3.1 Gene Ontology and Canonical Pathway Analysis in three subgroups
We explore the biological and functional difference in three subgroups based on the differential expressed genes, especially the immune response and tumor microenvironment. Firstly, a total of 5699 DEGs were calculated in KIRC relative to normal tissue, including 3804 up-regulated and 1895 down-regulated genes(Fig. 1A); In KIRP relative to normal tissue, 4896 genes were differentially expressed including 2899 up-regulated and 1997 down-regulated genes(Fig. 1B); 5759 of genes significantly differentially expressed in KICH relative to normal tissue, with 2685 up-regulated and 3074 down-regulated genes (Fig. 1C). Further exploration, a total of 1208 intersection genes among the three subgroups were screened including 607 up-regulated and 601 down-regulated genes (Fig. 1D).
Among all the GO-terms, only 786 (27.7%) intersected among the three subgroups (Supplemental Figure1A). GO-enrichment analysis revealed that among the DEGs were those involved in cell differentiation, meiotic cell cycle, cell maturation, DNA transcription, growth factor activity, leukocyte migration, and DNA repair. These processes were involved in cancer progress and play critical role in the initiation and promotion of tumorigenesis (Supplemental Figure1B). When we looked at the GO-terms in each subgroup of RCC, we noticed that, immune response process was enriched in KIRC, such as T cell differentiation, T cell activation, cell killing, leukocyte proliferation, lymphocyte proliferation and cytokine secretion (Supplemental Figure1C). What’s more, we found GO-terms in KIRP were related with metabolism of organic and inorganic matter, such as response to lipopolysaccharide and carbohydrate binding. Interestingly, the immune response also was enriched in KIRP, such as interleukin-1 production, mononuclear cell proliferation and mononuclear cell migration (Supplemental Figure1D). In KICH, more biological functions were seemed to be involve in regulation of synaptic plasticity, kidney morphogenesis, axoneme, and metabolic process (Supplemental Figure1E).
Pathways analysis identified 73, 77 and 73 altered pathways in KICH, KIRC, and KIRP, respectively (FDR<0.05) (Supplemental Figure2A). The top 10 pathways of each subgroups were screened compared with normal tissue. Among them, a total of 32 pathways were common to each subgroup. Cytokine-cytokine receptor interaction, cell adhesion molecules (CAMs), calcium signaling pathway, ECM-receptor interaction, steroid hormone biosynthesis and PPAR signaling pathway were the most significant changed pathways in each subgroup of RCC(Supplemental Figure2B). The tope dysregulated pathways detected in KIRC were more activated mainly associated with immune response (Supplemental Figure2C), such as Th1 and Th2 cell differentiation, Allograft rejection, Graft-versus-host disease, Th17 cell differentiation, Natural killer cell mediated cytotoxicity. Besides, the cancer-related signal pathways also were more activated compared with normal tissue, such as Transcriptional misregulation in cancer, Chemokine signaling pathway, JAK-STAT signaling pathway, and Rap1 signaling pathway. We found the KEGG pathways was only enriched in KIRP (Supplemental Figure2D), such as p53 signaling pathway, cGMP-PKG signaling pathway, Primary immunodeficiency, PI3K-Akt signaling pathway, PI3K-Akt signaling pathway, Wnt-catenin formation, and Tyrosine metabolism. This founding indicated that most cancer-related pathways were activated compared with normal tissue. KEGG analysis for all differentially expressed genes in KICH compared with normal tissue revealed TGF-beta signaling pathway, MAPK signaling pathway, cAMP signaling pathway, Chemical carcinogenesis, Cholesterol metabolism, Complement and coagulation cascades, and Cholesterol metabolism at the top cancer-related pathways, not disclosed in KIRC and KIRP(Supplemental Figure2E). Overall, these pathways and GO-terms results indicated that cell migration, cancer-related signal pathways play an important role in KICH.
3.2 CD8+ T cell infiltration in RCC is associated with the three subtypes
Based on the GO and KEGG analysis, the immune infiltration was found to be different in three subtypes. CD8+ cytolytic T cells (CTLs) recruitment also reflect immune cell infiltration by measuring CD8A expression. Immune cell cytolytic activity (CYT) by measuring the mRNA expression levels of granzyme A (GZMA) and perforin 1 (PRF1) are a prerequisite for effective antitumor killing. We obtained RNAseq from TCGA to explore if the CD8+ cytolytic T cell was associated with molecular subtypes. Interestingly, we found CD8A was highest in KIRC compared with the rest of two subtypes(Fig. 2B), meanwhile, the KIRP has a higher CD8+ cytolytic T cell infiltration relative to KICH, but CYT levels in KIRP was lower than KICH (Fig. 2B), so it’s necessary to further explore. In addition, pathological type of RCC are found to have opposite trends in immune cell score and tumor purity based on ESTIMATE package of R(Fig. 2A), with tumor purity increasing from KIRC to KICH (KIRC<KIRP<KICH) and immune cell score decreasing from KIRC to KICH (KIRC> KIRP> KICH). In a short, these results may indicate that KIRC raised highest number of CD8+ T cell infiltration, while the KICH contained the lowest levels.
3.3 Distinct immune landscape associated with three subtypes in RCC
The different immune-related pathways and CD8+ T cell infiltration among the three subtypes of RCC make us to explore the immune landscape in three subtypes. The ssGSEA confirmed an expected main difference in expression of marker gene sets for immune landscape (Fig. 3A), including gradually increasing expression of marker gene sets for most of T cell subpopulations (CD4 and CD8 T cell, Natural killer T cell, Gamma delta T cell, Type 1 T helper cell, Regulatory T cell (treg), T follicular helper cell) from KICH to KIRC (KICH< KIRP< KIRC). Interestingly, Type 17 T helper cell was enriched highest level in KIRP, while this kind of subtype have lowest dense of Type 1 T helper cell relative to KIRC and KICH. In addition, some of innate immune cells including Macrophage, Mast cell, MDSC, Neutrophil, Activated and Immature dendritic cell were also gradually increasing from KICH to KIRC (KICH< KIRP< KIRC), exclusive of Eosinophil, Monocyte, CD56 natural killer cell, which suggest that the higher activation of effector and professional antigen-presenting immune process in KIRC. On the other hand, T cell priming and activity, including T cell co-stimulation, T cell co- inhibition and IFN expression also was explored based on ssGSEA (Fig. 3B). Besides, exhaustion T cell could indicate the immune process, especially immune evasion, we found KIRC has highest T cell exhaustion level according to gene sets (CTLA4, PD1, TIM3, LAG3, PDL1, and FASLG). Importantly, we found enrichment of T cell inflamed gene expression profiles (Parainflammation and Inflammation), which could be used as a predictive of response to immunotherapy in tumor(Fig. 3C).
3.4 Differences in APC related to molecular subtypes
Dendritic cell (DC), as the most important antigen presenting cells (APC), play a critical role in innate immunity and adaptive new immunity, and as the only member of activating naïve T cell, DC has been paid more and more attention. We thus explored the process associated with DC maturation and T cell activation. From our above analysis, we found gradually increasing of immune signaling pathways and DC activation from KICH to KIRC. In addition, APC function could be reflected by the expression of gene sets including MHC Class I, HLA family, APC Co-inhibition, APC Co-stimulation and we observed the KIRC present highest levels compared with others(Fig. 4A). In addition, Pre-CDC differentiated into IRF4-dependent DC (IRF4-DC) and BATF3-dependent DC (BATF3-DC). Tissue DCS migrate to draining lymph nodes, where they show a mature phenotype, while the DCS stay in lymphoid organs always showed immature phenotype. The BARF3-DC development depends on the transcription factors IRF8 and BATF3, while the expression level RELB and IRF4 were critical to IRF4-DC mature (Fig. 4B). Our results reflected that the expression of BATF3-DC, LC, IRF4-DC signature were increasing from KICH to KIRC (KICH< KIRP< KIRC). Together, these results indicated KIRC was more closely associated with innate immune pathways and APC process which was critical to T cell activation.
3.5 The chemokine signatures difference among the three subtypes
Chemokines are increasingly recognized for their chemotactic effects, driving primed effector T cell recruitment into tumor, and the diversity of chemokine expression can mask the contribution of individual chemokine, then the 40 known human chemokines were explored in three subtypes respectively. We explored the relationship of all chemokines with cytolytic T cells in three subtypes(Fig. 5A), although active chemokines are similarity between KIRC and KIRP, we still found some chemokines were different, such as CXCL13 and CXCL16 which were more activity in immune response in KIRC than KIRP, while CCL25 and CXCL14 had the opposite trend. Previous report indicated that CXCL13/CXCR5 signaling modulates cancer cell ability to grow, proliferate, invade, and metastasize. There are specific examples of chemokines important in lymphoid development, of which the CCL25-CCR9 axis plays a critical role in T cell development in thymus. Our founding suggested that the different active chemokines between KIRC and KIRP may be critical biomarkers of the difference in immune mechanisms between them. The results also show that the active chemokines in KICH have huge variations compared with KIRC and KIRP, which indicated the immune response was different among them. When hematopoietic precursors from bone marrow colonize the thymus, the development of T cells in the thymus begins. Some chemokines participate in the seeding of the thymus rudiment by hematopoietic bone marrow precursors. Previous study found the CCR7 and CCR9, the ligands receptor of CCL19/CCL21 and CCL25, participate in this seeding process. Interestingly, we found KIRC has higher the three chemokines infiltration compared with KIRP, while the KICH has the highest infiltration of CCL21 and CCL25, thought above analysis found the CCL25 has lower correlation to cytolytic T cells, which mean that the KICH pay a more activity in this process [Fig. 5B].
More and more studies reported that multiple oncogenic mutations can affect the chemokine axes, which correlated with immune escape and tumor progress. The EGFR/Ras mutation in tumor cells induces a distinct chemokine repertoire, and tumors facilitate progression by the EGFR/Ras-induced production of CCL20. From Supplemental Figure2, we found the Ras signal was more active in KICH, which may could explain the reason why the CCL20 was highest active in KICH than the two subtypes. In the other hand, the presence of T cells correlated with the expression of CCL2, CCL3, CCL4, CCL5, CXCL9, and CXCL10 and the cognate receptors of these chemokines were found to be upregulated on CD8+ effector T cells, then we explored these chemokines in three subtypes. The results indicated CCL2, CCL3, CCL4, and CCL5 were gradually increasing from KICH to KIRC, but CXCL9, CXCL10 and CXCL11 were significantly higher in KICH compared with KIRP (Fig. 5C). From figure 7D, the top 30 mutation genes were found based on the data from TCGA, and we found TP53, MUC4, PTEN, ZAN, TTN were the highest mutation frequency in KICH, while TTN, MUC16, MET, KMT2C, SETD2 in KIRP, and VHL, PBRM1, TTN, SETD2, BAP1 in KIRC. Previous study confirmed that PTEN loss in triple-negative breast cancer increased downstream production of IRF3 targets including CXCL10 expression level, which was consistent with our founding. CCR5, receptor of CCL5, CCL3 and CCL4, were elevated in BAP1-mutant clear cell renal cell carcinoma, which also explain why KIRC has a higher immune response. In conclusion, we found that oncogenic mutations can affect the chemokine activation in three subtypes, which could change the immune response.
3.6 The immune difference in molecular subtypes was replicated in independent studies
Based on expression levels of above gene sets used in TCGA, the three subtypes (KIRC, KIRP, KICH) present the immune infiltration landscape in public gene sets. The similar results were found in our validation datasets (GSE15641 and GSE19949/GSE12090), the two datasets all showed that KIRC has a higher immune score, while KICH has the lowest immune score (Fig. 6B). The heatmap of GSE15641 show significant different immune landscape of the three subtypes (Fig. 6A). In conclusion, the immune landscape was distinct in the subtypes, and the immune cell infiltration were increasing from KICH to KIRC (KICH< KIRP< KIRC).
3.7 Comparison to normal tissues suggested Cytotoxic lymphocytes activation in KIRC tumors only
In our data, compared with their paired normal tissue, we found B lineage and CD3+ T cells showed either no change or lower population of immune cell in three subtypes relative to their normal tissues (Supplemental Figure3). Interestingly, we found the CD8 T cell and Cytotoxic lymphocytes were significantly higher activation in KIRC while KIRP and KICH didn’t show obvious activity relative to normal tissue. On the other hand, Monocytic lineage and Myeloid dendritic cells were more activity in KIRC and KIRP, though the latter is relatively lower, while the two kinds of immune cells have lower population of immune cell in KICH. As for NK cells, though our above analysis confirmed that KICH has a lower infiltration relative to KIRP, NK cells was found to be more activity in KICH relative to their normal tissue.