Expression and prognostic significance of unique ULBPs in pancreatic cancer

Killer instincts: natural killer cells as multifactorial cancer immunotherapy

Natural killer (NK) cells integrate heterogeneous signals for activation and inhibition using germline-encoded receptors. These receptors are stochastically co-expressed, and their concurrent engagement and signaling can adjust the sensitivity of individual cells to putative targets. Against cancers, which mutate and evolve under therapeutic and immunologic pressure, the diversity for recognition provided by NK cells may be key to comprehensive cancer control. NK cells are already being trialled as adoptive cell therapy and targets for immunotherapeutic agents. However, strategies to leverage their naturally occurring diversity and agility have not yet been developed. In this review, we discuss the receptors and signaling pathways through which signals for activation or inhibition are generated in NK cells, focusing on their roles in cancer and potential as targets for immunotherapies. Finally, we consider the impacts of receptor co-expression and the potential to engage multiple pathways of NK cell reactivity to maximize the scope and strength of antitumor activities.

ULBP2 is a biomarker related to prognosis and immunity in colon cancer

The study aimed to determine whether ULBP2 was associated with prognosis and immune infiltration in colon cancer (CC) and provided important molecular basis in order to early non-invasive diagnosis and immunotherapy of CC. Using The Cancer Genome Atlas database (TCGA) and ImmPort database, we extracted messenger RNA (mRNA) data of CC and immune-related genes, then we used "limma" package, "survival" package, and Venn overlap analysis to obtain the differentially expressed mRNA (DEmRNA) associated with prognosis and immunity of CC patients. "pROC" package was used to analyze receiver operating characteristics (ROC) of target gene. We used chi-square test and two-class logistics model to identify clinicopathological parameters that correlated with target gene expression. In order to determine the effects of target gene expression and clinicopathological parameters on survival, univariate and multivariate cox regression analyses were performed. We analyzed the related functions and signaling pathways of target gene by enrichment analysis. Finally, the correlation between target gene and tumor immune infiltrating was explored by ssGSEA and spearman correlation analysis. Results showed that ULBP2 was a target gene associated with immunity and prognosis in CC patients. CC patients with higher ULBP2 expression had poor outcomes. In terms of ROC, ULBP2 had an area under the curve (AUC) of 0.984. ULBP2 was associated with T stage, N stage, and pathologic stage of CC patients, and served as an independent predictor of overall survival in CC patients. Functional enrichment analysis revealed ULBP2 was obviously enriched in pathways connected with carcinogenesis and immunosuppression. The expression of ULBP2 was significantly associated with tumor immune cells and immune checkpoints according to ssGSEA and spearman correlation analysis. To conclude, our study suggested that ULBP2 was associated with tumor immunity, and might be a biomarker associated with the diagnosis and prognosis of CC patients, and a potential target of CC immunotherapy.

Expressional regulation of NKG2DLs is associated with the tumor development and shortened overall survival in lung adenocarcinoma

Natural killer group 2D ligands (NKG2DLs) are expressed on tumor cells as a ligand for Natural killer group 2D (NKG2D) receptors. NKG2DLs interact with NKG2D to induce immune cell-mediated cytotoxicity for eliminating tumors. Studies demonstrated that tumor cells can reduce NKG2DLs' expression to escape from anti-tumor immunity, leading to an aggressive cancer phenotype and poor prognosis in some cancers. However, these studies are limited and there is no comprehensive work on the regulation of NKG2DLs in lung adenocarcinoma (LUAD) which is one of the deadliest cancers worldwide. Here, we conducted an in silico analysis to evaluate the changes in NKG2DLs in LUAD by analyzing The Cancer Genome Atlas and the Gene Expression Omnibus datasets including tumor vs. normal comparisons, TNM stages, survival and infiltrating immune estimation profile. Results indicated that some members of NKG2DL were downregulated in LUAD as compared to normal samples. We determined that MICA (MHC class I polypeptide-related sequence A) was the most and significantly downregulated ligand among others and the results were nearly consistent with the different datasets which we used. Furthermore, survival analysis revealed that down-regulated MICA transcript expression might be one of the prognostic indicators of LUAD. Interestingly, according to the immune cell infiltrating analysis, there wasn't a direct correlation between the MICA transcript expression and immune cell infiltration, while for MICB there was. In addition, in genetic alteration, DNA methylation and miRNA analyses, we did not observe critical outcomes that would clarify the down-regulated MICA expression in detail. Regardless, this study is highly comprehensive and contributes valuable suggestions to further functional studies about the regulation of NKG2DLs and promising immunotherapeutic approaches in LUAD.

High-throughput proteomics of breast cancer interstitial fluid: identification of tumor subtype-specific serologically relevant biomarkers

Despite significant advancements in breast cancer (BC) research, clinicians lack robust serological protein markers for accurate diagnostics and tumor stratification. Tumor interstitial fluid (TIF) accumulates aberrantly externalized proteins within the local tumor space, which can potentially gain access to the circulatory system. As such, TIF may represent a valuable starting point for identifying relevant tumor-specific serological biomarkers. The aim of the study was to perform comprehensive proteomic profiling of TIF to identify proteins associated with BC tumor status and subtype. A liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of 35 TIFs of three main subtypes: luminal (19), Her2 (4), and triple-negative (TNBC) (12) resulted in the identification of > 8800 proteins. Unsupervised hierarchical clustering segregated the TIF proteome into two major clusters, luminal and TNBC/Her2 subgroups. High-grade tumors enriched with tumor infiltrating lymphocytes (TILs) were also stratified from low-grade tumors. A consensus analysis approach, including differential abundance analysis, selection operator regression, and random forest returned a minimal set of 24 proteins associated with BC subtypes, receptor status, and TIL scoring. Among them, a panel of 10 proteins, AGR3, BCAM, CELSR1, MIEN1, NAT1, PIP4K2B, SEC23B, THTPA, TMEM51, and ULBP2, was found to stratify the tumor subtype-specific TIFs. In particular, upregulation of BCAM and CELSR1 differentiates luminal subtypes, while upregulation of MIEN1 differentiates Her2 subtypes. Immunohistochemistry analysis showed a direct correlation between protein abundance in TIFs and intratumor expression levels for all 10 proteins. Sensitivity and specificity were estimated for this protein panel by using an independent, comprehensive breast tumor proteome dataset. The results of this analysis strongly support our data, with eight of the proteins potentially representing biomarkers for stratification of BC subtypes. Five of the most representative proteomics databases currently available were also used to estimate the potential for these selected proteins to serve as putative serological markers.

NK cells in pancreatic cancer demonstrate impaired cytotoxicity and a regulatory IL-10 phenotype

Pancreatic ductal adenocarcinoma (PDAC) is one of the most common tumor subtypes and remains associated with very poor survival. T cell infiltration into tumor tissue is associated with improved clinical outcome but little is known regarding the potential role of NK cells in disease control. Here we analyze the phenotype and function of NK cells in the blood and tumor tissue from patients with PDAC. Peripheral NK cells are present in normal numbers but display a CD16hiCD57hi phenotype with marked downregulation of NKG2D. Importantly, these cells demonstrate reduced cytotoxic activity and low levels of IFN-γ expression but instead produce high levels of intracellular IL-10, an immunoregulatory cytokine found at increased levels in the blood of PDAC patients. In contrast, NK cells are largely excluded from tumor tissue where they display strong downregulation of both CD16 and CD57, a phenotype that was recapitulated in primary NK cells following co-culture with PDAC organoids. Moreover, expression of activatory proteins, including DNAM-1 and NKP30, was markedly suppressed and the DNAM-1 ligand PVR was strongly expressed on tumor cells. As such, in situ and peripheral NK cells display differential features in patients with PDAC and indicate local and systemic mechanisms by which the tumor can evade immune control. These findings offer a number of potential options for NK-based immunotherapy in the management of patients with PDAC.

Radiation therapy and the innate immune response: Clinical implications for immunotherapy approaches

Radiation therapy is an essential component of cancer care, contributing up to 40% of curative cancer treatment regimens. It creates DNA double-strand breaks causing cell death in highly replicating tumour cells. However, tumours can develop acquired resistance to therapy. The efficiency of radiation treatment has been increased by means of combining it with other approaches such as chemotherapy, molecule-targeted therapies and, in recent years, immunotherapy (IT). Cancer-cell apoptosis after radiation treatment causes an immunological reaction that contributes to eradicating the tumour via antigen presentation and subsequent T-cell activation. By contrast, radiotherapy also contributes to the formation of an immunosuppressive environment that hinders the efficacy of the therapy. Innate immune cells from myeloid and lymphoid origin show a very active role in both acquired resistance and antitumourigenic mechanisms. Therefore, many efforts are being made in order to reach a better understanding of the innate immunity reactions after radiation therapy (RT) and the design of new combinatorial IT strategies focused in these particular populations.

Papillary Thyroid Carcinoma Variants are Characterized by Co-dysregulation of Immune and Cancer Associated Genes

Papillary thyroid carcinoma (PTC) variants exhibit different prognosis, but critical characteristics of PTC variants that contribute to differences in pathogenesis are not well-known. This study aims to characterize dysregulated immune-associated and cancer-associated genes in three PTC subtypes to explore how the interplay between cancer and immune processes causes differential prognosis. RNA-sequencing data from The Cancer Genome Atlas (TCGA) were used to identify dysregulated genes in each variant. The dysregulation profiles of the subtypes were compared using functional pathways clustering and correlations to relevant clinical variables, genomic alterations, and microRNA regulation. We discovered that the dysregulation profiles of classical PTC (CPTC) and the tall cell variant (TCPTC) are similar and are distinct from that of the follicular variant (FVPTC). However, unique cancer or immune-associated genes are associated with clinical variables for each subtype. Cancer-related genes MUC1, FN1, and S100-family members were the most clinically relevant in CPTC, while APLN and IL16, both immune-related, were clinically relevant in FVPTC. RAET-family members, also immune-related, were clinically relevant in TCPTC. Collectively, our data suggest that dysregulation of both cancer and immune associated genes defines the gene expression landscapes of PTC variants, but different cancer or immune related genes may drive the phenotype of each variant.

A six-mRNA prognostic model to predict survival in head and neck squamous cell carcinoma

BACKGROUND

Transcriptional dysregulation is one of the most important features of cancer genesis and progression. Applying gene expression dysregulation information to predict the development of cancers is useful for cancer diagnosis. However, previous studies mainly focused on the relationship between a single gene and cancer. Prognostic prediction using combined gene models remains limited.

MATERIALS AND METHODS

Gene expression profiles were downloaded from The Cancer Genome Atlas and the data sets were randomly divided into training data sets and test data sets. A six-gene signature associated with head and neck squamous cell carcinoma (HNSCC) and overall survival (OS) was identified according to a training cohort by using weighted gene correlation network analysis and least absolute shrinkage and selection operator Cox regression. The test data set and gene expression omnibus (GEO) data set were used to validate this signature.

RESULTS

We identified six candidate genes, namely, FOXL2NB, PCOLCE2, SPINK6, ULBP2, KCNJ18, and RFPL1, and, using a six-gene model, predicted the risk of death of head and neck squamous cell carcinoma in The Cancer Genome Atlas. At a selected cutoff, patients were clustered into low- and high-risk groups. The OS curves of the two groups of patients had significant differences, and the time-dependent receiver operating characteristics of OS, disease-specific survival (DSS), and progression-free survival (PFS) were as high as 0.766, 0.731, and 0.623, respectively. Then, the test data set and the GEO data set were used to evaluate our model, and we found that the OS time in the high-risk group was significantly shorter than in the low-risk group in both data sets, and the receiver operating characteristics of test data set were 0.669, 0.675, and 0.614, respectively. Furthermore, univariate and multivariate Cox regression analyses showed that the risk score was independent of clinicopathological features.

CONCLUSION

The six-gene model could predict the OS of HNSCC patients and improve therapeutic decision-making.

Independent prognostic genes and mechanism investigation for colon cancer

PROPOSE

We aimed to explore the potential molecular mechanism and independent prognostic genes for colon cancer (CC).

METHODS

Microarray datasets GSE17536 and GSE39582 were downloaded from Gene Expression Omnibus. Meanwhile, the whole CC-related dataset were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNA (DEMs) were identified between cancer tissue samples and para-carcinoma tissue samples in TCGA dataset, followed by the KEGG pathway and GO function analyses. Furthermore, the clinical prognostic analysis including overall survival (OS) and disease-free survival (DFS) were performed in all three datasets.

RESULTS

A total of 633 up- and 321 down-regulated mRNAs were revealed in TCGA dataset. The up-regulated mRNAs were mainly assembled in functions including extracellular matrix and pathways including Wnt signaling. The down-regulated mRNAs were mainly assembled in functions like Digestion and pathways like Drug metabolism. Furthermore, up-regulation of UL16-binding protein 2 (ULBP2) was associated with OS in CC patients. A total of 12 DEMs including Surfactant Associated 2 (SFTA2) were potential DFS prognostic genes in CC patients. Meanwhile, the GRP and Transmembrane Protein 37 (TMEM37) were two outstanding independent DFS prognostic genes in CC.

CONCLUSIONS

ULBP2 might be a potential novel OS prognostic biomarker in CC, while GRP and TMEM37 could be served as the independent DFS prognostic genes in CC. Furthermore, functions including extracellular matrix and digestion, as well as pathways including Wnt signaling and drug metabolism might play important roles in the process of CC.