Multi-Omics Analysis Showed the Clinical Value of Gene Signatures of C1QC+ and SPP1+ TAMs in Cervical Cancer

Purpose To evaluate the value of C1QC(+) and SPP1(+) TAMs gene signatures in patients with cervical cancer. Methods We compare the C1QC(+) and SPP1(+) TAMs gene signatures with the M1/M2 gene signatures at single cell level and bulk RNA-seq level and evaluate which gene signature can clearly divide TAMs and patients with cervical cancer into distinct clinical subclusters better. Results At single-cell level, C1QC(+) and SPP1(+) TAMs gene signatures, but not M1 and M2 gene signatures, could clearly divided TAMs into two subclusters in a colon cancer data set and an advanced basal cell data set. For cervical cancer data from TCGA, patients with C1QC(high) and SPP1(low) TAMs gene signatures have the best prognosis, lowest proportion (34.21%) of locally advanced cervical cancer (LACC), and highest immune cell infiltration, whereas patients with C1QC(low) and SPP1(high) TAMs gene signatures have the worst prognosis, highest proportion (71.79%) of LACC and lowest immune cell infiltration. Patients with C1QC(high) and SPP1(low) TAMs gene signature have higher expression of most of the Immune checkpoint molecules (ICMs) than patients with C1QC(low) and SPP1(high) TAMs gene signatures. The GSEA results suggested that subgroups of patients divided by C1QC(+) and SPP1(+) TAMs gene signatures showed different anti- or pro-tumor state. Conclusion C1QC(+) and SPP1(+) TAMs gene signatures, but not M1/M2 gene signatures, can divide cervical patients into subgroups with different prognosis, tumor stage, different immune cell infiltration, and ICMs expression. Our findings may help to find suitable treatment strategy for cervical cancer patients with different TAMs gene signatures.

Automated summary

The C1QC(+) and SPP1(+) TAMs gene signatures provide valuable predictive information for cervical cancer patients, including prognosis, tumor stage, and immune cell infiltration levels. It also shows potential in guiding treatment decisions based on different TAMs gene signatures.