Journal for Immunotherapy of Cancer最新文献

Background: Patients with liver metastases of triple-negative breast cancer (TNBC) show poor prognosis compared with other metastases. Chemotherapy is the primary treatment for advanced TNBC. Tumor cell diversity and the tumor microenvironment could affect therapeutic effect. However, whether liver metastases of TNBC exhibit differential chemotherapy efficacy compared with the primary tumors remains inadequately understood. The specific mechanisms that modulate chemotherapy efficacy in liver metastases need further investigation.

Methods: Single-cell RNA sequencing data from public databases were leveraged to contrast the immune profiles of liver metastases and primary tumors in TNBC. Murine models bearing liver tumors or primary tumors of TNBC were used to evaluate chemotherapy efficacy. Techniques such as immunohistochemistry, wound healing assays, and colony formation assays were employed to account for tumor heterogeneity. Intratumoral T lymphocytes and macrophages were quantified and characterized using RNA sequencing, immunohistochemistry, and flow cytometry. Antibody-mediated depletion of CD8+T cells or macrophages in mice substantiated their impact on chemotherapy responses.

Results: Single-cell RNA sequencing data showed the immune microenvironments of liver metastases and primary tumors exhibited significant differences, which may critically influence chemotherapy outcomes. Mouse models confirmed that chemotherapy was less effective against liver tumors compared with subcutaneous tumors. After excluding the influence of tumor cell heterogeneity, the weaker responsiveness in liver tumors was mediated by the impeded infiltration of CD8+T cells, attributed to the decreased activation of macrophages. Augmenting macrophage activation can improve the chemotherapeutic efficacy in liver tumors. Moreover, chemotherapy drove the immune microenvironment towards increased suppression through distinct mechanisms, with neutrophil extracellular traps (NETs) accumulating in liver tumors and impaired functionality of macrophages at the primary site. The combination of NET inhibitors or macrophage activators with chemotherapy enhanced treatment effectiveness.

Conclusions: These findings disclose the compromised chemotherapeutic efficacy in liver tumors of TNBC and elucidate the underlying immune-related mechanisms within the tumor microenvironment. Targeting the specific underpinnings of immune suppression at different tumor sites with selective drugs could optimize chemotherapeutic efficacy.

Background: Some patients with non-small-cell lung cancer (NSCLC) benefit from immune checkpoint inhibitors (ICIs) despite programmed death-ligand 1 (PD-L1) expression. To address the mechanism of ICI resistance in PD-L1-positive NSCLC, we investigated the role of tumor-cell-intrinsic function of PD-L1 in interleukin (IL)-6-mediated immunosuppression.

Methods: Cohorts of NSCLC patients treated with ICI and public datasets were analyzed. PD-L1-overexpressing and PD-L1-knockdown NSCLC cells were submitted to RNA-seq, in vitro analyses, chromatin immunoprecipitation-qPCR, CUT&Tag, and biochemical assays. Human myeloid-derived suppressor cells (MDSCs) sorted from peripheral blood mononuclear cells were co-cultured with NSCLC cells and then assessed for their immunosuppressive activity on T-cells. Mouse Lewis lung carcinoma (LLC) cells with PD-L1 overexpression or knockdown were subcutaneously injected into wild-type or PD-1-knockout C57BL/6 mice in the presence of IL-6 and/or PD-1 blockade.

Results: In the ICI cohort with RNA-seq data, the IL-6/Jak/Stat3 pathway was enriched, and IL-6 expression was higher in patients with PD-L1-high NSCLCs who did not respond to ICIs. In another cohort, a higher baseline serum IL-6 level was associated with poor clinical outcomes after ICI therapy. IL-6 expression and the IL-6/Jak/Stat3 pathway were enhanced in PD-L1-high NSCLCs in the ICI cohorts and The Cancer Genome Atlas analysis. IL-6 expression correlated positively with tumor-infiltrating MDSCs in NSCLCs. In NSCLC cells, PD-L1 activated Jak2/Stat3 signaling by binding to and inhibiting protein tyrosine phosphatase 1B. PD-L1 also bound to p-Stat3 in the nucleus, thus promoting the activity of p-Stat3 in the transcription of several cytokines (IL-6, TGF-β, TNF-α, IL-1β) and chemokines. PD-L1-overexpressing NSCLC cells enhanced the migration and immunosuppressive activity of human MDSCs in vitro, mediated by IL-6 and CXCL1. In both wild-type and PD-1-knockout mice, PD-L1-overexpressing LLC tumors were infiltrated by increased MDSCs with high immunosuppressive function, increased Tregs, and decreased granzyme B⁺ or IFNγ⁺ CD8 T-cells. These responses were mediated by IL-6 secreted from PD-L1-overexpressing tumor cells. Combined blockade of PD-1 and IL-6 was effective in tumor control and decreased MDSCs while increasing granzyme B⁺ or IFNγ⁺ CD8 T-cells.

Conclusions: The tumor-cell-intrinsic function of PD-L1 drives immunosuppression and tumor progression through the PD-L1/Jak/Stat3/IL-6/MDSC axis. This pathway represents a potential therapeutic target to improve ICI efficacy in PD-L1-high NSCLC.

Background: The efficacy of immune checkpoint blockade (ICB) depends on restoring immune recognition of cancer cells that have evaded immune surveillance. Transforming growth factor-beta (TGFβ) is associated with immune-poor, so-called cold tumors whereas loss of its signaling promotes DNA misrepair that could stimulate immune response.

Methods: We analyzed transcriptomic data from IMvigor210, The Cancer Genome Atlas, and Tumor Immune Syngeneic MOuse data sets to evaluate the predictive value of high βAlt, a score representing low expression of a signature consisting of TGFβ targets and high expression of genes involved in error-prone DNA repair. The immune context of βAlt was assessed by evaluating tumor-educated immune signatures. An ICB-resistant, high βAlt preclinical tumor model was treated with a TGFβ inhibitor, radiation, and/or ICB and assessed for immune composition and tumor control.

Results: We found that a high βAlt score predicts ICB response yet is paradoxically associated with an immune-poor tumor microenvironmentcancer in both human and mouse tumors. We postulated that high βAlt cancers consist of cancer cells in which loss of TGFβ signaling generates a TGFβ rich, immunosuppressive tumor microenvironment. Accordingly, preclinical modeling showed that TGFβ inhibition followed by radiotherapy could convert an immune-poor, high βAlt tumor to an immune-rich, ICB-responsive tumor. Mechanistically, TGFβ inhibition increased activated natural killer (NK) cells, which were required to recruit lymphocytes to respond to ICB in irradiated tumors. NK cell activation signatures were also increased in high βAlt, cold mouse and human tumors that responded to ICB.

Conclusions: These studies indicate that loss of TGFβ signaling competency and gain of error-prone DNA repair identifies a subset of cold tumors that are responsive to ICB. Our mechanistic studies show that inhibiting TGFβ activity can convert a high βAlt, cold tumor into ICB-responsive tumors via NK cells. A biomarker consisting of combined TGFβ, DNA repair, and immune context signatures is a means to prospectively identify patients whose cancers may be converted from cold to hot with appropriate therapy.

Background: Current prognostic and predictive biomarkers for lung adenocarcinoma (LUAD) predominantly rely on unimodal approaches, limiting their characterization ability. There is an urgent need for a comprehensive and accurate biomarker to guide individualized adjuvant therapy decisions.

Methods: In this retrospective study, data from patients with resectable LUAD (stage I-III) were collected from two hospitals and a publicly available dataset, forming a training dataset (n=223), a validation dataset (n=95), a testing dataset (n=449), and the non-small cell lung cancer (NSCLC) Radiogenomics dataset (n=59). Tumor and peritumor scores were constructed from preoperative CT radiomics features (shape/intensity/texture). An immune score was derived from the density of tumor-infiltrating lymphocytes (TILs) within the cancer epithelium and stroma on hematoxylin and eosin-stained whole-slide images. A clinical score was constructed based on clinicopathological risk factors. A Cox regression model was employed to integrate these scores, thereby constructing a multimodal nomogram to predict disease-free survival (DFS). The adjuvant chemotherapy benefit rate was subsequently calculated based on this nomogram.

Results: The multimodal nomogram outperformed each of the unimodal scores in predicting DFS, with a C-index of 0.769 (vs 0.634-0.731) in the training dataset, 0.730 (vs 0.548-0.713) in the validation dataset, and 0.751 (vs 0.660-0.692) in the testing dataset. It was independently associated with DFS after adjusting for other clinicopathological risk factors (training dataset: HR=3.02, p<0.001; validation dataset: HR=2.33, p<0.001; testing dataset: HR=2.03, p=0.001). The adjuvant chemotherapy benefit rate effectively distinguished between patients benefiting from adjuvant chemotherapy and those from observation alone (interaction p<0.001). Furthermore, the high-/low-risk groups defined by the multimodal nomogram provided refined stratification of candidates for adjuvant chemotherapy identified by current guidelines (p<0.001). Gene set enrichment analyses using the NSCLC Radiogenomics dataset revealed associations between tumor/peritumor scores and pathways involved in epithelial-mesenchymal transition, angiogenesis, IL6-JAK-STAT3 signaling, and reactive oxidative species.

Conclusion: The multimodal nomogram, which incorporates tumor and peritumor morphology with anti-tumor immune response, provides superior prognostic accuracy compared with unimodal scores. Its defined adjuvant chemotherapy benefit rates can inform individualized adjuvant therapy decisions.

Background: The programmed cell death 1 (PD-1) is an immune checkpoint that mediates immune evasion of tumors. Alternative splicing (AS) such as intron retention (IR) plays a crucial role in the immune-related gene processing and its function. However, it is not clear whether PDCD1 encoding PD-1 exists as an IR splicing isoform and what underlying function of such isoform plays in tumor evasion.

Methods: An AS isoform of human PDCD1, characterized by the second IR and named PD-1^IR2, was identified by reverse transcription-PCR (RT-PCR) and Sanger sequencing. The expression profile of PD1^IR2 was assessed by quantitative RT-PCR and flow cytometry, while its function was evaluated through immune cell proliferation, cytokine interleukin 2 secretion, and tumor cell killing assays. PDCD1^{IR2 CKI} mice which specifically conditional knock-in PDCD1^IR2 in T cells and humanized peripheral blood mononuclear cells (PBMC)-NOG (NOD.Cg-PrkdcscidIL2rgtm1Sug/JicCrl) mice were utilized to further confirm the physiological function of PD-1^IR2 in vivo.

Results: PD-1^IR2 is expressed in a variety of human leukemia cell lines and tumor-infiltrating lymphocytes. PD-1^IR2 expression is induced on T cell activation and regulated by the RNA-binding protein hnRNPLL. PD-1^IR2 negatively regulates the immune function of CD8⁺ T cells, indicated by inhibiting T cell proliferation, cytokine production, and tumor cell killing in vitro. PD-1^IR2+ CD8⁺ T cells show impaired antitumor function, which consequently promote tumor evasion in a conditional knock-in mouse model and a PBMC-engrafted humanized NOG mouse model. PD-1^IR2 mice exhibit resistance to anti-PD-L1 therapy compared with wild-type mice.

Conclusions: PD-1^IR2 is a potential immune checkpoint that may mediate potential resistance to immune checkpoint therapy.

Background: Natural killer (NK) cells play a critical role in modulating immune responses by secreting soluble factors, including chemotactic cytokines. Our previous study demonstrated the potent antitumor activity of Chem_NK, referring to NK cells chemically primed with 25 kDa branched polyethyleneimine. However, the potential of Chem_NK secretomes to educate other NK cells and enhance their tumor-homing ability remains unexplored.

Methods: The effects of Chem_NK conditioned media (Chem CM) on NK cells were evaluated in vitro by examining chemokine receptor expression and migration toward cancer cells. In vivo, the impact of Chem_NK and Chem CM on endogenous NK cell populations was assessed using xenograft and syngeneic mouse tumor models. Cytokine array and signaling analyses were performed to identify factors secreted by Chem_NK and their role in activating recipient NK cells.

Results: Chem CM effectively educated NK cells in vitro, enhancing chemokine receptor expression and improving their migration toward cancer cells. In vivo, adoptively transferred Chem_NK increased endogenous NK cell populations within xenograft tumors. Furthermore, direct injection of Chem CM into a syngeneic mouse tumor model significantly promoted endogenous NK cell infiltration into tumors and suppressed lung metastasis. Cytokine analysis revealed that Chem_NK secreted high levels of cytokines, which activated ERK1/2 signaling in recipient NK cells, leading to upregulation of chemokine receptors.

Conclusions: Chem_NK secretomes effectively enhance the tumor-homing ability of NK cells and amplify antitumor efficacy by educating other NK cells. These findings offer novel insights into activated NK cell-mediated immune communication and highlight the therapeutic potential of NK cell-derived secretomes in cancer therapy.

Background: Intratumoral tertiary lymphoid structures (iTLS) in hepatocellular carcinoma (HCC) are associated with improved survival and may influence treatment decisions. However, their non-invasive detection remains challenging in HCC. We aim to develop a non-invasive model using baseline contrast-enhanced MRI to predict the iTLS status.

Methods: A total of 660 patients with HCC who underwent surgery were retrospectively recruited from four centers between October 2015 and January 2023 and divided into training, internal test, and external validation sets. After features dimensionality and selection, corresponding features were used to construct transfer learning radiomic (TLR) models for diagnosing iTLS, and model interpretability was explored with pathway analysis in The Cancer Genome Atlas-Liver HCC. The performances of models were assessed using the area under the receiver operating characteristic curve (AUC). The log-rank test was used to evaluate the prognostic value of the TLR model. The combination therapy set of 101 patients with advanced HCC treated with first-line anti-programmed death 1 or ligand 1 plus antiangiogenic treatment between January 2021 and January 2024 was used to investigate the value of the TLR model for evaluating the treatment response.

Results: The presence of iTLS was identified in 46.0% (n=308) patients. The TLR model demonstrated excellent performance in predicting the presence of iTLS in training (AUC=0.91, 95% CI: 0.87, 0.94), internal test (AUC=0.85, 95% CI: 0.77, 0.93) and external validation set (AUC=0.85, 95% CI: 0.81, 0.90). The TLR model-predicted iTLS group has favorable overall survival (HR=0.66; 95% CI: 0.48, 0.90; p=0.007) and relapse-free survival (HR=0.64; 95% CI: 0.48, 0.85; p=0.001) in the external validation set. The model-predicted iTLS status was associated with inflammatory response and specific tumor-associated signaling activation (all p<0.001). The proportion of treatment responders was significantly higher in the model-predicted group with iTLS than in the group without iTLS (36% vs 13.73%, p=0.009).

Conclusion: The TLR model has indicated accurate prediction of iTLS status, which may assist in the risk stratification for patients with HCC in clinical practice.