Identification of a Five-Gene Prognostic Signature Related to B Cells Infiltration in Pancreatic Adenocarcinoma

Genome-scale CRISPR-Cas9 screening stratifies pancreatic cancer with distinct outcomes and immunotherapeutic efficacy

Pancreatic cancer (PC) was featured by dramatic heterogeneity and dismal outcomes. An ideal classification strategy capable of achieving risk stratification and individualized treatment is urgently needed to significantly improve prognosis. In this study, using the 105 prognostic cancer essential genes identified by genome-scale CRISPR-Cas9 screening and univariate Cox analysis, we established and verified three heterogeneous subtypes via non-negative matrix factorization (NMF) and nearest template prediction (NTP) algorithms in the TCGA-PAAD cohort (176 samples) and four multi-center cohorts (233 samples), respectively. Among them, C1 with the worst prognosis was enriched in immune-related pathways, possessed superior infiltration abundance of immune cells and immune checkpoint molecules expression, and might be most sensitive to immunotherapy. C3, owing a moderate prognosis, might be featured by proliferative biological function, and despite its highest immunogenicity, the defects in antigen processing and presentation ability coupled with barren immune environment render it ineffective for immunotherapy, while it had potential sensitivity to paclitaxel and methotrexate. Besides, C2 harbored the best prognosis and was characterized by metabolism-related functions. These results could deepen our understanding of PC molecular heterogeneity and provide a trustworthy reference for prognostic stratification management and precision medicine in clinical practice.

The genome of the pygmy right whale illuminates the evolution of rorquals

BACKGROUND

Baleen whales are a clade of gigantic and highly specialized marine mammals. Their genomes have been used to investigate their complex evolutionary history and to decipher the molecular mechanisms that allowed them to reach these dimensions. However, many unanswered questions remain, especially about the early radiation of rorquals and how cancer resistance interplays with their huge number of cells. The pygmy right whale is the smallest and most elusive among the baleen whales. It reaches only a fraction of the body length compared to its relatives and it is the only living member of an otherwise extinct family. This placement makes the pygmy right whale genome an interesting target to update the complex phylogenetic past of baleen whales, because it splits up an otherwise long branch that leads to the radiation of rorquals. Apart from that, genomic data of this species might help to investigate cancer resistance in large whales, since these mechanisms are not as important for the pygmy right whale as in other giant rorquals and right whales.

RESULTS

Here, we present a first de novo genome of the species and test its potential in phylogenomics and cancer research. To do so, we constructed a multi-species coalescent tree from fragments of a whole-genome alignment and quantified the amount of introgression in the early evolution of rorquals. Furthermore, a genome-wide comparison of selection rates between large and small-bodied baleen whales revealed a small set of conserved candidate genes with potential connections to cancer resistance.

CONCLUSIONS

Our results suggest that the evolution of rorquals is best described as a hard polytomy with a rapid radiation and high levels of introgression. The lack of shared positive selected genes between different large-bodied whale species supports a previously proposed convergent evolution of gigantism and hence cancer resistance in baleen whales.

Low Expression of CLEC2B Indicates Poor Prognosis in Melanoma

Background

Melanoma is a highly malignant skin tumor with a poor prognosis. Identification of novel biomarkers might potentially reveal the underlying mechanisms of melanoma progression.

Methods

We demonstrated the relationship between pan-cancer CLEC2B expression and melanoma samples in The Cancer Genome Atlas (TCGA) database. Next, the Kaplan-Meier plot and Cox regression analysis determined the prognostic value of CLEC2B in melanoma. Biological pathway enrichment was screened by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA), enabling the correlation analysis between the immune infiltration level and CLEC2B expression in melanoma. Our final claim was validated using qPCR, immunohistochemistry, Western blot, cell colony formation assays, ethynyldeoxyuridine (Edu) analysis, and cell Invasion assays.

Results

Our study revealed that the high CLEC2B expression correlates with poor overall survival of melanoma patients. Moreover, a low expression of CLEC2B was found in the A375 cell line. In addition, CLEC2B has significant prognostic value in melanoma diagnosis, with an AUC of 0.896. Prognostic analysis showed the low expression of CLEC2B to be independently associated with melanoma patients. Moreover, the expression of CLEC2B was significantly correlated with B cells, eosinophils, macrophages, neutrophils, NK cells, T helper cells, Tregs, Th1 cells, Th17 cells, and Th2 cells. PCR and immunohistochemistry indicated CLEC2B to be significantly downregulated in melanoma. The cell colony formation assay showed CLEC2B knockout increased the proliferation of A375 cells.

Conclusion

Our study established low levels of CLEC2B to be poor prognostic markers, enabling immunosuppressive cell infiltration in melanoma.

An integrative analysis to reveal that CLEC2B and ferroptosis may bridge the gap between psoriatic arthritis and cancer development

Patients with cutaneous psoriasis (PsC) and psoriatic arthritis (PsA) are reported with increased cancer risk, but the underlying mechanism is less clear, especially the association between the presence of PsA and cancer risk. Motivated by the role of ferroptosis in the progression of cancers as well as inflammation response in psoriasis, this experiment attempts to investigate the relationship between ferroptosis regulators and hub genes in PsA by bioinformatic analysis. The findings revealed an exclusive correlation between CISD1 (ferroptosis regulator) and CLEC2B (hub gene) in PsA group as well as multiple cancer types. Furthermore, CLEC2B was discovered differentially expressed in a variety of cancers and is closely associated with immune cell infiltration as well as immune checkpoints. These results indicate that ferroptosis may act as a bridge between psoriatic arthritis and the onset of certain malignancies.

Oxidation and reduction of actin: Origin, impact in vitro and functional consequences in vivo

Actin is among the most abundant proteins in eukaryotic cells and assembles into dynamic filamentous networks regulated by many actin binding proteins. The actin cytoskeleton must be finely tuned, both in space and time, to fulfill key cellular functions such as cell division, cell shape changes, phagocytosis and cell migration. While actin oxidation by reactive oxygen species (ROS) at non-physiological levels are known for long to impact on actin polymerization and on the cellular actin cytoskeleton, growing evidence shows that direct and reversible oxidation/reduction of specific actin amino acids plays an important and physiological role in regulating the actin cytoskeleton. In this review, we describe which actin amino acid residues can be selectively oxidized and reduced in many different ways (e.g. disulfide bond formation, glutathionylation, carbonylation, nitration, nitrosylation and other oxidations), the cellular enzymes at the origin of these post-translational modifications, and the impact of actin redox modifications both in vitro and in vivo. We show that the regulated balance of oxidation and reduction of key actin amino acid residues contributes to the control of actin filament polymerization and disassembly at the subcellular scale and highlight how improper redox modifications of actin can lead to pathological conditions.

A Novel Immunogenomic Signature to Predict Prognosis and Reveal Immune Infiltration Characteristics in Pancreatic Ductal Adenocarcinoma

Background

The immune response in the tumor microenvironment (TME) plays a crucial role in cancer progression and recurrence. We aimed to develop an immune-related gene (IRG) signature to improve prognostic predictive power and reveal the immune infiltration characteristics of pancreatic ductal adenocarcinoma (PDAC).

Methods

The Cancer Genome Atlas (TCGA) PDAC was used to construct a prognostic model as a training cohort. The International Cancer Genome Consortium (ICGC) and the Gene Expression Omnibus (GEO) databases were set as validation datasets. Prognostic genes were screened by using univariate Cox regression. Then, a novel optimal prognostic model was developed by using least absolute shrinkage and selection operator (LASSO) Cox regression. Cell type identification by estimating the relative subsets of RNA transcripts (CIBERSORT) and estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) algorithms were used to characterize tumor immune infiltrating patterns. The tumor immune dysfunction and exclusion (TIDE) algorithm was used to predict immunotherapy responsiveness.

Results

A prognostic signature based on five IRGs (MET, ERAP2, IL20RB, EREG, and SHC2) was constructed in TCGA-PDAC and comprehensively validated in ICGC and GEO cohorts. Multivariate Cox regression analysis demonstrated that this signature had an independent prognostic value. The area under the curve (AUC) values of the receiver operating characteristic (ROC) curve at 1, 3, and 5 years of survival were 0.724, 0.702, and 0.776, respectively. We further demonstrated that our signature has better prognostic performance than recently published ones and is superior to traditional clinical factors such as grade and tumor node metastasis classification (TNM) stage in predicting survival. Moreover, we found higher abundance of CD8+ T cells and lower M2-like macrophages in the low-risk group of TCGA-PDAC, and predicted a higher proportion of immunotherapeutic responders in the low-risk group.

Conclusions

We constructed an optimal prognostic model which had independent prognostic value and was comprehensively validated in external PDAC databases. Additionally, this five-genes signature could predict immune infiltration characteristics. Moreover, the signature helped stratify PDAC patients who might be more responsive to immunotherapy.