Background: This study aimed to explore the potentially predictive role and dynamic changes of immune checkpoints on T cell subsets in patients with breast cancer receiving neoadjuvant chemotherapies. Methods: Fluorescent multiplex immunohistochemistry (mIHC) was used to stain CD4, CD8, PD1, TIM3, and cytokeratins simultaneously in paired breast cancer samples before and after neoadjuvant therapies (NAT) in a prospective cohort (n = 50). Singleplex IHC was conducted to stain for CD3 in 100 cases with inclusion of extra retrospective 50 cases. Cell levels were correlated with clinicopathological parameters and pathological complete response (pCR). Results: In pretreatment tumors, the percentages of infiltrating CD8 + , PD1 + , PD1 + CD8 + , and the ratio of PD1 + CD8 + /CD8 + cells, were higher in pCR than non-pCR patients in either the stromal or intratumoral area, but PD1 + CD4 + , TIM3 + CD4 + , TIM3 + CD8 + cells and CD4 + /CD8 + ratio was not. Multivariate analyses showed that the percentage of intratumoral CD8 + cells (OR, 1.712; 95% CI: 1.052-2.786; P = 0.030) and stromal PD1 + CD8 + /CD8 + ratio (OR, 1.109; 95% CI: 1.009-1.218; P = 0.032) were significantly associated with pCR. Dynamically, reduction in the percentages of PD1 + , CD8 + and PD1 + CD8 + cells after therapy strongly correlated with pCR. Notably, incremental percentages of PD1 + CD8 + cells, rather than TIM3 + CD8 + , were shown in tumors from non-pCR patients after NAT. CD3 staining confirmed the percentage of T cells were associated with pCR. Conclusions: PD1 + CD8 + rather than TIM3 + CD8 + cells are main predictive components within tumor-infiltrating T cells in NAT breast cancer patients. Dynamically incremental levels of PD1 + CD8 + cells occurred in non-pCR cases after NAT, suggesting the combination of chemotherapy with PD1 inhibition might benefit these patients.

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Immune characteristics were reported correlated to benefit neoadjuvant chemotherapy (NAC) in breast cancer, yet integration of comprehensive genomic alterations and T-cell receptors (TCR) to predict efficacy of NAC needs further investigation. This study simultaneously analyzed TMB (Tumor Mutation Burden), TCRs, and TILs (tumor infiltrating lymphocyte) in breast cancers receiving NAC was conducted in a prospective cohort (n = 22). The next-generation sequencing technology-based analysis of genomic alterations and TCR repertoire in paired breast cancer samples before and after NAC was conducted in a prospective cohort (n = 22). Fluorescent multiplex immunohistochemistry was used to stain CD4, CD8, PD1, TIM3, and cytokeratins simultaneously in those paired samples. TMB in pretreatment tumor tissues and TCR diversity index are higher in non-pCR patients than in pCR patients (10.6 vs. 2.3; p = 0.043) (2.066 vs. 0.467; p = 0.010). TMB and TCR diversity index had linear correlation (y = 5.587x − 0.881; r = 0.522, p = 0.012). Moreover, infiltrating T cells are significantly at higher presence in pCR versus non-pCR patients. Dynamically, the TMB reduced significantly after therapy in non-pCR patients (p = 0.010) but without TCR index change. The CDR3 peptide AWRSAGNYNEQF is the most highly expressed in pre-NAC samples of pCR patients and in post-NAC samples of non-pCR patients. In addition to pCR, high clonality of TCR and high level of CD8+ expression are associated with disease-free survival (DFS). TCR index and TMB have significant interaction and may guide neo-adjuvant treatment in operable breast cancers. Response to NAC in tumors with high TCR clonality may be attributable to high infiltration and expansion of tumor-specific CD8 positive effector cells.

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System paclitaxel-based chemotherapy is the first-line treatment regimen of defense against breast cancer, but inherent or acquired chemotherapy resistance remains a major obstacle in breast cancer therapy. Elucidating the molecular mechanism of chemoresistance is essential to improve the outcome of patients with breast cancer. Here, we demonstrate that IFT20 is positively associated with shorter relapse-free survival in patients with system paclitaxel-based chemotherapy. High-expressed IFT20 in breast cancer cells increases resistance to cell death upon paclitaxel treatment; in contrast, IFT20 knockdown enhances apoptosis in breast cancer cells in response to paclitaxel. Mechanistically, IFT20 triggers β-arrestin-1 to bind with ASK1 and promotes the ubiquitination of ASK1 degradation, leading to attenuating ASK1 signaling and its downstream JNK cascades, which helps cells to escape from cell death during paclitaxel treatment. Our results reveal that IFT20 drives paclitaxel resistance through modulating ASK1 signaling and identifies IFT20 as a potential molecular biomarker for predicting the response to paclitaxel therapeutic in breast cancer. Implications: IFT20 drives paclitaxel resistance through modulating ASK1 signaling and IFT20 may act as a potential molecular biomarker for predicting the response to paclitaxel therapeutic in breast cancer.