Immunodeficiency in Pancreatic Adenocarcinoma with Diabetes Revealed by Comparative Genomics

Identification of gemcitabine resistance-related AHNAK2 gene associated with prognosis and immune infiltration in pancreatic cancer

Purpose

Gemcitabine is a basic chemotherapy drug for pancreatic cancer (PC), but resistance is common and causes tumor recurrence and metastasis. Therefore, it is significant to explore gemcitabine resistance-related molecules for individualized treatment and prognosis assessment of PC.

Methods

In this study, transcriptome sequencing and TCGA database analysis were performed, and a differentiated gene AHNAK2 was screened. MEXPRESS database, tissue microarray analysis, and CIBERSORT and TIMER databases were used to correlate AHNAK2 expression with clinicopathological features and prognosis and immune infiltration of PC. Enrichment analysis was used to investigate the significant biological processes associated with AHNAK2.

Results

AHNAK2 was highly expressed in gemcitabine-resistant cells. High expression of AHNAK2 increased the risk of poor overall survival (OS) and progression-free survival (PFS) in PC. Clinicopathologic analysis revealed that AHNAK2 correlated with KRAS, TP53 mutations, histologic type, short OS, N stage, and elevated CA199 levels in PC. Knockdown of AHNAK2 inhibited the ability of cell proliferation and colony formation and enhanced the toxic effect of gemcitabine in PC. Meanwhile, the knockdown of AHNAK2 expression enhanced cell-ECM adhesion, inhibited cell-cell adhesion, and downregulated the KRAS/p53 signaling pathway in PC. Furthermore, AHNAK2 was correlated with immune infiltration, especially B cells and macrophages.

Conclusions

Our study unveils for the first time the pivotal role of AHNAK2 in PC, particularly its association with gemcitabine resistance, clinical prognosis, and immune infiltration. AHNAK2 not only drives the proliferation and drug resistance of PC cells by potentially activating the KRAS/p53 pathway but also significantly impacts cell-cell and cell- ECM adhesion. Additionally, AHNAK2 plays a crucial role in modulating the tumor immune microenvironment. These insights underscore AHNAK2's unique potential as a novel therapeutic target for overcoming gemcitabine resistance, offering new perspectives for PC treatment strategies.

GLIPR2: a potential biomarker and therapeutic target unveiled - Insights from extensive pan-cancer analyses, with a spotlight on lung adenocarcinoma

Background

Glioma pathogenesis related-2 (GLIPR2), an emerging Golgi membrane protein implicated in autophagy, has received limited attention in current scholarly discourse.

Methods

Leveraging extensive datasets, including The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), Human Protein Atlas (HPA), and Clinical Proteomic Tumor Analysis Consortium (CPTAC), we conducted a comprehensive investigation into GLIPR2 expression across diverse human malignancies. Utilizing UALCAN, OncoDB, MEXPRESS and cBioPortal databases, we scrutinized GLIPR2 mutation patterns and methylation landscapes. The integration of bulk and single-cell RNA sequencing facilitated elucidation of relationships among cellular heterogeneity, immune infiltration, and GLIPR2 levels in pan-cancer. Employing ROC and KM analyses, we unveiled the diagnostic and prognostic potential of GLIPR2 across diverse cancers. Immunohistochemistry provided insights into GLIPR2 expression patterns in a multicenter cohort spanning various cancer types. In vitro functional experiments, including transwell assays, wound healing analyses, and drug sensitivity testing, were employed to delineate the tumor suppressive role of GLIPR2.

Results

GLIPR2 expression was significantly reduced in neoplastic tissues compared to its prevalence in healthy tissues. Copy number variations (CNV) and alterations in methylation patterns exhibited discernible correlations with GLIPR2 expression within tumor tissues. Moreover, GLIPR2 demonstrated diagnostic and prognostic implications, showing pronounced associations with the expression profiles of numerous immune checkpoint genes and the relative abundance of immune cells in the neoplastic microenvironment. This multifaceted influence was evident across various cancer types, with lung adenocarcinoma (LUAD) being particularly prominent. Notably, patients with LUAD exhibited a significant decrease in GLIPR2 expression within practical clinical settings. Elevated GLIPR2 expression correlated with improved prognostic outcomes specifically in LUAD. Following radiotherapy, LUAD cases displayed an increased presence of GLIPR2+ infiltrating cellular constituents, indicating a notable correlation with heightened sensitivity to radiation-induced therapeutic modalities. A battery of experiments validated the functional role of GLIPR2 in suppressing the malignant phenotype and enhancing treatment sensitivity.

Conclusion

In pan-cancer, particularly in LUAD, GLIPR2 emerges as a promising novel biomarker and tumor suppressor. Its involvement in immune cell infiltration suggests potential as an immunotherapeutic target.

New insights into epigenetic regulation of resistance to PD-1/PD-L1 blockade cancer immunotherapy: mechanisms and therapeutic opportunities

Programmed cell death protein 1(PD-1) is a type of immune-inhibitory checkpoint protein, which delivers inhibitory signals to cytotoxic T cells by binding to the programmed death ligand-1 (PD-L1) displayed on the surface of cancer cells. Antibodies blocking PD-1/PD-L1 interaction have been extensively used in treatment of human malignancies and have achieved promising outcomes in recent years. However, gradual development of resistance to PD-1/PD-L1 blockade has decreased the effectiveness of this immunotherapy in cancer patients. The underlying epigenetic mechanisms need to be elucidated for application of novel strategies overcoming this immunotherapy resistance. Epigenetic aberrations contribute to cancerogenesis by promoting different hallmarks of cancer. Moreover, these alterations may lead to therapy resistance, thereby leading to poor prognosis. Recently, the epigenetic regulatory drugs have been shown to decrease the resistance to PD-1/PD-L1 inhibitors in certain cancer patients. Inhibitors of the non-coding RNAs, DNA methyltransferases, and histone deacetylases combined with PD-1/PD-L1 inhibitors have shown considerable therapeutic efficacy against carcinomas as well as blood cancers. Importantly, DNA methylation-mediated epigenetic silencing can inhibit antigen processing and presentation, which promotes cancerogenesis and aggravates resistance to PD-1/PD-L1 blockade immunotherapy. These observations altogether suggest that the combination of the epigenetic regulatory drugs with PD-1/PD-L1 inhibitors may present potential solution to the resistance caused by monotherapy of PD-1/PD-L1 immunotherapy.

Cuprotosis Programmed-Cell-Death-Related lncRNA Signature Predicts Prognosis and Immune Landscape in PAAD Patients

In terms of mortality and survival, pancreatic cancer is one of the worst malignancies. Known as a unique type of programmed cell death, cuprotosis contributes to tumor cell growth, angiogenesis, and metastasis. Cuprotosis programmed-cell-death-related lncRNAs (CRLs) have been linked to PAAD, although their functions in the tumor microenvironment and prognosis are not well understood. This study included data from the TCGA-PAAD cohort. Random sampling of PAAD data was conducted, splitting the data into two groups for use as a training set and test set (7:3). We searched for differentially expressed genes that were substantially linked to prognosis using univariate Cox and Lasso regression analysis. Through the use of multivariate Cox proportional risk regression, a risk-rating system for prognosis was developed. Correlations between the CRL signature and clinicopathological characteristics, tumor microenvironment, immunotherapy response, and chemotherapy sensitivity were further evaluated. Lastly, qRT-PCR was used to compare CRL expression in healthy tissues to that in tumors. Some CRLs are thought to have strong correlations with PAAD outcomes. These CRLs include AC005332.6, LINC02041, LINC00857, and AL117382.1. The CRL-based signature construction exhibited outstanding predictive performance and offers a fresh approach to evaluating pre-immune effectiveness, paving the way for future studies in precision immuno-oncology.

Establishment of a 4-miRNA Prognostic Model for Risk Stratification of Patients With Pancreatic Adenocarcinoma

Pancreatic adenocarcinomas (PAADs) often remain undiagnosed until later stages, limiting treatment options and leading to poor survival. The lack of robust biomarkers complicates PAAD prognosis, and patient risk stratification remains a major challenge. To address this issue, we established a panel constructed by four miRNAs (miR-4444-2, miR-934, miR-1301 and miR-3655) based on The Cancer Genome Atlas (TCGA) and Human Cancer Metastasis Database (HCMDB) to predicted the prognosis of PAAD patients. Then, a risk prediction model of these four miRNAs was constructed by using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) regression analysis. This model stratified TCGA PAAD cohort into the low-risk and high-risk groups based on the panel-based risk score, which was significantly associated with 1-, 2-, 3-year OS (AUC=0.836, AUC=0.844, AUC=0.952, respectively). The nomogram was then established with a robust performance signature for predicting prognosis compared to clinical characteristics of pancreatic cancer (PC) patients, including age, gender and clinical stage. Moreover, two GSE data were validated the expressions of 4 miRNAs with prognosis/survival outcome in PC. In the external clinical sample validation, the high-risk group with the upregulated expressions of miR-934/miR-4444-2 and downregulated expressions of miR-1301/miR-3655 were indicated a poor prognosis. Furthermore, the cell counting kit-8 (CCK-8) assay, clone formation, transwell and wound healing assay also confirmed the promoting effect of miR-934/miR-4444-2 and the inhibiting effect of miR-1301/miR-3655 in PC cell proliferation and migration. Taken together, we identified a new 4-miRNA risk stratification model could be used in predicting prognosis in PAAD.

Whole genome sequencing identifies rare germline variants enriched in cancer related genes in first degree relatives of familial pancreatic cancer patients

First-degree relatives (FDRs) of familial pancreatic cancer (FPC) patients have increased risk of developing pancreatic ductal adenocarcinoma (PDAC). Investigating and understanding the genetic basis for PDAC susceptibility in FPC predisposed families may contribute toward future risk-assessment and management of high-risk individuals. Using a Danish cohort of 27 FPC families, we performed whole-genome sequencing of 61 FDRs of FPC patients focusing on rare genetic variants that may contribute to familial aggregation of PDAC. Statistical analysis was performed using the gnomAD database as external controls. Through analysis of heterozygous premature truncating variants (PTV), we identified cancer-related genes and cancer-driver genes harboring multiple germline mutations. Association analysis detected 20 significant genes with false discovery rate, q < 0.05 including: PALD1, LRP1B, COL4A2, CYLC2, ZFYVE9, BRD3, AHDC1, etc. Functional annotation showed that the significant genes were enriched by gene clusters encoding for extracellular matrix and associated proteins. PTV genes were over-represented by functions related to transport of small molecules, innate immune system, ion channel transport, and stimuli-sensing channels. In conclusion, FDRs of FPC patients carry rare germline variants related to cancer pathogenesis that may contribute to increased susceptibility to PDAC. The identified variants may potentially be useful for risk prediction of high-risk individuals in predisposed families.

Identification of an Immune-Related Signature for Predicting Prognosis in Patients With Pancreatic Ductal Adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is one of the highest fatality rate cancers with poor survival rates. The tumor microenvironment (TME) is vital for tumor immune responses, leading to resistance to chemotherapy and poor prognosis of PDAC patients. This study aimed to provide a comprehensive evaluation of the immune genes and microenvironment in PDAC that might help in predicting prognosis and guiding clinical treatments.

METHODS

We developed a prognosis-associated immune signature (i.e., PAIS) based on immune-associated genes to predict the overall survival of patients with PDAC. The clinical significance and immune landscapes of the signature were comprehensively analyzed.

RESULTS

Owing to gene expression profiles from TCGA database, functional enrichment analysis revealed a significant difference in the immune response between PDAC and normal pancreas. Using transcriptome data analysis of a training set, we identified an immune signature represented by 5 genes (ESR2, IDO1, IL20RB, PPP3CA, and PLAU) related to the overall survival of patients with PDAC, significantly. This training set was well-validated in a test set. Our results indicated a clear association between a high-risk score and a very poor prognosis. Stratification analysis and multivariate Cox regression analysis revealed that PAIS was an important prognostic factor. We also found that the risk score was positively correlated with the inflammatory response, antigen-presenting process, and expression level of some immunosuppressive checkpoint molecules (e.g., CD73, PD-L1, CD80, and B7-H3). These results suggested that high-risk patients had a suppressed immune response. However, they could respond better to chemotherapy. In addition, PAIS was positively correlated with the infiltration of M2 macrophages in PDAC.

CONCLUSIONS

This study highlighted the relationship between the immune response and prognosis in PDAC and developed a clinically feasible signature that might serve as a powerful prognostic tool and help further optimize the cancer therapy paradigm.

CXCL10 is a Tumor Microenvironment and Immune Infiltration Related Prognostic Biomarker in Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is the 10th most common cancer worldwide and the outcomes for patients with the disease remain extremely poor. Precision biomarkers are urgently needed to increase the efficiency of early diagnosis and to improve the prognosis of patients. The tumor microenvironment (TME) and tumor immune infiltration are thought to impact the occurrence, progression, and prognosis of PAAD. Novel biomarkers excavated originating from the TME and immune infiltration may be effective in predicting the prognosis of PAAD patients. In the current study, the ESTIMATE and CIBERSORT algorithms were applied to estimate the division of immune and stromal components and the proportion of tumor-infiltrating immune cells in 182 PAAD cases downloaded from The Cancer Genome Atlas database. Intersection analyses of the Protein-Protein Interaction networks and Cox regression analysis identified the chemokine (CXC-motif) ligand 10 (CXCL10) as a predictive biomarker. We verified that CXCL10 in the TME negatively correlates with prognosis in PAAD and positively correlates with tumor cell differentiation. GSE62452 from the GEO database and cumulative survival analysis were performed to validate CXCL10 expression as an independent prognostic indicator. We also found that memory B cells, regulatory T cells, and macrophages M0 and M1 were correlated with the expression of CXCL10 indicating that expression of CXCL10 influenced the immune activity of the TME. Our data suggest that CXCL10 is beneficial as a prognostic indicator in PAAD patients and highlights the potential for immune targeted therapy in the treatment of PAAD.

Multi-omics analysis of copy number variations of RNA regulatory genes in soft tissue sarcoma

AIMS

RNA regulatory genes were closely associated with tumorigenesis and prognosis in multiple tumors. Copy number variation (CNV) is a frequent characteristic in soft tissue sarcomas (STS). However, little is known regarding their possible roles in STS.

MAIN METHODS

RNA sequence profiles and CNV data of 255 STS patients were downloaded from the Cancer Genome Atlas (TCGA). The correlation analysis involved CNVs of RNA regulatory genes, patient survival, immune infiltration, and DNA methylation. Drug sensitivity (IC50) was analyzed and validated by MTT assays in STS cell lines.

KEY FINDINGS

CNV events were frequently observed in all kinds (m6A, m5C, ac4C, m1A, m3C, m6Am, m7G, and Ψ) of RNA regulatory genes. Diploid copy number (CN) of METTL4 was associated with better overall survival (OS) in STS and the subtypes (leiomyosarcoma, LMS; dedifferentiated liposarcoma, DDLPS). In STS and LMS, diploid CN of METTL4 was significantly associated with higher infiltration fraction of resting mast cells. In STS and DDLPS, diploid CN of METTL4 possessed lower methylation level in CpG site of cg12105018, which represented better OS. Besides, sensitive drugs for STS cell lines were analyzed according to lower IC50 for the loss CN of METTL4. Temozolomide and Olaparib were identified. Further validation by MTT assays demonstrated that GCT was the most sensitive cell line to both Temozolomide and Olaparib.

SIGNIFICANCE

CNV of METTL4 could be a prognostic biomarker for STS by potentially influencing mast cell infiltration and DNA methylation. Besides, STS with loss CN of METTL4 would be sensitive to Temozolomide and Olaparib.

Genetic landscape of prognostic value in pancreatic ductal adenocarcinoma microenvironment

Background

The prognosis of pancreatic ductal adenocarcinoma (PDAC) remains dismally poor and is widely considered as an intricate genetic disorder. The mutational landscape of PDAC may directly reflect cancer immunogenicity and dictate the extent and phenotype of immune cell infiltration. In adverse, the microenvironment may also effect the gene expression of cancer cells, which is associated with clinical prognosis. Thus, it is crucial to identify genomic alterations in PDAC microenvironment and its impacts on clinical prognosis.

Methods

The gene expression profiles, mutation data and clinical information of 179 pancreatic cancer patients with an initial pathologic diagnosis ranging from 2001 to 2013 were retrieved from The Cancer Genome Atlas (TCGA) database. The MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm for calculating immune scores and stromal scores and Tumor IMmune Estimation Resource (TIMER) resource for cell infiltrations were applied in this study.

Results

The average immune score or stromal score of PDAC subtype was significantly higher than that of other specific subtypes. KRAS mutant cases had significantly lower immune scores (P=0.001) and stromal scores (P=0.007), in concert with lower immune scores in TP53 mutant cases (P=0.030). However, no significant difference was found in SMAD4 and CDKN2A mutations. In the cohort OS/RFS, the infiltration levels of CD8+ T cells, B cells, Macrophages, Neutrophils and DCs in high stromal score group were higher than those in the low score group (all P<0.001), as well as in immune score groups except for Macrophages in the cohort RFS. In the cohort OS/RFS, 317/379 upregulated genes and 9/6 downregulated genes were observed in the high immune score group, while 227/205 upregulated genes and 17/6 downregulated genes in the high stromal score group. With the analysis for prognostic value of DEGs, 82 and 58 DEGs respectively in the high immune and stromal score group were verified to be significantly associated with better OS (P<0.05), while 53 and 17 DEGs respectively with longer RFS (P<0.05). Functional enrichment analysis showed genes of prognostic values were significantly related to immune response.

Conclusions

A list of genes with prognostic value in PDAC microenvironment were obtained from functional enrichment analysis based on immune and stromal scores, which indicates a series of potential auxiliary prognostic biomarkers for PDAC are available. Further research on these genes may be valuable and helpful to understand the crosstalk between tumor and microenvironment, new immune evasion mechanisms and underlying novel therapeutic targets in an integrated manner.

Genomic testing for pancreatic cancer in clinical practice as real-world evidence

BACKGROUND

Precision medicine guided by comprehensive genome sequencing represents a potential treatment strategy for pancreatic cancer. However, clinical sequencing for pancreatic cancer entails several practical difficulties. We have launched an in-house clinical sequencing system and started genomic testing for patients with cancer in clinical practice. We have analyzed the clinical utility of this system in pancreatic cancer.

METHODS

We retrospectively reviewed 20 patients with pancreatic cancer who visited our division. Genomic DNA was extracted from both tumor tissue and peripheral blood mononuclear cells obtained from the patients. We performed a comprehensive genomic testing using targeted amplicon sequencing for 160 cancer-related genes. The primary endpoints were the detection rates of potential actionable and druggable gene alterations. The secondary endpoints were the detection rate of secondary germline findings, the rate of re-biopsy required for genome sequencing, survival time after the initial visit (post-sequencing survival time), and turnaround time.

RESULTS

Although re-biopsy was required for 25% (5/20) of all patients, genomic testing was performed in all patients. Actionable and druggable gene alterations were detected in 100% (20/20) and 35% (7/20) of patients, respectively, whereas secondary germline findings were detected in 5% (1/20) of patients. The median turnaround times for physicians and patients were 20 and 26 days, respectively. The median post-sequencing survival time was 10.3 months. Only 10% (2/20) of all patients were treated with therapeutic agents based on the outcomes of genomic testing.

CONCLUSIONS

The clinical application of comprehensive genomic testing for pancreatic cancer was feasible and promising in clinical practice.