AP3S1 is a Novel Prognostic Biomarker and Correlated With an Immunosuppressive Tumor Microenvironment in Pan-Cancer

AP5Z1 affects hepatocellular carcinoma growth and autophagy by regulating PTEN ubiquitination and modulating the PI3K/Akt/mTOR pathway

BACKGROUND

Hepatocellular carcinoma (HCC) is a leading cause of cancer death worldwide, with high incidence and mortality rates, and the number of cases is expected to increase by 2030. Understanding the molecular mechanisms of HCC and identifying new therapeutic targets and biomarkers for HCC are crucial.

METHODS

In this study, we examined adaptor-related protein complex 5 subunit ζ1 (AP5Z1) expression in liver cancer and nearby noncancerous tissues to explore its effects on HCC cell growth, death, and autophagy. The functional and molecular mechanisms of AP5Z1 were studied using clinical sample analysis, Western blot (WB), immunohistochemistry (IHC), quantitative reverse-transcription polymerase chain reaction (qRT‒PCR), coimmunoprecipitation (Co-IP), cell proliferation assays, flow cytometry (FCM), autophagy assays, electron microscopy, mass spectrometry (MS), transcriptome analysis, and animal model experiments.

RESULTS

AP5Z1 expression was notably higher in HCC tissues than in normal tissues and was linked to a poor prognosis. The results of both in vitro and in vivo studies revealed that AP5Z1 promoted HCC cell growth and reduced apoptosis. In addition, AP5Z1 regulates cellular autophagy by ubiquitinating the phosphatase and tensin homolog (PTEN) protein and modulating the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) pathway.

CONCLUSIONS

AP5Z1 influences autophagy and apoptosis in HCC cells by interacting with PTEN to modulate the PI3K/Akt/mTOR pathway. This gene might promote PTEN ubiquitination and degradation by recruiting tripartite motif-containing protein 21 (TRIM21), making it a potential biomarker for diagnosing and predicting the outcome of HCC as well as a target for new treatment strategies.

Mitochondrial-associated programmed-cell-death patterns for predicting the prognosis of non-small-cell lung cancer

Mitochondria are the convergence point of multiple pathways that trigger programmed cell death (PCD). Mitochondrial-associated PCD (mtPCD) is involved in the pathogenesis of several diseases. However, the role of mtPCD in the prognostic prediction of cancers including non-small-cell lung cancer (NSCLC) remains to be investigated. Here, 12 mtPCD patterns were analyzed in transcriptomics, genomics, and clinical data collected from 4 datasets containing 977 patients. A risk-score assessment system containing 18 genes was established. We found that NSCLC patients with a high-risk score had a poorer prognosis. A nomogram was constructed by incorporating the risk score with clinical features. The risk score was further associated with clinicopathological information, tumor-mutation frequency, and immunotherapy responses. NSCLC patients with a high risk score had more Treg cells infiltration. However, these patients had higher tumor-mutation burden scores and may be more sensitive to immunotherapy. Moreover, receptor-interacting serine/threonine protein kinase 2 (RIPK2) was selected from mtPCD gene model for validation. We found that RIPK2 exhibited oncogenic function, and its expression level was inversely associated with the overall survival of NSCLC. Taken together, our results indicated the accuracy and practicability of the mtPCD gene model and RIPK2 in predicting the prognosis of NSCLC.

A Novel Lysosome-Related Gene Signature Predicts Lung Cancer Prognosis: A Bioinformatics-Driven Study

Background and Aims

The biological function of lysosomes has been increasingly appreciated in cancer. However, the relationship between lysosome and lung adenocarcinoma (LUAD) was not well understood. In this study, a lysosome-related signature was developed for LUAD risk stratification and prognosis prediction.

Methods

Download RNA-seq data of LUAD and clinical information of corresponding samples from the UCSC-Xena platform. GSE31210 databases is used as a validation cohort. The lysosome-related genes was obtained from molecular signature database. The differentially expressed genes (DEGs) as well as lysosome-associated prognosis signatures were identified by using univariate, multivariate cox, and Lasso regression. A nomogram was constructed and evaluated using ROC and DCA.

Results

A total of 109 lysosome-related DEGs were identified and 30 prognostic related DEGs were subsequently screened. Cluster analysis further divides the TCGA cohort into clusters 1 and 2. Patients in cluster 2 had a worse prognosis (p = 0.016), lower LYSOSOME score. Enrichment analysis showed that 21 significantly enriched gene sets in the cluster 2 were activated. And 10 pathways, such as E2F_TARGETS, G2M_CHECKPOINT were upregulated. Multivariate Cox regression analysis identified 17 best prognostic genes as risk signature. An independent prognostic factor, the risk signature, was identified. A prognostic nomogram including risk signature, age, TNM stage, and gender was constructed, and ROC and DCA curves proved its excellent performance. We examined CTSZ and AP3S2 protein expression in 48 stage 3-4 NSCLC samples. Low AP3S2 expression was associated with better prognosis (median overall survival: 37.87 vs. 8.53 months, p = 0.0211). Increased CTSZ expression also indicated better prognosis (median overall survival: 6.77 vs. 30.50 months, p = 0.0306).

Conclusion

We identified molecular subtypes and lysosomal-based prognostic signatures for LUAD patients, as well as 17 genes that serve as a biomarker for evaluating the prognosis of LUAD patients.

Molecular patterns and mechanisms of tumorigenesis in HPV-associated and HPV-independent sinonasal squamous cell carcinoma

Mechanisms of tumorigenesis in sinonasal squamous cell carcinoma (SNSCC) remain poorly described due to its rare nature. A subset of SNSCC are associated with the human papillomavirus (HPV); however, it is unknown whether HPV is a driver of HPV-associated SNSCC tumorigenesis or merely a neutral bystander. We hypothesized that performing the first large high-throughput sequencing study of SNSCC would reveal molecular mechanisms of tumorigenesis driving HPV-associated and HPV-independent SNSCC and identify targetable pathways. High-throughput sequencing was performed on 64 patients with HPV-associated and HPV-independent sinonasal carcinomas. Mutation annotation, viral integration, copy number, and pathway-based analyses were performed. Analysis of HPV-associated SNSCC revealed similar mutational patterns observed in HPV-associated cervical and head and neck squamous cell carcinoma, including lack of TP53 mutations and the presence of known hotspot mutations in PI3K and FGFR3. Further similarities included enrichment of APOBEC mutational signature, viral integration at known hotspot locations, and frequent mutations in epigenetic regulators. HPV-associated SNSCC-specific recurrent mutations were also identified including KMT2C , UBXN11 , AP3S1 , MT-ND4 , and MT-ND5 . Mutations in KMT2D and FGFR3 were associated with decreased overall survival. We developed the first known HPV-associated SNSCC cell line and combinatorial small molecule inhibition of YAP/TAZ and PI3K pathways synergistically inhibited tumor cell clonogenicity. In conclusion, HPV-associated SNSCC and HPV-independent SNSCC are driven by molecularly distinct mechanisms of tumorigenesis. Combinatorial blockade of YAP/TAZ and vertical inhibition of the PI3K pathway may be useful in targeting HPV-associated SNSCC whereas targeting MYC and horizontal inhibition of RAS/PI3K pathways for HPV-independent SNSCC.

One Sentence Summary

This study solidifies HPV as a driver of HPV-associated SNSCC tumorigenesis, identifies molecular mechanisms distinguishing HPV-associated and HPV-independent SNSCC, and elucidates YAP/TAZ and PI3K blockade as key targets for HPV-associated SNSCC.

Functional analysis and validation of oncodrive gene AP3S1 in ovarian cancer through filtering of mutation data from whole-exome sequencing

BACKGROUND

High-grade serous ovarian carcinoma (HGSOC) is the most aggressive and prevalent subtype of ovarian cancer and accounts for a significant portion of ovarian cancer-related deaths worldwide. Despite advancements in cancer treatment, the overall survival rate for HGSOC patients remains low, thus highlighting the urgent need for a deeper understanding of the molecular mechanisms driving tumorigenesis and for identifying potential therapeutic targets. Whole-exome sequencing (WES) has emerged as a powerful tool for identifying somatic mutations and alterations across the entire exome, thus providing valuable insights into the genetic drivers and molecular pathways underlying cancer development and progression.

METHODS

Via the analysis of whole-exome sequencing results of tumor samples from 90 ovarian cancer patients, we compared the mutational landscape of ovarian cancer patients with that of TCGA patients to identify similarities and differences. The sequencing data were subjected to bioinformatics analysis to explore tumor driver genes and their functional roles. Furthermore, we conducted basic medical experiments to validate the results obtained from the bioinformatics analysis.

RESULTS

Whole-exome sequencing revealed the mutational profile of HGSOC, including BRCA1, BRCA2 and TP53 mutations. AP3S1 emerged as the most weighted tumor driver gene. Further analysis of AP3S1 mutations and expression demonstrated their associations with patient survival and the tumor immune response. AP3S1 knockdown experiments in ovarian cancer cells demonstrated its regulatory role in tumor cell migration and invasion through the TGF-β/SMAD pathway.

CONCLUSION

This comprehensive analysis of somatic mutations in HGSOC provides insight into potential therapeutic targets and molecular pathways for targeted interventions. AP3S1 was identified as being a key player in tumor immunity and prognosis, thus providing new perspectives for personalized treatment strategies. The findings of this study contribute to the understanding of HGSOC pathogenesis and provide a foundation for improved outcomes in patients with this aggressive disease.

I kappa B kinase interacting protein as a promising biomarker in pan-cancer: A multi-omics analysis

Background: Human chromosome 12 contains I kappa B kinase interacting protein (IKBIP) is also commonly known as IKIP. The involvement of IKBIP in the growth of tumors has only been discussed in a small number of publications.

Purpose: To explore the role that IKBIP plays in the development of a wide variety of neoplasms, as well as the tumor immunological microenvironment.

Methods: UALCAN, HPA, Genotype Tissue Expression, Cancer Genome Maps, and other datasets were used to analyze IKBIP expression. We thoroughly investigated the predictive importance of IKBIP in pan-cancer, clinical traits, and genetic anomalies. We studied whether there is a link between IKBIP and immune-related genes, microsatellite instability (MSI), and the incidence of tumor mutational burden (TMB). The link between immune cell infiltration and IKBIP expression was examined using data on immune cell infiltration from ImmuCellAI, TIMER2, and earlier studies. Finally, gene set enrichment analysis (GSEA) was performed to determine the signaling pathways associated with IKBIP.

Results: IKBIP is highly expressed in most cancers and is negatively associated with the prognosis of several major cancer types. Furthermore, IKBIP expression was linked to TMB in 13 cancers and MSI in seven cancers. Additionally, IKBIP is associated with numerous immunological and cancer-promoting pathways. Simultaneously, various cancer types have unique tumor-infiltrating immune cell profiles.

Conclusion: IKBIP has the potential to act as a pan-cancer oncogene and is crucial for both carcinogenesis and cancer immunity. Elevated IKBIP expression implies an immunosuppressive environment and may be used as a prognostic biomarker and therapeutic target.

Vesicle-mediated transport-related genes are prognostic predictors and are associated with tumor immunity in lung adenocarcinoma

Background

Globally, lung adenocarcinoma (LUAD) is the leading cause of cancer-related deaths. It is a progressive disorder that arises from multiple genetic and environmental factors. Dysregulated expression of vesicle-mediated transport-related genes (VMTRGs) have been reported in several cancers. However, the prognostic significance of VMTRGs in LUAD has yet to be established.

Methods

The VMTRG profiling data for 482 LUAD patients and 59 normal controls were downloaded from The Cancer Genome Altas (TCGA). Univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were performed to construct and optimize the risk model. Several GEO datasets were used to validate the risk model. The roles of these genes were investigated via the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analyses. Differences in immune cell infiltrations between risk groups were evaluated using five algorithms. "pRRophetic" was used to investigate anti-cancer drug sensitivities in two groups. Expression of these five genes in LUAD samples and adjacent normal tissues were evaluated by qRT-PCR. Colony formation and wound healing assays were performed to assess the significance of CNIH1 and AP3S1 in LUAD cells.

Results

We identified 85 prognosis-associated VMTRGs that could be constructed a risk model for LUAD patients, indicating their potential importance in LUAD development. The risk model including the five VMTRGs (CNIH1, KIF20A, GALNT2, GRIA1, and AP3S1) was associated with clinical outcomes. Tumor stage and risk score were found to be independent prognostic factors for LUAD patients. The five VMTRGs were also correlated with activation of the Notch and p53 signaling pathways. The risk model was significantly associated with immune responses and with high-level expression of immune checkpoints. High-risk group patients were more sensitive to several chemotherapeutic drugs and Lapatinib. Furthermore, CNIH1 and AP3S1 promoted LUAD cell growth and migration in vitro.

Conclusion

We constructed a VMTRG-based risk model for effective prediction of prognostic outcomes for LUAD patients. The risk model was associated with immune infiltration levels. These five hub genes are potential targets for immune therapy combined with chemotherapy in LUAD.