Transcriptional reprogramming of tumor-infiltrating T cells during PD-1 blockade revealed through gene regulatory network and trajectory inference in squamous cell carcinoma

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The paper analyzed a publicly available single-cell RNA-seq dataset of 25,581 tumor-infiltrating T cells from squamous cell carcinoma to reconstruct differentiation trajectories before and after anti–PD-1 therapy, using trajectory inference and gene regulatory network inference. In CD8+ T cells, PD-1 blockade enhanced transitions from memory to activated states, implicating IL-12–associated pathways, and uncovered a memory-to-exhaustion trajectory driven by regulatory activity of EOMES and TCF7. Gene regulatory network results showed therapy-induced transcriptional rewiring that distinguished precursor exhausted (Tpex) from terminally exhausted (Tex) states, while CD4+ T cells displayed trajectory and functional shifts with increased CXCL13+ Tfh programs and reduced numbers of but more transcriptionally active Tregs. A key caveat is that the work relies on one publicly available SCC dataset rather than generating new cohorts. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract Understanding the tumor microenvironment is crucial for optimizing anti-cancer immune responses. At single-cell resolution, trajectory inference methods can reconstruct the dynamic transitions between cell states during differentiation. Immune checkpoint blockade (ICB) therapies, such as PD-1/PD-L1 inhibitors, are used across multiple cancers, including non-melanoma skin cancers (NMSCs), yet the transcriptional mechanisms that shape T cell responses in this context remain unclear. Here, we analyzed a publicly available squamous cell carcinoma (SCC) single-cell RNA-seq dataset comprising 25,581 tumor-infiltrating T-cell profiles to map differentiation trajectories before and after anti-PD-1 therapy. In CD8+ T cells, therapy enhanced the transition from memory to activated states, prominently involving IL-12–associated pathways, and revealed a distinct memory-to-exhaustion trajectory driven by EOMES and TCF7 regulatory activity. Gene regulatory network inference further revealed therapy-induced transcriptional rewiring distinguishing precursor exhausted (Tpex) from terminally exhausted (Tex) states. CD4+ T cell populations also underwent substantial reshaping, with trajectory and functional analyses highlighting therapy-driven programs that enhanced CXCL13+ Tfh responses while generating fewer but more transcriptionally active Tregs. Together, these findings reveal a dual remodeling of helper and cytotoxic T cell compartments upon PD-1 blockade, define key transcriptional regulators controlling cell-state transitions, and identify potential molecular targets and biomarkers to predict and enhance treatment response. Competing Interest Statement The authors have declared no competing interest.

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last seen: 2026-05-20T01:45:00.602351+00:00