Transporter associated with antigen processing 1 (TAP1) expression and prognostic analysis in breast, lung, liver, and ovarian cancer

Expression pattern and prognostic significance of aldehyde dehydrogenase 2 in lung adenocarcinoma as a potential predictor of immunotherapy efficacy

Background

The incidence of alcohol-associated cancers is higher within Asian populations having an increased prevalence of an inactivating mutation in aldehyde dehydrogenase 2 (ALDH2), a mitochondrial enzyme required for the clearance of acetaldehyde, a cytotoxic metabolite of ethanol. The role of alcohol consumption in promoting lung cancer is controversial, and little attention has been paid to the association between alcohol drinking and pulmonary ALDH2 expression.

Methods

We performed a comprehensive bioinformatic analysis of multi-omics data available in public databases to elucidate the role of ALDH2 in lung adenocarcinoma (LUAD).

Results

Transcriptional and proteomic data indicate a substantial pulmonary expression of ALDH2, which is functional for the metabolism of alcohol diffused from the bronchial circulation. ALDH2 expression is higher in healthy lung tissue than in LUAD and inhibits cell cycle, apoptosis, and epithelial-mesenchymal transition pathways. Moreover, low ALDH2 mRNA levels predict poor prognosis and low overall survival in LUAD patients. Interestingly, ALDH2 expression correlates with immune infiltration in LUAD.

Conclusions

A better understanding of the role of ALDH2 in lung tumor progression and immune infiltration might support its potential use as a prognostic marker and therapeutic target for improving immunotherapeutic response.

PMN-MDSCs are responsible for immune suppression in anti-PD-1 treated TAP1 defective melanoma

INTRODUCTION

The transporter associated with antigen processing (TAP) is a key component of the classical HLA I antigen presentation pathway. Our previous studies have demonstrated that the downregulation of TAP1 contributes to tumor progression and is associated with an increased presence of myeloid-derived suppressor cells (MDSCs) in the tumor microenvironment. However, it remains unclear whether the elevation of MDSCs leads to immune cell exhaustion in tumors lacking TAP1. In this study, we established mouse models of tumors with TAP1 deficiency, and we employed PMN-MDSC depletion to investigate their impact on the immune microenvironment within the tumors. We found that MDSC depletion significantly altered the immune-suppressive effects of TAP1-deficient tumor when anti-PD-1 treatment was administered. Targeting PMN-MDSC may be a promising therapeutic strategy for the treatment of tumors with TAP1 deficiency during ICB treatment.

METHODS

Immunohistochemistry (IHC) was conducted to assess TAP1 expression in mouse melanoma tissues. Ly6G, F4/80, and NKp46 markers were detected in B16 parental and TAP1 knockout tissues, respectively. To enhance anti-tumor immunity, hyperthermia-treated B16F10 WT cell suspension was injected prior to tumor cell introduction. Subsequently, we established B16F10 TAP1 knockout and WT melanoma mouse models. Tumors were collected, and the immune microenvironment was monitored accordingly. Anti-Ly6G antibody was administered to deplete polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs). Finally, flow cytometry analysis for immune infiltration, quantitative PCR for cytokine levels, and immunofluorescence assays were performed to analyze the immune response.

RESULTS

The level of Ly6G+ cell infiltration was significantly higher in samples exhibiting low TAP1 expression, while no differences were observed in the infiltration of F4/80+ cells or NKp46+ cells. Furthermore, the immune-suppressive effects associated with PMN-MDSCs were reversed following their elimination; this resulted in an increase in CD8+ T cells and a higher ratio of CD8+ T cells to Tregs, while the infiltration of innate immune cells remained unaffected. Functional markers of these immune cells indicated an active anti-tumoral immune response following the removal of PMN-MDSCs. Quantitative PCR analysis indicated elevated levels of TNF-α and IL-6, accompanied by decreased levels of TGF-β in the tumor microenvironment of TAP1.

CONCLUSIONS

Our data indicate that myeloid-derived suppressor cells (PMN-MDSCs) play an essential role in creating a tumorigenic immune microenvironment in TAP1 knockout tumors. Therefore, targeting PMN-MDSCs may become a promising therapeutic strategy for the treatment of tumors with TAP1 deficiency during ICB treatment.

Identification and validation of genes associated with prognosis of cisplatin-resistant ovarian cancer

PURPOSE

To investigate the role of prognostic genes related to cisplatin resistance in ovarian cancer during disease progression.

METHOD

The gene expression profile of the NCI-60 cell line was acquired through comprehensive analysis of the GEO database accession GSE116439. We performed a thorough analysis of gene expression differences in samples from seven individuals exposed to cisplatin concentrations of 0 nM compared to seven samples exposed to 15000 nM over a 24-h period. Key genes were initially identified through LASSO regression, followed by their enrichment through differential gene function analysis (GO) and pathway enrichment analysis (KEGG). Subsequently, a prognostic risk model was established for these key genes. The prognostic model's performance was assessed through K-M survival curves and ROC curves. To examine the variance in immune cell infiltration between the high and low-risk groups, CIBERSORTx analysis was employed. Finally, validation of prognostic gene expression in cisplatin-resistant ovarian cancer was carried out using clinical samples, employing RT-qPCR and Western Blot techniques.

RESULTS

A total of 132 differential genes were found between cisplatin resistance and control group, and 8 key prognostic genes were selected by analysis, namely VPS13B, PLGRKT, CDKAL1, TBC1D22A, TAP1, PPP3CA, CUX1 and PPP1R15A. The efficacy of the risk assessment model derived from prognostic biomarkers, as indicated by favorable performance on both Kaplan-Meier survival curves and ROC curves. Significant variations in the abundance of Macrophages M1, T cells CD4 memory resting, T cells follicular helper, and T cells gamma delta were observed between the high and low-risk groups. To further validate our findings, RT-qPCR and Western Blot analyses were employed, confirming differential expression of the identified eight key genes between the two groups.

CONCLUSION

VPS13B, TBC1D22A, PPP3CA, CUX1 and PPP1R15A were identified as poor prognostic genes of cisplatin resistance in ovarian cancer, while PLGRKT, CDKAL1 and TAP1 were identified as good prognostic genes. This offers a novel perspective for future advancements in ovarian cancer treatment, suggesting potential avenues for the development of new therapeutic targets.

Spatial multiomics of arterial regions from cardiac allograft vasculopathy rejected grafts reveal novel insights into the pathogenesis of chronic antibody-mediated rejection

Cardiac allograft vasculopathy (CAV) causes late graft failure and mortality after heart transplantation. Donor-specific antibodies (DSAs) lead to chronic endothelial cell injury, inflammation, and arterial intimal thickening. In this study, GeoMx digital spatial profiling was used to analyze arterial areas of interest (AOIs) from CAV+DSA+ rejected cardiac allografts (N = 3; 22 AOIs total). AOIs were categorized based on CAV neointimal thickening and underwent whole transcriptome and protein profiling. By comparing our transcriptomic data with that of healthy control vessels of rapid autopsy myocardial tissue, we pinpointed specific pathways and transcripts indicative of heightened inflammatory profiles in CAV lesions. Moreover, we identified protein and transcriptomic signatures distinguishing CAV lesions exhibiting low and high neointimal lesions. AOIs with low neointima showed increased markers for activated inflammatory infiltrates, endothelial cell activation transcripts, and gene modules involved in metalloproteinase activation and TP53 regulation of caspases. Inflammatory and apoptotic proteins correlated with inflammatory modules in low neointima AOIs. High neointima AOIs exhibited elevated TGFβ-regulated transcripts and modules enriched for platelet activation/aggregation. Proteins associated with growth factors/survival correlated with modules enriched for proliferation/repair in high neointima AOIs. Our findings reveal novel insight into immunological mechanisms mediating CAV pathogenesis.

Pharmacokinetics and drug-likeness of anti-cancer traditional Chinese medicine: molecular docking and molecular dynamics simulation study

MCM7 (Minichromosome Maintenance Complex Component 7) is a component of the DNA replication licensing factor, which controls DNA replication. The MCM7 protein is linked to tumor cell proliferation and has a function in the development of several human cancers. Several types of cancer may be treated by inhibiting the protein, as it is strongly produced throughout this process. Significantly, Traditional Chinese Medicine (TCM), which has a long history of clinical adjuvant use against cancer, is rapidly gaining traction as a valuable medical resource for the development of novel cancer therapies, including immunotherapy. Therefore, the goal of the research was to find small molecular therapeutic candidates against the MCM7 protein that may be used to treat human cancers. A computational-based virtual screening of 36,000 natural TCM libraries is carried out for this goal using a molecular docking and dynamic simulation technique. Thereby, ∼8 novel potent compounds i.e., ZINC85542762, ZINC95911541, ZINC85542617, ZINC85542646, ZINC85592446, ZINC85568676, ZINC85531303, and ZINC95914464 were successfully shortlisted, each having the capacity to penetrate the cell as potent inhibitors for MCM7 to curb this disorder. These selected compounds were found to have high binding affinities compared to the reference (AGS compound) i.e. < -11.0 kcal/mol. ADMET and pharmacological properties showed that none of these 8 compounds poses any toxic property (carcinogenicity) and have anti-metastatic, and anticancer activity. Additionally, MD simulations were run to assess the compounds' stability and dynamic behavior with the MCM7 complex for about 100 ns. Finally, ZINC95914464, ZINC95911541, ZINC85568676, ZINC85592446, ZINC85531303, and ZINC85542646 are identified as highly stable within the complex throughout the 100 ns simulations. Moreover, the results of binding free energy suggested that the selected virtual hits significantly bind to the MCM7 which implied these compounds may act as a potential MCM7 inhibitor. However, in vitro testing protocols are required to further support these results. Further, assessment through various lab-based trial methods can assist with deciding the action of the compound that will give options in contrast to human cancer immunotherapy.Communicated by Ramaswamy H. Sarma.

An integrated machine learning-based model for joint diagnosis of ovarian cancer with multiple test indicators

OBJECTIVE

To construct a machine learning diagnostic model integrating feature dimensionality reduction techniques and artificial neural network classifiers to develop the value of clinical routine blood indexes for the auxiliary diagnosis of ovarian cancer.

METHODS

Patients with ovarian cancer clearly diagnosed in our hospital were collected as a case group (n = 185), and three groups of patients with other malignant otolaryngology tumors (n = 138), patients with benign otolaryngology diseases (n = 339) and those with normal physical examination (n = 92) were used as an overall control group. In this paper, a fully automated segmentation network for magnetic resonance images of ovarian cancer is proposed to improve the reproducibility of tumor segmentation results while effectively reducing the burden on radiologists. A pre-trained Res Net50 is used to the three edge output modules are fused to obtain the final segmentation results. The segmentation results of the proposed network architecture are compared with the segmentation results of the U-net based network architecture and the effect of different loss functions and region of interest sizes on the segmentation performance of the proposed network is analyzed.

RESULTS

The average Dice similarity coefficient, average sensitivity, average specificity (specificity) and average hausdorff distance of the proposed network segmentation results reached 83.62%, 89.11%, 96.37% and 8.50, respectively, which were better than the U-net based segmentation method. For ROIs containing tumor tissue, the smaller the size, the better the segmentation effect. Several loss functions do not differ much. The area under the ROC curve of the machine learning diagnostic model reached 0.948, with a sensitivity of 91.9% and a specificity of 86.9%, and its diagnostic efficacy was significantly better than that of the traditional way of detecting CA125 alone. The model was able to accurately diagnose ovarian cancer of different disease stages and showed certain discriminative ability for ovarian cancer in all three control subgroups.

CONCLUSION

Using machine learning to integrate multiple conventional test indicators can effectively improve the diagnostic efficacy of ovarian cancer, which provides a new idea for the intelligent auxiliary diagnosis of ovarian cancer.

Comprehensive analysis on clinical significance and therapeutic targets of LDL receptor related protein 11 (LRP11) in liver hepatocellular carcinoma

LDL lipoprotein receptor-related protein 11 (LRP11) plays a role in several tumors. However, their roles in hepatocellular carcinoma remain unclear. The present study aimed to explore the expression profile and prognostic value of LRP11 in liver hepatocellular carcinoma (LIHC) patients using various cancer databases and bioinformatic tools. In bioinformatics analysis, The Cancer Genome Atlas datasets showed increased LRP11 expression in tumor tissues compared to that in non-tumor tissues in various cancers. Moreover, patients with high expression LRP11 correlated with poor prognosis and clinical features. The LRP11 expression positively correlated with the infiltration of immune cells such as macrophages, neutrophils, and myeloid-derived suppressor cells and a combination of high LRP11 expression and high immune infiltrates was associated with the worst survival in LIHC tumors. Our results also indicated that LRP11 expression was closely associated with immune-modulate function, such as antigen presentation. In DNA methylation profiling, hypomethylation of LRP11 is widely observed in tumors and has prognostic value in LIHC patients. Functional enrichment analysis revealed that LIHC-specific LRP11 interacting genes are involved in protein binding, intracellular processing, and G-protein-related signaling pathways. Analyses of drug sensitivity and immune checkpoint inhibitor predict a number of drugs that could potentially be used to target LRP11. In addition, in vitro experiments verified the promoting effect of LRP11 on the migration, invasion, and colony formation capacity of hepatocellular carcinoma cells. Collectively, our results aided a better understanding of the clinical significance of LRP11 in gene expression, functional interactions, and epigenetic regulation in LIHC and suggested that it may be a useful prognostic biomarker for LIHC patients.

The Antigen-Processing Pathway via Major Histocompatibility Complex I as a New Perspective in the Diagnosis and Treatment of Endometriosis

Endometriosis is a debilitating gynecological disease defined as the presence of endometrium-like epithelium and/or stroma outside the uterine cavity. The most commonly affected sites are the pelvic peritoneum, ovaries, uterosacral ligaments, and the rectovaginal septum. The aberrant tissue responds to hormonal stimulation, undergoing cyclical growth and shedding similar to appropriately located endometrial tissue in the uterus. Common symptoms of endometriosis are painful periods and ovulation, severe pelvic cramping, heavy bleeding, pain during sex, urination and bowel pain, bleeding, and pain between periods. Numerous theories have been proposed to explain the pathogenesis of endometriosis. Sampson's theory of retrograde menstruation is considered to be the most accepted. This theory assumes that endometriosis occurs due to the retrograde flow of endometrial cells through the fallopian tubes during menstruation. However, it has been shown that this process takes place in 90% of women, while endometriosis is diagnosed in only 10% of them. This means that there must be a mechanism that blocks the immune system from removing endometrial cells and interferes with its function, leading to implantation of the ectopic endometrium and the formation of lesions. In this review, we consider the contribution of components of the Major Histocompatibility Complex (MHC)-I-mediated antigen-processing pathway, such as the ERAP, TAP, LMP, LNPEP, and tapasin, to the susceptibility, onset, and severity of endometriosis. These elements can induce significant changes in MHC-I-bound peptidomes that may influence the response of immune cells to ectopic endometrial cells.

Protein expression and localization of ABC transporters in pancreatic adenocarcinoma: Prognostic role of ABCC8

BACKGROUND

ATP-binding cassette (ABC) transporters translocate various substances across cellular membranes. Their deregulation may cause cancer drug resistance or perturbations in the supply of building blocks for cancer cells and modify patients' prognosis. This study investigated protein expression and cellular localization of the previously suggested putative prognostic biomarkers - ABCB2/TAP1, ABCC7/CFTR, ABCC8/SUR1, and ABCD4 in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

Protein expression and localization were assessed by immunohistochemistry in formalin-fixed paraffin-embedded primary tumor tissue blocks of 61 PDAC patients and associated with clinical data and the survival of patients.

RESULTS

No CFTR protein expression was observed in PDAC, while TAP1 and ABCC8 were expressed predominantly in the cytoplasm of tumor cells. Most samples (81 %) had detectable both membranous and cytoplasmic ABCD4 staining and 42 % had ABCD4 expressed in the apical orientation. Negative membranous ABCD4 staining was significantly more frequent in advanced stage III or IV tumors (p = 0.022). Small or medium counts of individual ABCC8-positive cells in the stroma surrounding tumor tubules were also more often found in stage III or IV (p = 0.044). Patients with moderate or strong ABCC8 cytoplasmic staining intensity in tumor cells had a 3.5-fold higher risk of disease progression than those with weak staining (p = 0.002).

CONCLUSIONS

The study shows for the first time that the cytoplasmic ABCC8 protein expression has prognostic value in PDAC.

Genetic characteristics of common variable immunodeficiency patients with autoimmunity

Background: The pathogenesis of common variable immunodeficiency disorder (CVID) is complex, especially when combined with autoimmunity. Genetic factors may be potential explanations for this complex situation, and whole genome sequencing (WGS) provide the basis for this potential. Methods: Genetic information of patients with CVID with autoimmunity, together with their first-degree relatives, was collected through WGS. The association between genetic factors and clinical phenotypes was studied using genetic analysis strategies such as sporadic and pedigree. Results: We collected 42 blood samples for WGS (16 CVID patients and 26 first-degree relatives of healthy controls). Through pedigree, sporadic screening strategies and low-frequency deleterious screening of rare diseases, we obtained 9,148 mutation sites, including 8,171 single-nucleotide variants (SNVs) and 977 Insertion-deletions (InDels). Finally, we obtained a total of 28 candidate genes (32 loci), of which the most common mutant was LRBA. The most common autoimmunity in the 16 patients was systematic lupus erythematosis. Through KEGG pathway enrichment, we identified the top ten signaling pathways, including "primary immunodeficiency", "JAK-STAT signaling pathway", and "T-cell receptor signaling pathway". We used PyMOL to predict and analyse the three-dimensional protein structures of the NFKB1, RAG1, TIRAP, NCF2, and MYB genes. In addition, we constructed a PPI network by combining candidate mutants with genes associated with CVID in the OMIM database via the STRING database. Conclusion: The genetic background of CVID includes not only monogenic origins but also oligogenic effects. Our study showed that immunodeficiency and autoimmunity may overlap in genetic backgrounds. Clinical Trial Registration: identifier ChiCTR2100044035.

Pharmacophore mapping approach to find anti-cancer phytochemicals with metformin-like activities against transforming growth factor (TGF)-beta receptor I kinase: An in silico study

The most frequently prescribed first-line treatment for type II diabetes mellitus is metformin. Recent reports asserted that this diabetes medication can also shield users from cancer. Metformin induces cell cycle arrest in cancer cells. However, the exact mechanism by which this occurs in the cancer system is yet to be elucidated. Here, we investigated the impact of metformin on cell cycle arrest in cancer cells utilizing transforming growth factor (TGF)-beta pathway. TGF-ß pathway has significant effect on cell progression and growth. In order to gain an insight on the underlying molecular mechanism of metformin's effect on TGF beta receptor 1 kinase, molecular docking was performed. Metformin was predicted to interact with transforming growth factor (TGF)-beta receptor I kinase based on molecular docking and molecular dynamics simulations. Furthermore, pharmacophore was generated for metformin-TGF-ßR1 complex to hunt for novel compounds having similar pharmacophore as metformin with enhanced anti-cancer potentials. Virtual screening with 29,000 natural compounds from NPASS database was conducted separately for the generated pharmacophores in Ligandscout® software. Pharmacophore mapping showed 60 lead compounds for metformin-TGF-ßR1 complex. Molecular docking, molecular dynamics simulation for 100 ns and ADMET analysis were performed on these compounds. Compounds with CID 72473, 10316977 and 45140078 showed promising binding affinities and formed stable complexes during dynamics simulation with aforementioned protein and thus have potentiality to be developed into anti-cancer medicaments.

Transporter-Mediated Cellular Distribution of Tyrosine Kinase Inhibitors as a Potential Resistance Mechanism in Chronic Myeloid Leukemia

Chronic myeloid leukemia (CML) is a hematologic neoplasm characterized by the expression of the BCR::ABL1 oncoprotein, a constitutively active tyrosine kinase, resulting in uncontrolled growth and proliferation of cells in the myeloid lineage. Targeted therapy using tyrosine kinase inhibitors (TKIs) such as imatinib, nilotinib, dasatinib, bosutinib, ponatinib and asciminib has drastically improved the life expectancy of CML patients. However, treatment resistance occurs in 10-20% of CML patients, which is a multifactorial problem that is only partially clarified by the presence of TKI inactivating BCR::ABL1 mutations. It may also be a consequence of a reduction in cytosolic TKI concentrations in the target cells due to transporter-mediated cellular distribution. This review focuses on drug-transporting proteins in stem cells and progenitor cells involved in the distribution of TKIs approved for the treatment of CML. Special attention will be given to ATP-binding cassette transporters expressed in lysosomes, which may facilitate the extracytosolic sequestration of these compounds.

Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer

To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.

Cancer Immunology: Immune Escape of Tumors-Expression and Regulation of HLA Class I Molecules and Its Role in Immunotherapies

The addition of "avoiding immune destruction" to the hallmarks of cancer demonstrated the importance of cancer immunology and in particular the role of immune surveillance and escape from malignancies. However, the underlying mechanisms contributing to immune impairment and immune responses are diverse. Loss or reduced expression of the HLA class I molecules are major characteristics of human cancers resulting in an impaired recognition of tumor cells by CD8 + cytotoxic T lymphocytes. This is of clinical relevance and associated with worse patients outcome and limited efficacy of T-cell-based immunotherapies. Here, we summarize the role of HLA class I antigens in cancers by focusing on the underlying molecular mechanisms responsible for HLA class I defects, which are caused by either structural alterations or deregulation at the transcriptional, posttranscriptional, and posttranslational levels. In addition, the influence of HLA class I abnormalities to adaptive and acquired immunotherapy resistances will be described. The in-depth knowledge of the different strategies of malignancies leading to HLA class I defects can be applied to design more effective cancer immunotherapies.

IL-18-mediated neutrophil recruitment promotes acute lung injury in inflammation-mediated chronic pancreatitis

Lung injury is the most common secondary complication of pancreatitis and pancreatic malignancy. Around 60-70% of pancreatitis-related deaths are caused by lung injury; however, there is no animal model of the inflammation-mediated progressive pulmonary pathological events that contribute to acute lung injury in chronic pancreatitis (CP). Hence, we developed an inflammation-mediated mouse model and studied the pathological events that have a critical role in promoting the pathogenesis of lung injury. Our proteomic analysis of lung tissue revealed neutrophil-associated induction of neutrophil gelatinase-associated lipocalin (NGAL) and myeloperoxidase enzyme, further supporting a role for neutrophils in promoting IL-18-associated lung injury. We show that neutrophils released IL-18-induced p-NF-κB along with profibrotic and oncogenic proteins like TTF1, PDX1, and SOX9 in lung tissues of a mouse model of chronic pancreatitis. We also show that neutrophil infiltration induces TGF-β and SMAD4 and activates epithelial cells to produce other profibrotic proteins like ZO-1 and MUC2, along with the fibroblast markers FGF-1 and αSMA, that cause mesenchymal transition and accumulation of extracellular matrix collagen. Most importantly, we present evidence that IL-18 inhibition significantly alleviates CP-induced lung injury. This was further established by the finding that IL-18 gene-deficient mice showed improved lung injury by inhibition of TGF-β and fibroblast to mesenchymal transition and reduced collagen accumulation. The present study suggests that inhibition of IL-18 may be a novel treatment for CP-associated induced acute lung injury.

TAP1, a potential immune-related prognosis biomarker with functional significance in uveal melanoma

BACKGROUND

TAP1 is an immunomodulation-related protein that plays different roles in various malignancies. This study investigated the transcriptional expression profile of TAP1 in uveal melanoma (UVM), revealed its potential biological interaction network, and determined its prognostic value.

METHODS

CIBERSORT and ESTIMATE bioinformatic methods were used on data sourced from The Cancer Genome Atlas database (TCGA) to determine the correlation between TAP1 expression, UVM prognosis, biological characteristics, and immune infiltration. Gene set enrichment analysis (GSEA) was used to discover the signaling pathways associated with TAP1, while STRING database and CytoHubba were used to construct protein-protein interaction (PPI) and competing endogenous RNA (ceRNA) networks, respectively. An overall survival (OS) prognostic model was constructed to test the predictive efficacy of TAP1, and its effect on the in vitro proliferation activity and metastatic potential of UVM cell line C918 cells was verified by RNA interference.

RESULTS

There was a clear association between TAP1 expression and UVM patient prognosis. Upregulated TAP1 was strongly associated with a shorter survival time, higher likelihood of metastasis, and higher mortality outcomes. According to GSEA analysis, various immunity-related signaling pathways such as primary immunodeficiency were enriched in the presence of elevated TAP1 expression. A PPI network and a ceRNA network were constructed to show the interactions among mRNAs, miRNAs, and lncRNAs. Furthermore, TAP1 expression showed a significant positive correlation with immunoscore, stromal score, CD8+ T cells, and dendritic cells, whereas the correlation with B cells and neutrophils was negative. The Cox regression model and calibration plots confirmed a strong agreement between the estimated OS and actual observed patient values. In vitro silencing of TAP1 expression in C918 cells significantly inhibited cell proliferation and metastasis.

CONCLUSIONS

This study is the first to demonstrate that TAP1 expression is positively correlated with clinicopathological factors and poor prognosis in UVM. In vitro experiments also verified that TAP1 is associated with C918 cell proliferation, apoptosis, and metastasis. These results suggest that TAP1 may function as an oncogene, prognostic marker, and importantly, as a novel therapeutic target in patients with UVM.

Pan-cancer analysis: predictive role of TAP1 in cancer prognosis and response to immunotherapy

BACKGROUND

Transporter associated with antigen processing 1 (TAP1) is a molecule involved in processing and presentation of major histocompatibility complex class I restricted antigens, including tumor-associated antigens. TAP1 participates in tumor immunity, and is aberrantly expressed in multiple cancer types; METHODS: Transcriptome profiles were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression databases. Genetic alterations, protein distribution, and interaction information for TAP1 were downloaded from cBioPortal, Human Protein Atlas and Compartmentalized Protein-Protein Interaction, respectively. Single-cell analyses of TAP1 across cancers were conducted via the Tumor Immune Single-cell Hub website. Gene set enrichment analysis was employed to investigate TAP1-associated functional mechanisms and processes. Immune cell infiltration was explored using Tumor Immune Estimation Resource 2.0. Pan-cancer correlations between TAP1 expression and immunotherapy biomarkers were explored using the Spearman's correlation test. Associations with immunotherapy responses were also investigated using clinicopathological and prognostic information from cohorts of patients with cancer receiving immune checkpoint inhibitors.

RESULTS

TAP1 expression was elevated in most cancer types and exhibited distinct prognostic value. Immune cells expressed more TAP1 than malignant cells within most tumors. TAP1 expression was significantly correlated with immune-related pathways, T-lymphocyte infiltration, and immunotherapeutic biomarkers. Clinical cohort validation revealed a significant correlation with immune therapeutic effects and verified the prognostic role of TAP1 in immunotherapy. Western blot assay indicated that TAP1 is upregulated in glioblastoma compared with adjacent normal brain tissues.

CONCLUSION

TAP1 is a robust tumor prognostic biomarker and a novel predictor of clinical prognosis and immunotherapeutic responses in various cancer types.

An IFN-γ-related signature predicts prognosis and immunotherapy response in bladder cancer: Results from real-world cohorts

Bladder cancer (BLCA) is featured with high incidence and mortality. Whether the IFN-γ signaling could be used as an immunotherapy determinant for BLCA has not been fully confirmed. In this study, the transcriptome data and clinical information of BLCA samples were collected from The Cancer Genome Atlas (TCGA). Besides, four immunotherapy cohorts including IMvigor210 cohort, Gide cohort, Van Allen cohort, and Lauss cohort were collected. The Xiangya real-world cohort was used for independent validation. An IFN-γ-related signature was developed and validated in BLCA for predicting prognosis, mutation, tumor microenvironment status, and immunotherapy response. This is the first study focusing on the comprehensive evaluation of predictive values on the IFN-γ-related signature in BLCA. The potential clinical application of the IFN-γ-related signature was expected to be further validated with more prospective clinical cohorts.

Exposure of Immunogenic Tumor Antigens in Surrendered Immunity and the Significance of Autologous Tumor Cell-Based Vaccination in Precision Medicine

The mechanisms by which immune systems identify and destroy tumors, known as immunosurveillance, have been discussed for decades. However, several factors that lead to tumor persistence and escape from the attack of immune cells in a normal immune system have been found. In the process known as immunoediting, tumors decrease their immunogenicity and evade immunosurveillance. Furthermore, tumors exploit factors such as regulatory T cells, myeloid-derived suppressive cells, and inhibitory cytokines that avoid cytotoxic T cell (CTL) recognition. Current immunotherapies targeting tumors and their surroundings have been proposed. One such immunotherapy is autologous cancer vaccines (ACVs), which are characterized by enriched tumor antigens that can escalate specific CTL responses. Unfortunately, ACVs usually fail to activate desirable therapeutic effects, and the low immunogenicity of ACVs still needs to be elucidated. This difficulty highlights the significance of immunogenic antigens in antitumor therapies. Previous studies have shown that defective host immunity triggers tumor development by reprogramming tumor antigenic expressions. This phenomenon sheds new light on ACVs and provides a potential cue to improve the effectiveness of ACVs. Furthermore, synergistically with the ACV treatment, combinational therapy, which can reverse the suppressive tumor microenvironments, has also been widely proposed. Thus, in this review, we focus on tumor immunogenicity sculpted by the immune systems and discuss the significance and application of restructuring tumor antigens in precision medicine.

The expression and prognostic value of transporter 1, ATP binding cassette subfamily B member in clear cell renal cell cancer with experimental validation

Transporter associated with antigen processing 1(TAP1) serves as a protein to transport antigenic peptides from the surface of the endoplasmic reticulum to the lumen of the endoplasmic reticulum when the antigens are presented by major histocompatibility complex type I (MHC-I), which has been identified to play a critical role in antigen presentation in innate immunity. In tumors, the role of TAP1 seems to remain controversial. On the one hand, given the role of TAP1 in antigen presentation, it is indicated that high TAP1 expression corresponds to the emergence of more neoantigens epitopes that facilitate the recognition for phagocytes, T cells and other cells. On the other hand, the genetic ablation of transporter associated with antigen processing (TAP) results in the presentation of new class I-restricted epitopes encoded in house-keeping products. Opposite result has been revealed by studies in other tumors suggest, which implies a more complex function of TAP1. Therefore, it's significant to clarify the role of TAP1 in clear cell renal cell carcinoma (ccRCC). In this study, we found the elevated expression levels in mRNA and protein of TAP1 in ccRCC tissues, which indicated a relatively worse prognosis. Transwell assay and Scratch assay in vitro demonstrated the promotive role of TAP1 in ccRCC migration as well as a significant role in metastasis. And the increased expression of TAP1 resulted in more immune cells infiltrated in cancer tissues. TAP1 was also demonstrated to be related to immune regulator genes, as gene set enrichment analysis (GSEA) indicated its significant role in immune regulation. The results of CancerSEA indicated the positive association of the high-level TAP1 expression with epithelial-mesenchymal transition (EMT) and the inverse association with Cell Cycle. The effective drugs were also predicted based on TAP1 expression, of which the high level was indeed associated with resistance to multiple drugs, but some effective drugs still identified based on high TAP1 expression. According to the analysis of various databases, the role of TAP1 in ccRCC was explored, especially in relationship of TAP1 with tumor microenvironment. These results indicate that TAP1 can serve as a potential target for treatment of ccRCC.

In silico investigation of the role of vitamins in cancer therapy through inhibition of MCM7 oncoprotein

An overabundance of MCM7 protein, a component of the minichromosome maintenance complex that normally initiates DNA replication, has been reported to cause different types of cancers with aggressive malignancy. Inhibition of MCM7 may lead to a significant reduction in cancer-associated cell proliferation. Despite such significance of MCM7 in cancer, the protein structure is yet to be resolved experimentally. This significantly halts the structure-guided ligand designing for cancer therapy targeting the MCM7. The present study aims to resolve the tertiary structure of MCM7 and repurpose the FDA-approved clinically used drugs for cancer therapy by targeting MCM7 protein. The secondary and 3D structures of MCM7 were generated using multiple bioinformatics tools, including the Self-Optimized Prediction Method with Alignment (SOPMA), SWISS-MODEL, and I-TASSER. The reliability of the modeled structure was assessed using PROCHECK. Initially, a structure-guided virtual screening was performed on the approved drug library to identify potential hits against MCM7. The detailed molecular mechanism of receptor interactions of the identified hits was evaluated using extensive molecular dynamics simulation. The results from this study reveal an intriguing discovery of the potential of ergocalciferol (vitamin D2), cholecalciferol (vitamin D3), ergosterol (precursor of vitamin D2) and menaquinone (vitamin K2) as oncoprotein inhibitors for cancer therapy via inhibition of MCM7.

Antigen Peptide Transporter 1 (TAP1) Promotes Resistance to MEK Inhibitors in Pancreatic Cancers

Mitogen-activated protein kinase (MAPK) kinase (MEK) inhibitors show limited benefit in Kirsten rat sarcoma (KRAS) mutant pancreatic cancer due to drug resistance. To identify mechanisms of resistance to MEK inhibitor (MEKi), we employed a differential expression analysis of MEKi-sensitive versus MEKi-resistant KRAS-mutant pancreatic cancer cell lines. Here, we report that the antigen peptide transporter 1 (TAP1) expression levels of MEKi-resistant cell lines were notably higher than those of MEKi-sensitive cell lines. Suppression of TAP1 significantly sensitized the MEKi-resistant pancreatic ductal adenocarcinoma (PDAC) cells to MEKi and induced higher apoptotic rate in vitro. Moreover, knockdown of TAP1 in MEKi-resistant tumor significantly decreased tumor growth in vivo. Consistently, overexpression of TAP1 in sensitive PDAC cells resulted in increased resistance to MEKi, both in vitro and in vivo. Mechanistic studies demonstrated that TAP1 promoted chemoresistance by enhancing the transport of MEKi out of PDAC cells, leading to reduced intracellular MEKi concentration and attenuated inhibition of KRAS signaling pathways. Moreover, TAP1 expression increased spheroid formation abilities of PDAC cells. These findings suggest that TAP1 could serve as a potential marker for predicting the response of patients to MEKi. Combination of TAP1 suppression and MEKi may provide a novel therapeutic strategy for PDAC treatment.

Targeting SARS-CoV-2 non-structural protein 13 via helicase-inhibitor-repurposing and non-structural protein 16 through pharmacophore-based screening

Novel drug compound hunting was carried out for SARS-CoV-2 proteins with low mutation susceptibility. The probability of escape mutation and drug resistance is lower if conserved microbial proteins are targeted by therapeutic drugs. Mutation rate of all SARS-CoV-2 proteins were analyzed via multiple sequence alignment Non-Structural Protein 13 and Non-Structural Protein 16 were selected for the current study due to low mutation rate among viral strains and significant functionality. Cross-species mutation rate analysis for NSP13 and NSP16 showed these are well-conserved proteins among four coronaviral species. Viral helicase inhibitors, identified using literature-mining, were docked against NSP13. Pharmacophore-based screening of 11,375 natural compounds was conducted for NSP16. Stabilities of top compounds inside human body were confirmed via molecular dynamic simulation. ADME properties and LD₅₀ values of the helicase inhibitors and Ambinter natural compounds were analyzed. Compounds against NSP13 showed binding affinities between −10 and −5.9 kcal/mol whereby ivermectin and scutellarein showed highest binding energies of −10 and −9.9 kcal/mol. Docking of 18 hit compounds against NSP16 yielded binding affinities between −8.9 and −4.1 kcal/mol. Hamamelitannin and deacyltunicamycin were the top compounds with binding affinities of −8.9 kcal/mol and −8.4 kcal/mol. The top compounds showed stable ligand–protein interactions in molecular dynamics simulation. The analyses revealed two hit compounds against each targeted protein displaying stable behavior, high binding affinity and molecular interactions. Conversion of these compounds into drugs after in vitro experimentation can become better treatment options to elevate COVID management.

Impact of Diets on Response to Immune Checkpoint Inhibitors (ICIs) Therapy against Tumors

Immunotherapy has revolutionized the established therapeutics against tumors. As the major immunotherapy approach, immune checkpoint inhibitors (ICIs) achieved remarkable success in the treatment of malignancies. However, the clinical gains are far from universal and durable, because of the primary and secondary resistance of tumors to the therapy, or side effects induced by ICIs. There is an urgent need to find safe combinatorial strategies that enhance the response of ICIs for tumor treatment. Diets have an excellent safety profile and have been shown to play pleiotropic roles in tumor prevention, growth, invasion, and metastasis. Accumulating evidence suggests that dietary regimens bolster not only the tolerability but also the efficacy of tumor immunotherapy. In this review, we discussed the mechanisms by which tumor cells evade immune surveillance, focusing on describing the intrinsic and extrinsic mechanisms of resistance to ICIs. We also summarized the impacts of different diets and/or nutrients on the response to ICIs therapy. Combinatory treatments of ICIs therapy with optimized diet regimens own great potential to enhance the efficacy and durable response of ICIs against tumors, which should be routinely considered in clinical settings.

Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform for early detection of cancer

Background

Cancer screening provides the opportunity to detect cancer early, ideally before symptom onset and metastasis, and offers an increased opportunity for a better prognosis. The ideal biomarkers for cancer screening should discriminate individuals who have not developed invasive cancer yet but are destined to do so from healthy subjects. However, most cancers lack effective screening recommendations. Therefore, further studies on novel screening strategies are urgently required.

Methods

We used a simple suboptimal inoculation melanoma mouse model to obtain ‘pre-diagnostic samples’ of mice with macroscopic melanomas. High-throughput sequencing and bioinformatic analysis were employed to identify differentially expressed RNAs in platelet signatures of mice injected with a suboptimal number of melanoma cells (eDEGs) compared with mice with macroscopic melanomas and negative controls. Moreover, 36 genes selected from the eDEGs via bioinformatics analysis were verified in a mouse validation cohort via quantitative real-time PCR. LASSO regression was utilized to generate the prediction models with gene expression signatures as the best predictors for occult tumor progression in mice.

Results

These RNAs identified from eDEGs of mice injected with a suboptimal number of cancer cells were strongly enriched in pathways related to immune response and regulation. The prediction models generated by 36 gene qPCR verification data showed great diagnostic efficacy and predictive value in our murine validation cohort, and could discriminate mice with occult tumors from control group (area under curve (AUC) of 0.935 (training data) and 0.912 (testing data)) (gene signature including Cd19, Cdkn1a, S100a9, Tap1, and Tnfrsf1b) and also from macroscopic tumor group (AUC of 0.920 (training data) and 0.936 (testing data)) (gene signature including Ccr7, Cd4, Kmt2d, and Ly6e).

Conclusions

Our proof-of-concept study provides evidence for potential clinical relevance of blood platelets as a platform for liquid biopsy-based early detection of cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03268-z.

Bioinformatics approaches identified dasatinib and bortezomib inhibit the activity of MCM7 protein as a potential treatment against human cancer

Minichromosome Maintenance Complex Component 7 (MCM7) is a key component of the DNA replication licensing factor and hexamer MCM (MCM2-7) complex that regulates the DNA replication process. The MCM7 protein is associated with tumor cell proliferation that plays an important role in different human cancer progression. As the protein is highly expressed during the cancer development process, therefore, inhibition of the protein can be utilized as a treatment option for different human cancer. However, the study aimed to identify potential small molecular drug candidates against the MCM7 protein that can utilize treatment options for human cancer. Initially, the compounds identified from protein-drugs network analysis have been retrieved from NetworkAnalyst v3.0 server and screened through molecular docking, MM-GBSA, DFT, pharmacokinetics, toxicity, and molecular dynamics (MD) simulation approach. Two compounds namely Dasatinib (CID_3062316) and Bortezomib (CID_387447) have been identified throughout the screening process, which have the highest negative binding affinity (Kcal/mol) and binding free energy (Kcal/mol). The pharmacokinetics and toxicity analysis identified drug-like properties and no toxicity properties of the compounds, where 500 ns MD simulation confirmed structural stability of the two compounds to the targeted proteins. Therefore, we can conclude that the compounds dasatinib and bortezomib can inhibit the activity of the MCM7 and can be developed as a treatment option against human cancer.

Spike protein recognizer receptor ACE2 targeted identification of potential natural antiviral drug candidates against SARS-CoV-2

Angiotensin-converting enzyme 2 (ACE2), also known as peptidyl-dipeptidase A, belongs to the dipeptidyl carboxydipeptidases family has emerged as a potential antiviral drug target against SARS-CoV-2. Most of the ACE2 inhibitors discovered till now are chemical synthesis; suffer from many limitations related to stability and adverse side effects. However, natural, and selective ACE2 inhibitors that possess strong stability and low side effects can be replaced instead of those chemicals' inhibitors. To envisage structurally diverse natural entities as an ACE2 inhibitor with better efficacy, a 3D structure-based-pharmacophore model (SBPM) has been developed and validated by 20 known selective inhibitors with their correspondence 1166 decoy compounds. The validated SBPM has excellent goodness of hit score and good predictive ability, which has been appointed as a query model for further screening of 11,295 natural compounds. The resultant 23 hits compounds with pharmacophore fit score 75.31 to 78.81 were optimized using in-silico ADMET and molecular docking analysis. Four potential natural inhibitory molecules namely D-DOPA (Amb17613565), L-Saccharopine (Amb6600091), D-Phenylalanine (Amb3940754), and L-Mimosine (Amb21855906) have been selected based on their binding affinity (−7.5, −7.1, −7.1, and −7.0 kcal/mol), respectively. Moreover, 250 ns molecular dynamics (MD) simulations confirmed the structural stability of the ligands within the protein. Additionally, MM/GBSA approach also used to support the stability of molecules to the binding site of the protein that also confirm the stability of the selected four natural compounds. The virtual screening strategy used in this study demonstrated four natural compounds that can be utilized for designing a future class of potential natural ACE2 inhibitor that will block the spike (S) protein dependent entry of SARS-CoV-2 into the host cell.

Gene Expression Subtyping Reveals Immune alterations:TCGA Database for Prognosis in Ovarian Serous Cystadenocarcinoma

Serous ovarian cancer is the most common and primary death type in ovarian cancer. In recent studies, tumor microenvironment and tumor immune infiltration significantly affect the prognosis of ovarian cancer. This study analyzed the four gene expression types of ovarian cancer in TCGA database to extract differentially expressed genes and verify the prognostic significance. Meanwhile, functional enrichment and protein interaction network analysis exposed that these genes were related to immune response and immune infiltration. Subsequently, we proved these prognostic genes in an independent data set from the GEO database. Finally, multivariate cox regression analysis revealed the prognostic significance of TAP1 and CXCL13. The genetic alteration and interaction network of these two genes were shown. Then, we established a nomogram model related to the two genes and clinical risk factors. This model performed well in Calibration plot and Decision Curve Analysis. In conclusion, we have obtained a list of genes related to the immune microenvironment with a better prognosis for serous ovarian cancer, and based on this, we have tried to establish a clinical prognosis model.