SPI1 is a prognostic biomarker of immune infiltration and immunotherapy efficacy in clear cell renal cell carcinoma

Genetically driven predisposition leads to an unusually genomic unstable renal cell carcinoma

Renal cell carcinoma originates from the lining of the proximal convoluted renal tubule and represents the most common type of kidney cancer. Risk factors and comorbidities might be associated to renal cell carcinoma, while a small fraction of 2-3% emerges from patients with predisposing cancer syndromes, typically associated to hereditary mutations in VHL, folliculin, fumarate hydratase or MET genes. Here, we report a case of renal cell carcinoma in patient with concurrent germline mutations in BRCA1 and RAD51 genes. This case displays an unusual high mutational burden and chromosomal aberrations compared to the typical profile of renal cell carcinoma. Mutational analysis on whole genome sequencing revealed an enrichment of the MMR2 mutational signature, which is indicative of impaired DNA repair capacity. Overall, the tumor displayed a profile of unusual high genomic instability which suggests a possible origin from germline predisposing mutations in the DNA repair genes BRCA1 and RAD51. While BRCA1 and RAD51 germline mutations are well-characterised in breast and ovarian cancer, their role in renal cell carcinoma is still largely unexplored. The genomic instability detected in this case of renal cell carcinoma, along with the presence of unusual mutations, might offer support to clinicians for the development of patient-tailored therapies.

Deciphering the molecular and clinical characteristics of TREM2, HCST, and TYROBP in cancer immunity: A comprehensive pan-cancer study

Background

Hematopoietic cell signal transducer (HCST) and tyrosine kinase-binding protein (TYROBP) are triggering receptors expressed on myeloid cells 2 (TREM2), which are pivotal in the immune response to disease. Despite growing evidence underscoring the significance of TREM2, HCST, and TYROBP in certain forms of tumorigenesis, a comprehensive pan-cancer analysis of these proteins is lacking.

Methods

Multiple databases were synthesized to investigate the relationship between TREM2, HCST, TYROBP, and various cancer types. These include prognosis, methylation, regulation by long non-coding RNAs and transcription factors, immune signatures, pathway activity, microsatellite instability (MSI), tumor mutational burden (TMB), single-cell transcriptome profiling, and drug sensitivity.

Results

TREM2, HCST, and TYROBP displayed extensive somatic changes across numerous tumors, and their mRNA expression and methylation levels influenced patient outcomes across multiple cancer types. long non-coding RNA (lncRNA) -messenger RNA (mRNA) and TF-mRNA regulatory networks involving TREM2, HCST, and TYROBP were identified, with lncRNA MEG3 and the transcription factor SIP1 emerging as potential key regulators. Further immune analyses indicated that TREM2, HCST, and TYROBP play critical roles in immune-related pathways and macrophage differentiation, and may be significantly associated with TGF-β and SMAD9. Furthermore, the expression of TREM2, HCST, and TYROBP correlated with the immunotherapy markers TMB and MSI, and influenced sensitivity to immune-targeted drugs, thereby indicating their potential as predictors of immunotherapy outcomes.

Conclusion

This study offers valuable insights into the roles of TREM2, HCST, and TYROBP in tumor immunotherapy, suggesting their potential as prognostic markers and therapeutic targets for various cancers.

Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection

Background

The immune response associated with periprosthetic joint infection (PJI) is an emerging but relatively unexplored topic. The aim of this study was to investigate immune cell infiltration in periprosthetic tissues and identify potential immune-related biomarkers.

Methods

The GSE7103 dataset from the GEO database was selected as the data source. Differentially expressed genes (DEGs) and significant modular genes in weighted correlation network analysis (WGCNA) were identified. Functional enrichment analysis and transcription factor prediction were performed on the overlapping genes. Next, immune-related genes from the ImmPort database were matched. The protein-protein interaction (PPI) analysis was performed to identify hub genes. CIBERSORTx was used to evaluate the immune cell infiltration pattern. Spearman correlation analysis was used to evaluate the relationship between hub genes and immune cells.

Results

A total of 667 DEGs were identified between PJI and control samples, and 1847 PJI-related module genes were obtained in WGCNA. Enrichment analysis revealed that the common genes were mainly enriched in immune and host defense-related terms. TFEC, SPI1, and TWIST2 were the top three transcription factors. Three hub genes, SDC1, MMP9, and IGF1, were identified in the immune-related PPI network. Higher levels of plasma cells, CD4+ memory resting T cells, follicular helper T cells, resting mast cells, and neutrophils were found in the PJI group, while levels of M0 macrophages were lower. Notably, the expression of all three hub genes correlated with the infiltration levels of seven types of immune cells.

Conclusion

The present study revealed immune infiltration signatures in the periprosthetic tissues of PJI patients. SDC1, MMP9, and IGF1 were potential immune-related biomarkers for PJI.

Mapping inherited genetic variation with opposite effects on autoimmune disease and cancer identifies candidate drug targets associated with the anti-tumor immune response

Background

Germline alleles near genes that encode certain immune checkpoints (CTLA4, CD200) are associated with autoimmune/autoinflammatory disease and cancer but in opposite directions. This motivates a systematic search for additional germline alleles which demonstrate this pattern with the aim of identifying potential cancer immunotherapeutic targets using human genetic evidence.

Methods

Pairwise fixed effect cross-disorder meta-analyses combining genome-wide association studies (GWAS) for breast, prostate, ovarian and endometrial cancers (240,540 cases/317,000 controls) and seven autoimmune/autoinflammatory diseases (112,631 cases/895,386 controls) coupled with in silico follow-up. To ensure detection of alleles with opposite effects on cancer and autoimmune/autoinflammatory disease, the signs on the beta coefficients in the autoimmune/autoinflammatory GWAS were reversed prior to meta-analyses.

Results

Meta-analyses followed by linkage disequilibrium clumping identified 312 unique, independent lead variants with Pmeta<5x10-8 associated with at least one of the cancer types at Pcancer<10-3 and one of the autoimmune/autoinflammatory diseases at Pauto<10-3. At each lead variant, the allele that conferred autoimmune/autoinflammatory disease risk was protective for cancer. Mapping each lead variant to its nearest gene as its putative functional target and focusing on genes with established immunological effects implicated 32 of the nearest genes. Tumor bulk RNA-Seq data highlighted that the tumor expression of 5/32 genes (IRF1, IKZF1, SPI1, SH2B3, LAT) were each strongly correlated (Spearman's ρ>0.5) with at least one intra-tumor T/myeloid cell infiltration marker (CD4, CD8A, CD11B, CD45) in every one of the cancer types. Tumor single-cell RNA-Seq data from all cancer types showed that the five genes were more likely to be expressed in intra-tumor immune versus malignant cells. The five lead SNPs corresponding to these genes were linked to them via expression quantitative trait locus mechanisms and at least one additional line of functional evidence. Proteins encoded by the genes were predicted to be druggable.

Conclusion

We provide population-scale germline genetic and functional genomic evidence to support further evaluation of the proteins encoded by IRF1, IKZF1, SPI1, SH2B3, and LAT as possible targets for cancer immunotherapy.