Integrative single-cell and pan-cancer analyses identify LINC01871 and TBX21 as candidate regulators of antitumor T-cell immunity in breast cancer

Technical Summary: Integrative Single-Cell and Pan-Cancer Analyses Identify LINC01871 and TBX21 as Candidate Regulators of Antitumor T-Cell Immunity in Breast Cancer

Problem Statement

While immune checkpoint blockade (ICB) has improved outcomes for a subset of breast cancer patients, particularly in triple-negative breast cancer, the molecular determinants driving effective CD8⁺ T-cell responses remain incompletely understood. Current biomarkers, such as PD-L1 immunohistochemistry and tumor mutational burden, fail to capture the full biological complexity of therapeutic response. Bulk transcriptomic profiling often obscures the functional heterogeneity of tumor-infiltrating lymphocytes, failing to distinguish between genuinely cytotoxic, inflamed tumors and those infiltrated by dysfunctional or exhausted cells. Conversely, single-cell RNA sequencing (scRNA-seq) provides high-resolution immune state definitions but often lacks the large-scale clinical survival data necessary for prognostic validation. There is a need for an integrative framework that combines single-cell resolution with large-scale clinical cohorts to define clinically relevant CD8⁺ T-cell activity programs and identify novel therapeutic targets.

Methodology

The authors employed a multi-step integrative approach combining single-cell transcriptomics, bulk RNA-sequencing, and network-based computational modeling:

1. Single-Cell Atlas Construction: scRNA-seq data from primary breast tumors, breast cancer brain metastases, and normal tissues (GSE281490, GSE281580) were processed using Seurat. Cells were filtered, normalized, and integrated to correct batch effects. Unsupervised clustering identified 22 clusters collapsed into nine lineages, with the T-cell compartment further resolved into six states (regulatory, naive CD8⁺, effector CD8⁺, exhausted CD8⁺, γδ T, and NKT).
2. Co-expression Network Analysis: Genes co-expressed with the cytotoxic CD8⁺ T-cell state were identified via correlation analysis. This network was subjected to Gene Ontology (GO) and KEGG pathway enrichment to define a coordinated "T-cell activity programme."
3. Prognostic Signature Derivation: Using bulk RNA-seq data from The Cancer Genome Atlas (TCGA) breast cancer cohort (n=240 network genes), genes were screened via univariate Cox regression. A LASSO-penalized Cox regression model, optimized via ten-fold cross-validation, reduced the gene set to an eight-gene signature: CCL5, TBX21, LINC01871, PLA2G2D, GFI1, KLRB1, CCR7, and PTPN7.
4. Clinical and Immune Validation: A risk score was calculated for TCGA patients. Survival was analyzed using Kaplan–Meier curves and time-dependent ROC. A nomogram integrating the risk score with age, sex, and tumor stage was constructed. Immune infiltration was estimated using CIBERSORT, and functional states were assessed via single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE scores.
5. Pan-Cancer and In Silico Knockout Analysis: The signature genes were evaluated across 33 TCGA cancer types for differential expression and survival association. Furthermore, network-based in silico knockout analysis (using scTenifoldKnk) was performed on KLRB1, LINC01871, PTPN7, and TBX21 to predict their dependency roles within the CD8⁺ T-cell regulatory network.

Key Contributions and Results

• Definition of a CD8⁺ T-Cell Activity Programme: The study established a coordinated network of genes associated with cytotoxic CD8⁺ T-cells, encompassing effector function (e.g., GZMK, GZMB, PRF1), T-cell receptor signaling, and immune checkpoint regulation. This network captures both the machinery for tumor killing and the mechanisms that restrain it.
• Development of an Eight-Gene Prognostic Signature: The derived signature (CCL5, TBX21, LINC01871, PLA2G2D, GFI1, KLRB1, CCR7, PTPN7) successfully stratified breast cancer patients into high- and low-risk groups. High-risk patients exhibited significantly shorter overall survival. The signature provided prognostic information independent of tumor stage, age, and sex, with time-dependent AUCs of 0.65, 0.68, and 0.63 at 1, 3, and 5 years, respectively.
• Characterization of the Tumor Immune Microenvironment (TME): Low-risk tumors (high signature expression) were characterized by an "inflamed" phenotype: enrichment of CD8⁺ T cells, activated memory CD4⁺ T cells, and M1 macrophages, alongside high expression of cytotoxic molecules (GZMB, PRF1) and checkpoint genes (PDCD1, CTLA4, HAVCR2). This suggests the signature identifies tumors with pre-existing antitumor immunity under adaptive immune restraint, potentially making them more amenable to ICB.
• Pan-Cancer Prioritization of LINC01871 and TBX21: Across 33 cancer types, LINC01871 and TBX21 were generally downregulated in tumors compared to normal tissue. However, higher expression of either gene correlated with longer survival and was enriched in immunologically active molecular subtypes (C2 and C3).
• Identification of Network Dependencies: In silico knockout of KLRB1, LINC01871, PTPN7, or TBX21 predicted a coordinated disruption of the cytotoxic CD8⁺ T-cell program, affecting genes involved in T-cell receptor signaling, lymphocyte activation, and cytotoxic effector function (e.g., CCL5, CD8A, GZMB). This suggests these genes are not merely correlates but potential regulatory dependencies sustaining the effector program.

Significance and Claims

The authors claim that this study defines a clinically relevant, biologically grounded transcriptional readout of CD8⁺ T-cell activity in breast cancer. By integrating single-cell definitions with large-scale clinical data, the study moves beyond simple cell abundance to characterize the functional state of the TME.

The primary significance lies in the identification of LINC01871 and TBX21 as candidate regulators of antitumor immunity.

• TBX21 (encoding T-bet) is a known master regulator of type 1 immunity; its inclusion validates the analytical framework.
• LINC01871, a poorly characterized long non-coding RNA, is highlighted as a novel candidate. Its consistent concordance with TBX21 across multiple analyses, its downregulation in tumors, and the predicted disruption of the cytotoxic program upon its loss position it as a potential therapeutic target rather than a passive prognostic marker.

The authors conclude that these findings nominate LINC01871 and TBX21 for further mechanistic evaluation as modulators of antitumor T-cell immunity. They propose that the eight-gene signature offers a framework for patient stratification, potentially identifying those most likely to benefit from immune checkpoint blockade.

Limitations and Modesty

The authors explicitly acknowledge several limitations:

• The single-cell cohort was relatively small and included brain metastases, meaning the identified T-cell states may not fully capture primary tumor heterogeneity.
• The signature has not yet been validated in an independent external cohort or in a prospective immunotherapy-treated population.
• The in silico knockout results represent computationally inferred dependencies, not experimentally established causal relationships.
• The molecular function of LINC01871 and its specific regulatory relationship with TBX21 remain unresolved.

Consequently, the authors state that the next necessary steps involve gain- and loss-of-function experiments in primary human CD8⁺ T cells and immunocompetent breast cancer models to determine if these genes directly sustain cytotoxic function and can be therapeutically manipulated.