 0.22); and progression-free survival (PFS) (HR = 0.83, 95% CI [0.59, 1.16], p = 0.27), with high heterogeneity (p = 0.005, I²  = 73.1%). TMB-High (TMB-H): OS (HR = 0.86, 95% CI [0.74, 1.00], p = 0.05); PFS (HR = 0.71, 95% CI [0.6, 0.85], p < 0.001). Lactate dehydrogenase (LDH) >upper limit of normal (ULN): OS (HR = 0.95, 95% CI [0.81, 1.11], p = 0.511). Asian patients: OS (HR = 0.87, 95% CI [0.72, 1.04], p = 0.135); White/Non-Asian patients: OS (HR = 0.83, 95% CI [0.76, 0.90], p < 0.001). Liver metastasis patients: OS (HR = 0.93, 95% CI [0.83, 1.05], p = 0.229); PFS (HR = 0.84, 95% CI [0.67, 1.06], p = 0.141). Central nervous system (CNS) metastasis patients: OS (HR = 0.91, 95% CI [0.71, 1.17], p = 0.474); PFS (HR = 1.03, 95% CI [0.66, 1.60], p = 0.903).

CONCLUSION

The available research results do not support the recommendation of PD-L1 positive and TMB-H as predictors for the application of immune checkpoint inhibitors (ICIs) in SCLC patients. LDH, baseline liver metastasis and CNS metastasis may be used as markers/influencing factors for predicting the efficacy of ICIs in SCLC patients. Non-Asian SCLC patients had better efficacy with ICIs in our results.

Influence of Genomic Landscape on Cancer Immunotherapy for Newly Diagnosed Ovarian Cancer: Biomarker Analyses from the IMagyn050 Randomized Clinical Trial

PURPOSE

To explore whether patients with BRCA1/2-mutated or homologous recombination deficient (HRD) ovarian cancers benefitted from atezolizumab in the phase III IMagyn050 (NCT03038100) trial.

PATIENTS AND METHODS

Patients with newly diagnosed ovarian cancer were randomized to either atezolizumab or placebo with standard chemotherapy and bevacizumab. Programmed death-ligand 1 (PD-L1) status of tumor-infiltrating immune cells (IC) was determined centrally (VENTANA SP142 assay). Genomic alterations, including deleterious BRCA1/2 alterations, genomic loss of heterozygosity (gLOH), tumor mutation burden (TMB), and microsatellite instability (MSI), were evaluated using the FoundationOne assay. HRD was defined as gLOH ≥ 16%, regardless of BRCA1/2 mutation status. Potential associations between progression-free survival (PFS) and genomic biomarkers were evaluated using standard correlation analyses and log-rank of Kaplan-Meier estimates.

RESULTS

Among biomarker-evaluable samples, 22% (234/1,050) harbored BRCA1/2 mutations and 46% (446/980) were HRD. Median TMB was low irrespective of BRCA1/2 or HRD. Only 3% (29/1,024) had TMB ≥10 mut/Mb, and 0.3% (3/1,022) were MSI-high. PFS was better in BRCA2-mutated versus BRCA2-non-mutated tumors and in HRD versus proficient tumors. PD-L1 positivity (≥1% expression on ICs) was associated with HRD but not BRCA1/2 mutations. PFS was not improved by adding atezolizumab in BRCA2-mutated or HRD tumors; there was a trend toward enhanced PFS with atezolizumab in BRCA1-mutated tumors.

CONCLUSIONS

Most ovarian tumors have low TMB despite BRCA1/2 mutations or HRD. Neither BRCA1/2 mutation nor HRD predicted enhanced benefit from atezolizumab. This is the first randomized double-blind trial in ovarian cancer demonstrating that genomic instability triggered by BRCA1/2 mutation or HRD is not associated with improved sensitivity to immune checkpoint inhibitors. See related commentary by Al-Rawi et al., p. 1645.

A pan-cancer analysis identifies SOAT1 as an immunological and prognostic biomarker

Sterol o-acyltransferase1 (SOAT1) is an enzyme that regulates lipid metabolism. Nevertheless, the predictive value of SOAT1 regarding immune responses in cancer is not fully understood. Herein, we aimed to expound the predictive value and the potential biological functions of SOAT1 in pan-cancer. Raw data related to SOAT1 expression in 33 different types of cancer were acquired from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. SOAT1 expression was significantly increased in most cancers and showed a distinct correlation with prognosis. This enhanced expression of the SOAT1 gene was confirmed by evaluating SOAT1 protein expression using tissue microarrays. In addition, we found significant positive associations between SOAT1 expression levels and infiltrating immune cells, including T cells, neutrophils, and macrophages. Moreover, the co-expression analysis between SOAT1 and immune genes showed that many immune-related genes were increased with enhanced SOAT1 expression. A gene set enrichment analysis (GSEA) revealed that the expression of SOAT1 correlated with the tumor microenvironment, adaptive immune response, interferon signaling, and cytokine signaling. These findings indicate that SOAT1 is a potential candidate marker for predicting prognosis and a promising target for tumor immunotherapy in cancers.

Prognostic value of pretreatment immune inflammation indices in patients with immune-related tumors

BACKGROUND

Pretreatment high levels of lactate dehydrogenase (LDH), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), modified Glasgow prognostic scores (mGPS), prognostic nutritional index (PNI), and other prognostic biomarkers have been associated with poor overall survival (OS) in immune-related tumor types. Therefore, we explored a simple, inexpensive and effective method for cancer prognosis.

METHODS

Between March 2017 and June 2022, 111 individuals who had immunotherapy were retrospectively examined. Oncologic outcomes of patients with immune-related tumor types, include OS and progression-free survival (PFS), and response rates (RR).

RESULTS

Pretreatment ECOG (Eastern Cooperative Oncology Group) performance quality was independently linked with poor OS ECOG ≥2 (HR 4.80, 95% CI 2.57-8.96, p < .001) and inferior PFS (HR 3.31, 95% CI 2.023-5.445, p < .001). Additionally, a high LDH status prior to therapy was independently linked to an inferior OS (HR 1.004, 95% CI 1.001-1.007, p = .003) and inferior PFS (HR 1.004, 95% CI 1.002-1.006, p < .001). Higher MLR at baseline was a prognostic factor for both shorter PFS (HR = 3.691, 95% CI 1.582-8.610, p = .003) and OS (HR = 2.876, 95% CI 1.127-7.342, p = .027).

CONCLUSIONS

In our cohort, elevated pre-treatment MLR, LDH and ECOG ≥2 were associated with poor OS and PFS. Prospective studies need to determine the utility of them.

Immune checkpoint PTPN2 predicts prognosis and immunotherapy response in human cancers

Background

PTPN2, a member of the non-receptor protein tyrosine phosphatases family, holds a crucial role in tumorigenesis and cancer immunotherapy. However, most studies on the role of PTPN2 in cancer are limited to specific cancer types. Therefore, this study aimed to investigate the prognostic significance of PTPN2 in human cancers and its function in the tumor microenvironment.

Methods

To shed light on this matter, we investigated the expression level, prognostic value, genomic alterations, molecular function, immune function, and immunotherapeutic predictive ability of PTPN2 in human cancers using the TCGA, GTEx, CGGA, GEO, cBioPortal, STRING, TISCH, TIMER2.0, ESTIMATE, and TIDE databases. Furthermore, the CCK-8 assay was utilized to detect the effect of PTPN2 on cell proliferation. Cell immunofluorescence analysis was performed to probe the cellular localization of PTPN2. Western blot was applied to examine the molecular targets downstream of PTPN2. Finally, a Nomogram model was constructed using the TCGA-LGG cohort and evaluated with calibration curves and time-dependent ROCs.

Results

PTPN2 was highly expressed in most cancers and was linked to poor prognosis in ACC, GBM, LGG, KICH, and PAAD, while the opposite was true in OV, SKCM, and THYM. PTPN2 knockdown promoted the proliferation of melanoma cells, while significantly inhibiting proliferation in colon cancer and glioblastoma cells. In addition, TC-PTP, encoded by the PTPN2 gene, was primarily localized in the nucleus and cytoplasm and could negatively regulate the JAK/STAT and MEK/ERK pathways. Strikingly, PTPN2 knockdown significantly enhanced the abundance of PD-L1. PTPN2 was abundantly expressed in Mono/Macro cells and positively correlated with multiple immune infiltrating cells, especially CD8⁺ T cells. Notably, DLBC, LAML, OV, and TGCT patients in the PTPN2-high group responded better to immunotherapy, while the opposite was true in ESCA, KIRC, KIRP, LIHC, and THCA. Finally, the construction of a Nomogram model on LGG exhibited a high prediction accuracy.

Conclusion

Immune checkpoint PTPN2 is a powerful biomarker for predicting prognosis and the efficacy of immunotherapy in cancers. Mechanistically, PTPN2 negatively regulates the JAK/STAT and MEK/ERK pathways and the abundance of PD-L1.

Genomic Signatures from Clinical Tumor Sequencing in Patients with Breast Cancer Having Germline BRCA1/2 Mutation

PURPOSE

BRCA1 and BRCA2 are among the most important genes involved in DNA repair via homologous recombination (HR). Germline BRCA1/2 (gBRCA1/2)-related cancers have specific characteristics and treatment options but conducting gBRCA1/2 testing and interpreting the genetic imprint are sometimes complicated. Here, we describe the concordance of gBRCA1/2 derived from a panel of clinical tumor tissues using next-generation sequencing (NGS) and genetic aspects of tumors harboring gBRCA1/2 pathogenic variants.

MATERIALS AND METHODS

Targeted sequencing was performed using available tumor tissue from patients who underwent gBRCA1/2 testing. Comparative genomic analysis was performed according to gBRCA1/2 pathogenicity.

RESULTS

A total of 321 patients who underwent gBRCA1/2 testing were screened, and 26 patients with gBRCA1/2 pathogenic (gBRCA1/2p) variants, eight patients with gBRCA1/2 variants of uncertain significance (VUS; gBRCA1/2v), and 43 patients with gBRCA1/2 wild-type (gBRCA1/2w) were included in analysis. Mutations in TP53 (49.4%) and PIK3CA (23.4%) were frequently detected in all samples. The number of single-nucleotide variants (SNVs) per tumor tissue was higher in the gBRCA1/2w group than that in the gBRCA1/2p group (14.81 vs. 18.86, p=0.278). Tumor mutation burden (TMB) was significantly higher in the gBRCA1/2w group than in the gBRCA1/2p group (10.21 vs. 13.47, p=0.017). Except for BRCA1/2, other HR-related genes were frequently mutated in patients with gBRCA1/2w.

CONCLUSION

We demonstrated high sensitivity of gBRCA1/2 in tumors analyzed by NGS using a panel of tumor tissues. TMB value and aberration of non-BRCA1/2 HR-related genes differed significantly according to gBRCA1/2 pathogenicity in patients with breast cancer.

Diabetes mellitus induces a novel inflammatory network involving cancer progression: Insights from bioinformatic analysis and in vitro validation

Background

Patients with diabetes mellitus (DM) have a higher incidence of malignant tumors than people without diabetes, but the underlying molecular mechanisms are still unclear.

Methods

To investigate the link between DM and cancer, we screened publicly available databases for diabetes and cancer-related genes (DCRGs) and constructed a diabetes-based cancer-associated inflammation network (DCIN). We integrated seven DCRGs into the DCIN and analyzed their role in different tumors from various perspectives. We also investigated drug sensitivity and single-cell sequencing data in colon adenocarcinoma as an example. In addition, we performed in vitro experiments to verify the expression of DCRGs and the arachidonic acid metabolic pathway.

Results

Seven identified DCRGs, including PPARG, MMP9, CTNNB1, TNF, TGFB1, PTGS2, and HIF1A, were integrated to construct a DCIN. The bioinformatics analysis showed that the expression of the seven DCRGs in different tumors was significantly different, which had varied effects on diverse perspectives. Single-cell sequencing analyzed in colon cancer showed that the activity of the DCRGs was highest in Macrophage and the lowest in B cells among all cell types in adenoma and carcinoma tissue. In vitro experiments showed that the DCRGs verified by western bolt and PEG2 verified by ELISA were all highly expressed in COAD epithelial cells stimulated by high glucose.

Conclusion

This study, for the first time, constructed a DCIN, which provides novel insights into the underlying mechanism of how DM increases tumor occurrence and development. Although further research is required, our results offer clues for new potential therapeutic strategies to prevent and treat malignant tumors.

A novel natural killer cell-related signatures to predict prognosis and chemotherapy response of pancreatic cancer patients

Background: Natural killer (NK) cells are involved in monitoring and eliminating cancers. The purpose of this study was to develop a NK cell-related genes (NKGs) in pancreatic cancer (PC) and establish a novel prognostic signature for PC patients. Methods: Omic data were downloaded from The Cancer Genome Atlas Program (TCGA), Gene Expression Omnibus (GEO), International Cancer Genome Consortium (ICGC), and used to generate NKG-based molecular subtypes and construct a prognostic signature of PC. NKGs were downloaded from the ImmPort database. The differences in prognosis, immunotherapy response, and drug sensitivity among subtypes were compared. 12 programmed cell death (PCD) patterns were acquired from previous study. A decision tree and nomogram model were constructed for the prognostic prediction of PC. Results: Thirty-two prognostic NKGs were identified in PC patients, and were used to generate three clusters with distinct characteristics. PCD patterns were more likely to occur at C1 or C3. Four prognostic DEGs, including MET, EMP1, MYEOV, and NGFR, were found among the clusters and applied to construct a risk signature in TCGA dataset, which was successfully validated in PACA-CA and GSE57495 cohorts. The four gene expressions were negatively correlated with methylation level. PC patients were divided into high and low risk groups, which exerts significantly different prognosis, clinicopathological features, immune infiltration, immunotherapy response and drug sensitivity. Age, N stage, and the risk signature were identified as independent factors of PC prognosis. Low group was more easily to happened on PCD. A decision tree and nomogram model were successfully built for the prognosis prediction of PC patients. ROC curves and DCA curves demonstrated the favorable and robust predictive capability of the nomogram model. Conclusion: We characterized NKGs-derived molecular subtypes of PC patients, and established favorable prognostic models for the prediction of PC prognosis, which may serve as a potential tool for prognosis prediction and making personalized treatment in PC.

Comprehensive genomics analysis of aging related gene signature to predict the prognosis and drug resistance of colon adenocarcinoma

Background: Colon adenocarcinoma (COAD) is a heterogeneous tumor and senescence is crucial in the occurrence of cancer. This study aimed to identify senescence-based subtypes and construct a prognostic signature to predict the prognosis and guide immunotherapy or chemotherapy decisions for COAD patients. Methods: Based on the single-cell RNA sequencing (scRNA-seq) data of 13 samples from the Gene Expression Omnibus (GEO) database, we assessed cellular senescence characteristics. Transcriptome data, copy number variations (CNVs) and single nucleotide variations (SNVs) data were obtained from The Cancer Genome Atlas (TCGA) database. GSE39582 and GSE17537 were used for validation. Senescence subtypes were identified using unsupervised consensus clustering analysis, and a prognostic signature was developed using univariate Cox analysis and least absolute shrinkage and selection operator (LASSO). Response of risk groups to chemotherapy was predicted using the half-maximal inhibitory concentration (IC50) values. We further analyzed the relationship between risk gene expression and methylation level. The prediction performance was assessed by nomogram. Results: Senescence-related pathways were highly enriched in malignant cells and bulk RNA-seq verified cellular senescence. Three senescence subtypes were identified, in which patients in clust3 had poorest prognosis and higher T stage, accompanied with higher tumor mutation burden (TMB) and mutations, activated inflammatory response, more immune cell infiltration, and higher immune escape tendency. A senescence-based signature using 11 genes (MFNG, GPRC5B, TNNT1, CCL22, NOXA1, PABPC1L, PCOLCE2, MID2, CPA3, HSPA1A, and CALB1) was established, and accurately predicted a lower prognosis in high risk patients. Its robustness was validated by external cohort. Low risk patients were more sensitive to small molecule drugs including Erlotinib, Sunitinib, MG-132, CGP-082996, AZ628, Sorafenib, VX-680, and Z-LLNle-CHO. Risk score was an independent prognostic factor and nomogram confirmed its reliability. Four risk genes (CALB1, CPA3, NOXA1, and TNNT1) had significant positive correlation with their methylation level, while six genes (CCL22, GPRC5B, HSPA1A, MFNG, PABPC1L, and PCOLCE2) were negatively correlated with their methylation level. Conclusion: This study provides novel understanding of heterogeneity in COAD from the perspective of senescence, and develops signatures for prognosis prediction in COAD.

Implementation of Comprehensive Genomic Profiling in Ovarian Cancer Patients: A Retrospective Analysis

Comprehensive genomic profiling (CGP) allows for the detection of driver alterations at high resolution, but the limited number of approved targeted therapies and their high costs have contributed to its limited clinical utilization. We retrospectively compared data of 946 women with ovarian cancer (11.4% were referred to CGP, and 88.6% served as control) to examine whether CGP provides a prognosis benefit. Patient baseline parameters were similar between the groups. Cox regression analysis adjusted for age, disease stage at diagnosis, and recurrence status showed statistically significantly longer median overall survival (mOS) in the CGP group versus the control (73.4 versus 54.5 months, p < 0.001). Fifty-four patients (52.9%) had actionable mutations with potential treatments; twenty-six (48.2%) were treated with matched targeted therapy, showing a trend for longer mOS than the eighty-six women in the CGP group who were not given a suggested treatment (105.5 versus 63.6 months, p = 0.066). None of the genomic alterations predicted metastasis location. CCNE1 amplification and KRAS mutations were associated with shorter mOS. Patients with tumor mutation burden ≥4 mutations/megabase had longer mOS. High loss of heterozygosity was associated with longer mOS (99.0 versus 48.2 months, p = 0.004). CGP testing may provide both prognostic and predictive insights for treatment of patients with ovarian cancer. Prospective studies of larger cohorts are warranted.

A bile acid-related prognostic signature in hepatocellular carcinoma

Due to the high mortality of hepatocellular carcinoma (HCC), its prognostic models are urgently needed. Bile acid (BA) metabolic disturbance participates in hepatocarcinogenesis. We aim to develop a BA-related gene signature for HCC patients. Research data of HCC were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) online databases. After least absolute shrinkage and selection operator (LASSO) regression analysis, we developed a BA-related prognostic signature in TCGA cohort based on differentially expressed prognostic BA-related genes. Then, the predictive performance of the signature was evaluated and verified in TCGA and ICGC cohort respectively. We obtained the risk score of each HCC patient according to the model. The differences of immune status and drug sensitivity were compared in patients that were stratified based on risk score. The protein and mRNA levels of the modeling genes were validated in the Human Protein Atlas database and our cell lines, respectively. In TCGA cohort, we selected 4 BA-related genes to construct the first BA-related prognostic signature. The risk signature exhibited good discrimination and predictive ability, which was verified in ICGC cohort. Patients were classified into high- and low-risk groups according to their median scores. The occurrence of death increased with increasing risk score. Low-risk patients owned favorable overall survival. High-risk patients possessed high immune checkpoint expression and low IC50 values for sorafenib, cisplatin and doxorubicin. Real-time quantitative PCR and immunohistochemical results validate expression of modeling genes in the signature. We constructed the first BA-related gene signature, which might help to identify HCC patients with poor prognosis and guide individualized treatment.

Spatial heterogeneity of infiltrating T cells in high-grade serous ovarian cancer revealed by multi-omics analysis

Tumor-infiltrating lymphocytes (TILs), especially CD8⁺ TILs, represent a favorable prognostic factor in high-grade serous ovarian cancer (HGSOC) and other tumor lineages. Here, we analyze the spatial heterogeneity of different TIL subtypes in HGSOC. We integrated RNA sequencing, whole-genome sequencing, bulk T cell receptor (TCR) sequencing, as well as single-cell RNA/TCR sequencing to investigate the characteristics and differential composition of TILs across different HGSOC sites. Two immune "cold" patterns in ovarian cancer are identified: (1) ovarian lesions with low infiltration of mainly dysfunctional T cells and immunosuppressive Treg cells and (2) omental lesions infiltrated with non-tumor-specific bystander cells. Exhausted CD8 T cells that are preferentially enriched in ovarian tumors exhibit evidence for expansion and cytotoxic activity. Inherent tumor immune microenvironment characteristics appear to be the main contributor to the spatial differences in TIL status. The landscape of spatial heterogeneity of TILs may inform potential strategies for therapeutic manipulation in HGSOC.

Tumor mutation burden involving epigenetic regulatory genes and the RhoA GTPase predicts overall survival in nodal mature T-cell lymphomas

Nodal mature T-cell lymphomas (nMTCL) comprises a heterogeneous group of rare malignancies with aggressive biological behavior and poor prognosis. Epigenetic phenomena, including mutations in genes that control DNA methylation and histone deacetylation, in addition to inactivating mutations in the RhoA GTPase, play a central role in its pathogenesis and constitute potential new targets for therapeutic intervention. Tumor mutational burden (TMB) reflects the process of clonal evolution, predicts response to anti-cancer therapies and has emerged as a prognostic biomarker in several solid neoplasms; however, its potential prognostic impact remains unknown in nMTCL. In this study, we conducted Sanger sequencing of formalin-fixed paraffin-embedded (FFPE) diagnostic tumor samples using a target-panel to search for recurrent mutations involving the IDH-1/IDH-2, TET-2, DNMT3A and RhoA genes in 59 cases of nMTCL. For the first time, we demonstrated that high-TMB, defined by the presence of ≥ two mutations involving the aforementioned genes, was associated with decreased overall survival in nMTCL patients treated with CHOP-like regimens. Additionally, high-TMB was correlated with bulky disease, lower overall response rate, and higher mortality. Future studies using larger cohorts may validate our preliminary results that indicate TMB as a potential molecular biomarker associated with adverse prognosis in nMTCL.

Prognostic value and immunological role of Kruppel-like transcription factor 9 gene in pan-carcinoma

OBJECTIVE

To investigate the correlation between the expression of Kruppel-like transcription factor 9 (KLF9) and the prognostic value of tumors as well as its relationship with tumor immune invasion.

METHODS

A series of bioinformatics methods were used to analyze the relationship between KLF9 and tumor prognosis, tumor mutation burden, microsatellite instability (MSI), and immune cell infiltration in multiple carcinomas.

RESULTS

In multiple tumor tissues, the expression of KLF9 was lower compared with paracancerous tissues. Therefore, KLF9 can serve as a protective factor to improve the prognosis of carcinoma patients with certain tumor types. KLF9 was closely related to the clinical staging of various carcinomas. The expression of KLF9 was not only associated with tumor mutation burden and MSI in some tumor types, but also positively correlated with immune and stromal cells in multiple tumors. Further studies have found that, the level of immune cell infiltration was significantly related to the expression of KLF9.

CONCLUSION

KLF9 can affect the prognosis of pan-carcinoma, which is related to immune invasion. Therefore, KLF9 can be used as a potential biomarker for the prognosis of pan-carcinoma.

A pan-cancer analysis of the oncogenic role of zinc finger protein 419 in human cancer

Background

As a ferroptosis-related gene, the polymorphism of zinc finger protein 419 (ZNF419) at the splice donor site may generate renal cell carcinoma-associated novel minor histocompatibility antigen ZAPHIR. However, the role of ZNF419 in prognosis and immunology in human tumors remains largely unknown. This study aimed to visualize the prognostic landscape of ZNF419 at pan-cancer level and explore the relationship between ZNF419 expression and the tumor immune microenvironment.

Method

Pan-cancer and mutation data were downloaded from TCGA databases and analyzed through R (version 3.6.4) and its suitable packages. Differential ZNF419 expression and prognosis were analyzed. Correlations with ferroptosis-related genes, pathway analysis, tumor stemness, heterogeneity, mutation landscape, and RNA modifications were also explored. The relationships between ZNF419 expression and tumor immunity were investigated through the TIMER and ESTIMATE methods.

Result

ZNF419 was differentially expressed between tumor and normal samples and was associated with overall survival, disease-specific survival and progression-free interval for STES, KIRC, LIHC, LUSC, PRAD, and BLCA. We found the interaction between ZNF419 and FANCD2 might involve in ferroptosis in pan-cancer level. In addition, the mutation frequencies of STES, KIRC, LIHC, LUSC, PRAD, and BLCA were 1.5%, 0.3%, 0.3%, 1.9%, 0.2%, and 0.7%, respectively. We detected that the expression of ZNF419 was closely correlated with most immune checkpoint genes and immune regulatory genes. Furthermore, we found that the ZNF419 expression level was negatively related to the immune score in the six cancers mentioned above. The expression of ZNF419 was significantly associated with various infiltrating immune cells, such as CD4+ T cells, CD8+ T cells, and macrophages in patients with KIRC, PRAD, and LUSC but was only significantly related to macrophages in BLCA patients.

Conclusion

ZNF419 might serve as a potential prognostic and immunological pan-cancer biomarker, especially for KIRC, LIHC, LUSC, PRAD, and BLCA.

Pan-Cancer analysis shows that ACO2 is a potential prognostic and immunotherapeutic biomarker for multiple cancer types including hepatocellular carcinoma

BACKGROUND

Recent evidence increasingly suggests key roles for the tricarboxylic acid cycle and fatty acid metabolism in tumor progression and metastasis. Aconitase 2 (ACO2) is a component of the tricarboxylic acid cycle and represents a key cellular metabolic hub that promotes de novo fatty acid biosynthesis. However, there have been few reports on the role of ACO2 in tumorigenesis and cancer progression.

METHODS

Through the comprehensive use of datasets from The Cancer Genome Atlas, Genotype-Tissue Expression Project, cBioPortal, Human Protein Atlas, UALCAN, Gene Expression Profiling Interactive Analysis, DNA Methylation Interactive Visualization Database, and TIMER2, we adopted bioinformatics methods to uncover the potential carcinogenic roles of ACO2, including by analysing ACO2 expression and correlations between prognosis, genetic mutations, immune cell infiltration, DNA methylation, tumor mutational burden, and microsatellite instability in different tumors. Additionally, the expression level and tumor-promoting effect of ACO2 were verified in hepatocellular carcinoma (HCC) cells. To explore the underlying mechanisms of ACO2 in human cancer, ACO2-related gene enrichment analysis and lipid metabolomics were performed using LM3 cells with or without ACO2 knockdown.

RESULTS

The results indicated that ACO2 was highly expressed in most cancers, showing early diagnostic value in six tumor types, and was positively or negatively associated with prognosis in different tumors. Moreover, ACO2 expression was associated with immune cell infiltration, such as CD8+ T cells and tumor-associated neutrophils, in some cancers. For most cancer types, there was a significant association between immune checkpoint-associated genes and ACO2 expression. Compared with normal hepatocytes, ACO2 was upregulated in HCC cells, which promoted their proliferation and migration. Furthermore, to explore the underlying molecular mechanism, we performed KEGG pathway enrichment analysis of ACO2-associated genes and lipidomics using LM3 cells with or without ACO2 knockdown, which screened 19 significantly altered metabolites, including 17 with reduced levels and 2 with increased levels.

CONCLUSION

Through pan-cancer analysis, we discovered for the first time and verified that ACO2 could be a useful diagnostic biomarker for cancer detection. Additionally, ACO2 could be used as an auxiliary prognostic marker or as a marker for immunotherapy in some tumor types.

Cuproptosis key gene FDX1 is a prognostic biomarker and associated with immune infiltration in glioma

Recent studies have found that the protein encoded by the FDX1 gene is involved in mediating Cuproptosis as a regulator of protein lipoylation and related to immune response process of tumors. However, the specific biological function of FDX1 in glioma is currently unclear. To explore the potential function of FDX1, this study explored the correlation between the expression of FDX1 in cancers and survival prognosis by analyzing the public databases of GEPIA and Cbioportal. Immune infiltration was analyzed by the TIMER2.0 database in tumors. The possible biological processes and functions of FDX1-related in glioma were annotated through gene enrichment. Relationship between Cuproptosis and autophagy was explored through gene co-expression studies. Summary and conclusions of this study: (1) FDX1 is highly expressed in gliomas and associated with poor prognosis in low-grade gliomas (LGG). (2) Gene annotation indicates that FDX1 is mainly involved in the tumor protein lipoylation and cell death. (3) FDX1 expression is positively correlated with the infiltration of immune cells. (4) LIPT2 and NNAT, two other genes involved in lipoylation, may be unidentified marker gene for Cuproptosis. And the Cuproptosis genes related to FDX1 were positively correlated with the expression of autophagy marker genes Atg5, Atg12, and BECN-1. This evidence suggests that there may be some interaction between FDX1 mediated Cuproptosis and autophagy. In summary, FDX1 may serve as a potential immunotherapy target and prognostic marker for Glioma.

Identification and validation of transferrin receptor protein 1 for predicting prognosis and immune infiltration in lower grade glioma

INTRODUCTION

Transferrin receptor protein 1 (TFRC), an ananda molecule associated with ferroptosis, has been identified as affecting a wide spectrum of pathological processes in various cancers, but the prognostic value correlates with the tumor microenvironment of TFRC in lower-grade glioma (LGG) is still unclear.

MATERIALS AND METHODS

Clinical pathological information and gene expression data of patients with LGG come from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), GTEx, Oncomine, UCSC Xena, and GEO databases. We then used various bioinformatics methods and mathematical models to analyze those data, aiming to investigate the clinical significance of TFRC in LGG and illustrate its association with tumor immunity. In addition, the molecular function and mechanisms of TFRC were revealed by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA). Immunohistochemical experiments and single-cell analysis have been performed.

RESULTS

TFRC expression was highly expressed in many tumors and showed a poor prognosis. Including gliomas, it was significantly associated with several poor clinical prognostic variables, tumor immune microenvironment, tumor mutational burden (TMB), m6a modification, and ferroptosis in LGG. TFRC as a key factor was further used to build a prediction nomogram. The C-index, calibration curve, and decision curve analysis showed the nomogram was clinically useful and calibration was accurate. At the same time, we also demonstrated that promoter hypomethylation of DNA upstream of TFRC could lead to high TFRC expression and poor overall survival. There is a significant correlation between TFRC and CD8 + T cell, macrophage cell infiltration, and several immune checkpoints, such as PD-L1(cd274), CTLA4, and PD1, suggesting a novel direction for future clinical application. Functional and molecular mechanism analysis showed an association of TFRC expression with immune-related pathways through GSEA, GO, and KEGG analysis. Finally, immunohistochemical experiments and single-cell analysis confirmed the expression of TFRC in glioma.

CONCLUSION

TFRC may be a potential prognostic biomarker and an immunotherapeutic target for glioma.

The role of YAP1 in survival prediction, immune modulation, and drug response: A pan-cancer perspective

Introduction

Dysregulation of the Hippo signaling pathway has been implicated in multiple pathologies, including cancer, and YAP1 is the major effector of the pathway. In this study, we assessed the role of YAP1 in prognostic value, immunomodulation, and drug response from a pan-cancer perspective.

Methods

We compared YAP1 expression between normal and cancerous tissues and among different pathologic stages survival analysis and gene set enrichment analysis were performed. Additionally, we performed correlation analyses of YAP1 expression with RNA modification-related gene expression, tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoint regulator expression, and infiltration of immune cells. Correlations between YAP1 expression and IC50s (half-maximal inhibitory concentrations) of drugs in the CellMiner database were calculated.

Results

We found that YAP1 was aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications, particularly m6A methylation. High expression of YAP1 was associated with poor survival outcomes in ACC, BLCA, LGG, LUAD, and PAAD. YAP1 expression was negatively correlated with the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, and positively correlated with the infiltration of myeloid-derived suppressor cells (MDSCs) and cancer-associated fibroblasts (CAFs) in pan-cancer. Higher YAP1 expression showed upregulation of TGF-β signaling, Hedgehog signaling, and KRAS signaling. IC50s of FDA-approved chemotherapeutic drugs capable of inhibiting DNA synthesis, including teniposide, dacarbazine, and doxorubicin, as well as inhibitors of hypoxia-inducible factor, MCL-1, ribonucleotide reductase, and FASN in clinical trials were negatively correlated with YAP1 expression.

Discussion

In conclusion, YAP1 is aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications. High expression of YAP1 is associated with poor survival outcomes in certain cancer types. YAP1 may promote tumor progression through immunosuppression, particularly by suppressing the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, as well as recruiting MDSCs and CAFs in pan-cancer. The tumor-promoting activity of YAP1 is attributed to the activation of TGF-β, Hedgehog, and KRAS signaling pathways. AZD2858 and varlitinib might be effective in cancer patients with high YAP1 expression.

Exploitation of tumor antigens and construction of immune subtype classifier for mRNA vaccine development in bladder cancer

Background

Bladder cancer (BLCA) is one of the most prevalent urinary system malignancies, with high mortality and recurrence. The present study aimed to identify potential tumor antigens for mRNA vaccines in BLCA and patient subtypes suitable for different immunotherapy.

Methods

Gene expression profiles, mutation data, methylation data, and corresponding clinical information were obtained from the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and ArrayExpress databases. Immunohistochemical staining of microarrays was performed to assess protein expression levels of IGF2BP2 and MMP9. Differential gene analysis, survival analysis, correlation analysis, consensus clustering analysis, and immune cell infiltration analysis were conducted using R software. Finally, the R package "immcluster" was used based on Combat and eXtreme Gradient Boosting algorithms to predict immune clusters of BLCA samples.

Results

Two mutated, amplified, and over-expressed tumor antigens, IGF2BP2 and MMP9, were found to be associated with clinical outcomes and the abundance of antigen-presenting cells (APCs). Subsequently, three immune subtypes (BIS1, BIS2, and BIS3) were defined in the BLCA cohort. BIS3 subtype exhibited an "active" immune phenotype, while BIS1 and BIS2 subtypes have a "suppressive" immune phenotype. Patients in BIS1 and BIS2 had a poor prognosis compared to BIS3. BIS3 had a higher score in checkpoints or immunomodulators (CP) and immunophenoscore (IPS), while BIS1 and BIS2 scored higher in major histocompatibility complex-related molecules (MHC molecules). Meanwhile, BIS2 and BIS3 had a significantly higher tumor mutational burden (TMB) compared to patients with BIS1. Finally, the "immcluster" package was applied to the dataset, which has been shown to accurately predict the immune subtypes of BLCA samples in many cohorts.

Conclusions

IGF2BP2 and MMP9 were potential antigens for developing mRNA vaccines against BLCA. The results in the present study suggested that immunotherapy targeting these two antigens would be suitable for patients falling under the BIS2 subtype. R package "immcluster" could assist in screening suitable BLCA patients for antitumor therapy.

Prognosis Risk Model Based on Necroptosis-Related Signature for Bladder Cancer

Background: Bladder cancer(BLCA) is the ninth most common cancer. In recent years, necroptosis was found to be related to the occurrence and development of tumors. In this study, we aimed to construct a model based on a necroptosis-related signature to evaluate the potential prognostic application in BLCA. Methods: A total of 67 necroptosis-related genes were used to select the ideal cluster numbers, and it was found that there were four necroptosis-related patterns. Then, we compared the gene expression levels among all of the groups and established a necroptosis-related prognostic model. We made the following enrichment analysis of function and built a novel scoring system, the NEC score, to evaluate the state of necroptosis according to the expression level of necroptosis-related genes. Results: A total of 67 necroptosis-related genes were used to define four distinct necroptosis-related patterns: NEC cluster1–4. Each NEC cluster exhibited different patterns of survival and immune infiltration. Based on univariate Cox regression analyses and least absolute shrinkage and selection operator (Lasso) regression, 14 necroptosis-related genes were established to develop the NEC score. Patients were divided into two groups based on the NEC score. Patients in the high NEC score group had a significantly poorer overall survival than those in the low NEC score group. We further confirmed the correlation of clinical characteristics, as well as the immunotherapy outcome, with the NEC score, and confirmed the potential of the NEC score to be an independent prognostic factor. Furthermore, we compared the expression levels of eight potential biomarker genes between our own BLCA tissues and para-carcinoma tissue. Conclusion: We developed a novel NEC score that has a potential prognostic value in BLCA patients and may help personalized immunotherapy counselling.

EZH2 as a Prognostic Factor and Its Immune Implication with Molecular Characterization in Prostate Cancer: An Integrated Multi-Omics in Silico Analysis

Prostate cancer (PCa) is a type of potentially fatal malignant tumor. Immunotherapy has shown a lot of potential for various types of solid tumors, but the benefits have been less impressive in PCa. Enhancer of zeste homolog 2 (EZH2) is one of the three core subunits of the polycomb repressive complex 2 that has histone methyltransferase activity, and the immune effects of EZH2 in PCa are still unclear. The purpose of this study was to explore the potential of EZH2 as a prognostic factor and an immune therapeutic biomarker for PCa, as well as the expression pattern and biological functions. All analyses in this study were based on publicly available databases, mainly containing Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), UCSCXenaShiny, and TISIDB. We performed differential expression analysis, developed a prognostic model, and explored potential associations between EZH2 and DNA methylation modifications, tumor microenvironment (TME), immune-related genes, tumor mutation burden (TMB), tumor neoantigen burden (TNB), and representative mismatch repair (MMR) genes. We also investigated the molecular and immunological characterizations of EZH2. Finally, we predicted immunotherapeutic responses based on EZH2 expression levels. We found that EZH2 was highly expressed in PCa, was associated with a poor prognosis, and may serve as an independent prognostic factor. EZH2 expression in PCa was associated with DNA methylation modifications, TME, immune-related genes, TMB, TNB, and MMR. By gene set enrichment analysis and gene set variation analysis, we found that multiple functions and pathways related to tumorigenesis, progression, and immune activation were enriched. Finally, we inferred that immunotherapy may be more effective for PCa patients with low EZH2 expression. In conclusion, our study showed that EZH2 could be a potentially efficient predictor of prognosis and immune response in PCa patients.

Oxidative stress-related patterns determination for establishment of prognostic models, and characteristics of tumor microenvironment infiltration

Oxidative stress-mediated excessive accumulation of ROS in the body destroys cell homeostasis and participates in various diseases. However, the relationship between oxidative stress-related genes (ORGs) and tumor microenvironment (TME) in gastric cancer remains poorly understood. For improving the treatment strategy of GC, it is necessary to explore the relationship among them. We describe the changes of ORGs in 732 gastric cancer samples from two data sets. The two different molecular subtypes revealed that the changes of ORGs were associated with clinical features, prognosis, and TME. Subsequently, the OE_score was related to RFS, as confirmed by the correlation between OE_score and TME, TMB, MSI, immunotherapy, stem cell analysis, chemotherapeutic drugs, etc. OE_score can be used as an independent predictive marker for the treatment and prognosis of gastric cancer. Further, a Norman diagram was established to improve clinical practicability. Our research showed a potential role of ORGs in clinical features, prognosis, and tumor microenvironment of gastric cancer. Our research findings broaden the understanding of gastric cancer ORGs as a potential target for individualized treatment of gastric cancer and a new direction to evaluate the prognosis.

State of the Biomarker Science in Ovarian Cancer: A National Cancer Institute Clinical Trials Planning Meeting Report

PURPOSE

Despite therapeutic advances in the treatment of ovarian cancer (OC), 5-year survival remains low, and patients eventually die from recurrent, chemotherapy-resistant disease. The National Cancer Gynecologic Cancer Steering Committee identified the integration of scientifically defined subgroups as a top strategic priority in clinical trial planning.

METHODS

A group of experts was convened to review the scientific literature in OC to identify validated predictive biomarkers that could inform patient selection and treatment stratification. Here, we report on these findings and their potential for use in future clinical trial design on the basis of hierarchal evidence grading.

RESULTS

The biomarkers were classified on the basis of mechanistic targeting, including DNA repair and replication stress, immunotherapy and tumor microenvironment, oncogenic signaling, and angiogenesis. Currently, BRCA mutations and homologous recombination deficiency to predict poly (ADP-ribose) polymerase inhibitor response are supported in OC by the highest level of evidence. Additional biomarkers of response to agents targeting the pathways above have been identified but require prospective validation.

CONCLUSION

Although a number of biomarkers of response to various agents in OC have been described in the literature, high-level evidence for the majority is lacking. This report highlights the unmet need for identification and validation of predictive biomarkers to guide therapy and future trial design in OC.

An oxidative stress-related prognostic signature for indicating the immune status of oral squamous cell carcinoma and guiding clinical treatment

Oral squamous cell carcinoma (OSCC) is the eighth most common cancer worldwide and presents high mortality. Oxidative stress, caused by reactive oxygen species accumulation, plays a crucial role in tumorigenesis, cancer progression, and drug resistance. Nevertheless, the specific prognostic and clinical values of oxidative stress-related genes (OSGs) in OSCC remain unclear. Here, we developed an oxidative stress-related prognostic signature according to mRNA expression data from The Cancer Genome Atlas (TCGA) database and evaluated its connections with the prognosis, clinical features, immune status, immunotherapy, and drug sensitivity of OSCC through a series of bioinformatics analyses. Finally, we filtered out six prognostic OSGs to construct a prognostic signature. On the basis of both TCGA-OSCC and GSE41613 cohorts, the signature was proven to be an independent prognostic factor with high accuracy and was confirmed to be an impactful indicator for predicting the prognosis and immune status of patients with OSCC. Additionally, we found that patients with high-risk scores may obtain greater benefit from immune checkpoint therapy compared to those with low-risk scores, and the risk score presented a close interaction with the tumor microenvironment and chemotherapy sensitivity. The prognostic signature may provide a valid and robust predictive tool that could predict the prognosis and immune status and guide clinicians to develop personalized therapeutic strategies for patients with OSCC.

Multi-Omics Analysis of GNL3L Expression, Prognosis, and Immune Value in Pan-Cancer

Simple Summary

Guanine nucleotide-binding protein-like 3-like (GNL3L) is a novel GTP-binding nucleolar protein. In this study, we analyzed the expression, prognosis, and immune roles of GNL3L in pan-cancer from multiple omics analyses. The final results showed that GNL3L is differentially expressed in a variety of cancers, plays a prognostic role, and has good immune value. Moreover, GNL3L may affect the occurrence of cancer through processes such as ribonucleoprotein, ribosomal RNA processing, and cell proliferation. At the same time, we established an esophageal cancer (ESCA) prediction model with strong predictive ability and proved that GNL3L can significantly affect the proliferation ability of esophageal cancer cells through clone formation assays. In conclusion, GNL3L is an important biomarker.

Abstract

Guanine nucleotide-binding protein-like 3-like protein (GNL3L) is a novel, evolutionarily conserved, GTP-binding nucleolar protein. This study aimed to investigate the expression, prognosis, and immune value of GNL3L in pan-cancer from multiple omics analyses. Firstly, the expression and prognostic value of GNL3L in pan-cancer were discussed using the TIMER2 database, the GEPIA database, the cBioportal database, COX regression analysis, and enrichment analysis. The association of GNL3L with tumor mutational burden (TMB), tumor microsatellite instability (MSI), mismatch repair (MMR) genes, and immune cells was then analyzed. Finally, an esophageal cancer (ESCA) prediction model was established, and GNL3L clone formation assays were performed. The final results showed that GNL3L is differentially expressed in the vast majority of cancers, is associated with the prognosis of various cancers, and may affect cancer occurrence through processes such as ribonucleoprotein, ribosomal RNA processing, and cell proliferation. At the same time, it was found that the correlation between GNL3L and TMB, MSI, MMR, and various immune cells is significant. The established ESCA prediction model had a strong predictive ability, and GNL3L could significantly affect the proliferation of esophageal cancer cells. In conclusion, GNL3L may serve as an important prognostic biomarker and play an immunomodulatory role in tumors.

ENTPD1/CD39 as a predictive marker of treatment response to gemogenovatucel-T as maintenance therapy in newly diagnosed ovarian cancer

Background

Broadened use of predictive molecular and phenotypic profiling amongst oncologists has facilitated optimal integration of targeted- and immuno-therapeutics into clinical care. However, the use of predictive immunomarkers in ovarian cancer (OC) has not consistently translated into clinical benefit. Vigil (gemogenovatucel-T) is a novel plasmid engineered autologous tumor cell immunotherapy designed to knock down the tumor suppressor cytokines, TGFβ1 and TGFβ2, augment local immune function via increased GMCSF expression and enhance presentation of clonal neoantigen epitopes. Methods: All patients enrolled in the VITAL trial (NCT02346747) of maintenance Vigil vs. placebo as front-line therapy with homologous recombination proficient (HRP) stage IIIB-IV newly diagnosed ovarian cancer underwent NanoString gene expression analysis. Tissue was obtained from surgically resected ovarian tumor tissue following surgical debulking. A statistical algorithm was used to analyze the NanoString gene expression data.

Results

Using the NanoString Statistical Algorithm (NSA), we identify high expression of ENTPD1/CD39 (which functions as the rate-limiting step in the production of the immune suppressor adenosine from ATP to ADP) as a presumptive predictor of response to Vigil versus placebo regardless of HRP status on the basis of relapse free survival (median not achieved vs 8.1 months, p = 0.00007) and overall survival (median not achieved vs 41.4 months, p = 0.013) extension.

Conclusion

NSA should be considered for application to investigational targeted therapies in order to identify populations most likely to benefit from treatment, in preparation for efficacy conclusive trials.

Characterization of the immune related lncRNAs in bladder cancer to aid immunotherapy

Bladder cancer (BLCA) is the 10th most common form of cancer worldwide. Currently, the response rate of BLCA patients to novel immunotherapy and immune checkpoint inhibitor (ICI) treatment is around 30% or less. Therefore, there is an urgent clinical demand to understand the regulation of immune function in BLCA patients. LncRNAs are known to play fundamental roles in the regulation of the immune system in the tumor microenvironment. In this report, we performed a comprehensive analysis to identify immune-related lncRNAs (IRLs) in BLCA patients using The Cancer Genome Atlas (TCGA) databases. BLCA patients were divided into five TME subtypes. Subtype HMIE was strongly related to survival and high anti-tumor activity of patients. Through a four-step analysis, we identified 34 IRLs as subtype HMIE related lncRNAs (HMIE-lncs).The correlation analysis with immune cell infiltration and target gene pathway enrichment showed that 34 HMIE-lncs were correlated with immune cell activation and tumor cell killing. Among them, 24 lncRNAs were related to good prognosis. We constructed a risk model to predict BLCA. Cross tumor validation was performed, and the results showed that the 34 HMIE-lncs identified in the BLCA patients in this study were highly expressed in the immune-favorable TME subtype (IE) in most of the other cancer types.