Novel Genetic Variants of ALG6 and GALNTL4 of the Glycosylation Pathway Predict Cutaneous Melanoma-Specific Survival

A genome-wide association study of germline variation and melanoma prognosis

Background

The high mortality of cutaneous melanoma (CM) is partly due to unpredictable patterns of disease progression in patients with early-stage lesions. The reliable prediction of advanced disease risk from early-stage CM, is an urgent clinical need, especially given the recent expansion of immune checkpoint inhibitor therapy to the adjuvant setting. In our study, we comprehensively investigated the role of germline variants as CM prognostic markers.

Methods

We performed a genome-wide association analysis in two independent cohorts of N=551 (discovery), and N=550 (validation) early-stage immunotherapy-naïve melanoma patients. A multivariable Cox proportional hazard regression model was used to identify associations with overall survival in the discovery group, followed by a validation analysis. Transcriptomic profiling and survival analysis were used to elucidate the biological relevance of candidate genes associated with CM progression.

Results

We found two independent associations of germline variants with melanoma prognosis. The alternate alleles of these two SNPs were both associated with an increased risk of death [rs60970102 in MELK: HR=3.14 (2.05-4.81), p=1.48×10^-7; and rs77480547 in SH3BP4: HR=3.02 (2.02-4.52), p=7.58×10^-8, both in the pooled cohort]. The addition of the combined risk alleles (CRA) of the identified variants into the prognostic model improved the predictive power, as opposed to a model of clinical covariates alone.

Conclusions

Our study provides suggestive evidence of novel melanoma germline prognostic markers, implicating two candidate genes: an oncogene MELK and a tumor suppressor SH3BP4, both previously suggested to affect CM progression. Pending further validation, these findings suggest that the genetic factors may improve the prognostic stratification of high-risk early-stage CM patients, and propose putative biological insights for potential therapeutic investigation of these targets to prevent aggressive outcome from early-stage melanoma.

The melanoma tumor glyco-code impacts human dendritic cells' functionality and dictates clinical outcomes

Subversion of immunity is a hallmark of cancer development. Dendritic cells (DCs) are strategic immune cells triggering anti-tumor immune responses, but tumor cells exploit their versatility to subvert their functions. Tumor cells harbor unusual glycosylation patterns, which can be sensed through glycan-binding receptors (lectins) expressed by immune cells that are crucial for DCs to shape and orientate antitumor immunity. Yet, the global tumor glyco-code and its impact on immunity has not been explored in melanoma. To decrypt the potential link between aberrant glycosylation patterns and immune evasion in melanoma, we investigated the melanoma tumor glyco-code through the GLYcoPROFILE™ methodology (lectin arrays), and depicted its impact on patients' clinical outcome and DC subsets' functionality. Specific glycan patterns correlated with clinical outcome of melanoma patients, GlcNAc, NeuAc, TF-Ag and Fuc motifs being associated with poor outcome, whereas Man and Glc residues elicited better survival. Strikingly, tumor cells differentially impacting cytokine production by DCs harbored distinct glyco-profiles. GlcNAc exhibited a negative influence on cDC2s, whereas Fuc and Gal displayed inhibitory impacts on cDC1s and pDCs. We further identified potential booster glycans for cDC1s and pDCs. Targeting specific glycans on melanoma tumor cells restored DCs' functionality. The tumor glyco-code was also linked to the nature of the immune infiltrate. This study unveils the impact of melanoma glycan patterns on immunity, and paves the way for innovative therapeutic options. Glycans/lectins interactions arise as promising immune checkpoints to rescue DCs from tumor' hijacking to reshape antitumor immunity and inhibit immunosuppressive circuits triggered by aberrant tumor glycosylation.

Unique CLR expression patterns on circulating and tumor-infiltrating DC subsets correlated with clinical outcome in melanoma patients

Subversion of immunity by tumors is a crucial step for their development. Dendritic cells (DCs) are strategic immune cells that orchestrate anti-tumor immune responses but display altered functions in cancer. The bases for such DCs' hijacking are not fully understood. Tumor cells harbor unusual glycosylation patterns of surface glycoproteins and glycolipids. DCs express glycan-binding receptors, named C-type lectin receptors (CLR), allowing them to sense changes in glycan signature of their environment, and subsequently trigger a response. Recognition of tumor glycans by CLRs is crucial for DCs to shape antitumor immunity, and decisive in the orientation of the response. Yet the status of the CLR machinery on DCs in cancer, especially melanoma, remained largely unknown. We explored CLR expression patterns on circulating and tumor-infiltrating cDC1s, cDC2s, and pDCs of melanoma patients, assessed their clinical relevance, and further depicted the correlations between CLR expression profiles and DCs' features. For the first time, we highlighted that the CLR repertoire of circulating and tumor-infiltrating cDC1s, cDC2s, and pDCs was strongly perturbed in melanoma patients, with modulation of DCIR, CLEC-12α and NKp44 on circulating DCs, and perturbation of Dectin-1, CD206, DEC205, DC-SIGN and CLEC-9α on tumor-infiltrating DCs. Furthermore, melanoma tumor cells directly altered CLR expression profiles of healthy DC subsets, and this was associated with specific glycan patterns (Man, Fuc, GlcNAc) that may interact with DCs through CLR molecules. Notably, specific CLR expression profiles on DC subsets correlated with unique DCs' activation status and functionality and were associated with clinical outcome of melanoma patients. Higher proportions of DCIR-, DEC205-, CLEC-12α-expressing cDCs were linked with a better survival, whereas elevated proportions of CD206-, Dectin1-expressing cDCs and NKp44-expressing pDCs were associated with a poor outcome. Thus, melanoma tumor may shape DCs' features by exploiting the plasticity of the CLR machinery. Our study revealed that melanoma manipulates CLR pathways to hijack DC subsets and escape from immune control. It further paved the way to exploit glycan-lectin interactions for the design of innovative therapeutic strategies, which exploit DCs' potentialities while avoiding hijacking by tumor, to properly reshape anti-tumor immunity by manipulating the CLR machinery.

Integrated Multi-Omics Data Analysis Reveals Associations Between Glycosylation and Stemness in Hepatocellular Carcinoma

Background

Glycosylation plays an essential role in driving the progression and treatment resistance of hepatocellular carcinoma (HCC). However, its function in regulating the acquisition and maintenance of the cancer stemness-like phenotype in HCC remains largely unknown. There is also very little known about how CAD and other potential glycosylation regulators may influence stemness. This study explores the relationship between glycosylation and stemness in HCC.

Methods

Gene set variance analysis (GSVA) was used to assess the TCGA pan-cancer enrichment in glycosylation-related pathways. Univariate, LASSO, and multivariate COX regression were then used to identify prognostic genes in the TCGA-LIHC and construct a prognostic signature. HCC patients were classified into high- and low-risk subgroups based on the signature. The relationship between gene expression profiles and stemness was confirmed using bulk and single-cell RNA-sequencing data. The role of CAD and other genes in regulating the stemness of HCC was also validated by RT-qPCR, CCK-8, and colony formation assay. Copy number variation (CNV), immune infiltration, and clinical features were further analyzed in different subgroups and subsequent gene expression profiles. Sensitive drugs were also screened.

Results

In the pan-cancer analysis, HCC was shown to have specific glycosylation alterations. Five genes, CAD, SLC51B, LGALS3, B3GAT3, and MT3, identified from 572 glycosylation-related genes, were used to construct a gene signature and predict HCC patient survival in the TCGA cohort. The results demonstrated a significant positive correlation between patients in the high-risk group and both elevated gene expression and HCC dedifferentiation status. A significant reduction in the stemness-related markers, CD24, CD44, CD20, FOXM1, and EpCAM, was found after the knockdown of CAD and other genes in HepG2 and Huh7 cells. Frequent mutations increased CNVs, immune-suppressive responses, and poor prognosis were also associated with the high-risk profile. The ICGC-LIRI-JP cohort confirmed a similar relationship between glycosylation-related subtypes and stemness. Finally, 84 sensitive drugs were screened for abnormal glycosylation of HCC, and carfilzomib was most highly correlated with CAD.

Conclusions

Glycosylation-related molecular subtypes are associated with HCC stemness and disease prognosis. These results provide new directions for further research on the relationship between glycosylation and stemness phenotypes.

Where all the Roads Meet? A Crossover Perspective on Host Factors Regulating SARS-CoV-2 infection

COVID-19 caused by SARS-CoV-2 is the latest pandemic which has thrown the world into an unprecedented social and economic uncertainties along with huge loss to humanity. Identification of the host factors regulating the replication of SARS-CoV-2 in human host may help in the development of novel anti-viral therapies to combat the viral infection and spread. Recently, some research groups used genome-wide CRISPR/Cas screening to identify the host factors critical for the SARS-CoV-2 replication and infection. A comparative analysis of these significant host factors (p < 0.05) identified fifteen proteins common in these studies. Apart from ACE2 (receptor for SARS-CoV-2 attachment), other common host factors were CSNK2B, GDI2, SLC35B2, DDX51, VPS26A, ARPP-19, C1QTNF7, ALG6, LIMA1, COG3, COG8, BCOR, LRRN2 and TLR9. Additionally, viral interactome of these host factors revealed that many of them were associated with several SARS-CoV-2 proteins as well. Interestingly, some of these host factors have already been shown to be critical for the pathogenesis of other viruses suggesting their crucial role in virus-host interactions. Here, we review the functions of these host factors and their role in other diseases with special emphasis on viral diseases.

Robust Glycogene-Based Prognostic Signature for Proficient Mismatch Repair Colorectal Adenocarcinoma

Background

Proficient mismatch repair (pMMR) colorectal adenocarcinoma (CRAC) metastasizes to a greater extent than MMR-deficient CRAC. Prognostic biomarkers are preferred in clinical practice. However, traditional biomarkers screened directly from sequencing are often not robust and thus cannot be confidently utilized.

Methods

To circumvent the drawbacks of blind screening, we established a new strategy to identify prognostic biomarkers in the conserved and specific oncogenic pathway and its regulatory RNA network. We performed RNA sequencing (RNA-seq) for messenger RNA (mRNA) and noncoding RNA in six pMMR CRAC patients and constructed a glycosylation-related RNA regulatory network. Biomarkers were selected based on the network and their correlation with the clinicopathologic information and were validated in multiple centers (n = 775).

Results

We constructed a competing endogenous RNA (ceRNA) regulatory network using RNA-seq. Genes associated with glycosylation pathways were embedded within this scale-free network. Moreover, we further developed and validated a seven-glycogene prognosis signature, GlycoSig (B3GNT6, GALNT3, GALNT8, ALG8, STT3B, SRD5A3, and ALG6) that prognosticate poor-prognostic subtype for pMMR CRAC patients. This biomarker set was validated in multicenter datasets, demonstrating its robustness and wide applicability. We constructed a simple-to-use nomogram that integrated the risk score of GlycoSig and clinicopathological features of pMMR CRAC patients.

Conclusions

The seven-glycogene signature served as a novel and robust prognostic biomarker set for pMMR CRAC, highlighting the role of a dysregulated glycosylation network in poor prognosis.