Background: Anti-PD-(L)1 immunotherapy has been recommended for non-small cell lung cancer (NSCLC) patients with lymph node metastases (LNM). However, the exact functional feature and spatial architecture of tumor-infiltrating CD8 + T cells remain unclear in these patients. Methods: Tissue microarrays (TMAs) from 279 IA-IIIB NSCLC samples were stained by multiplex immunofluorescence (mIF) for 11 markers (CD8, CD103, PD-1, Tim3, GZMB, CD4, Foxp3, CD31, αSMA, Hif-1α, pan-CK). We evaluated the density of CD8 + T-cell functional subsets, the mean nearest neighbor distance (mNND) between CD8 + T cells and neighboring cells, and the cancer-cell proximity score (CCPS) in invasive margin (IM) as well as tumor center (TC) to investigate their relationships with LNM and prognosis. Results: The densities of CD8 + T-cell functional subsets, including predysfunctional CD8 + T cells (T_predys) and dysfunctional CD8 + T cells (T_dys), in IM predominated over those in TC (P < 0.001). Multivariate analysis identified that the densities of CD8 + T_predys cells in TC and CD8 + T_dys cells in IM were significantly associated with LNM [OR = 0.51, 95%CI (0.29–0.88), P = 0.015; OR = 5.80, 95%CI (3.19–10.54), P < 0.001; respectively] and recurrence-free survival (RFS) [HR = 0.55, 95%CI (0.34–0.89), P = 0.014; HR = 2.49, 95%CI (1.60–4.13), P = 0.012; respectively], independent of clinicopathological factors. Additionally, shorter mNND between CD8 + T cells and their neighboring immunoregulatory cells indicated a stronger interplay network in the microenvironment of NSCLC patients with LNM and was associated with worse prognosis. Furthermore, analysis of CCPS suggested that cancer microvessels (CMVs) and cancer-associated fibroblasts (CAFs) selectively hindered CD8 + T cells from contacting with cancer cells, and were associated with the dysfunction of CD8 + T cells. Conclusion: Tumor-infiltrating CD8 + T cells were in a more dysfunctional status and in a more immunosuppressive microenvironment in patients with LNM compared with those without LNM.

Although immunotherapy has achieved great clinical success in clinical outcomes, especially the anti-PD-1 or anti-PD-L1 antibodies, not all patients respond to anti-PD-1 immunotherapy. It is urgently required for a clinical diagnosis to develop non-invasive imaging meditated strategy for assessing the expression level of PD-L1 in tumors. In this work, a 68Ga-labeled single-domain antibody tracer, 68Ga-NOTA-Nb109, was designed for specific and noninvasive imaging of PD-L1 expression in an MC38 tumor-bearing mouse model. Comprehensive studies including Positron Emission Tomography (PET), biodistribution, blocking studies, immunohistochemistry, and immunotherapy, have been performed in differences PD-L1 expression tumor-bearing models. These results revealed that 68Ga-NOTA-Nb109 specifically accumulated in the MC38-hPD-L1 tumor. The content of this nanobody in MC38 hPD-L1 tumor and MC38 Mixed tumor was 8.2 ± 1.3, 7.3 ± 1.2, 3.7 ± 1.5, 2.3 ± 1.2%ID/g and 7.5 ± 1.4, 3.6 ± 1.7, 1.7 ± 0.6, 1.2 ± 0.5%ID/g at 0.5, 1, 1.5, 2 hours post-injection, respectively. 68Ga-NOTA-Nb109 has the potential to further noninvasive PET imaging and therapy effectiveness assessments based on the PD-L1 status in tumors. To explore the possible synergistic effects of immunotherapy combined with chemotherapy, MC38 xenografts with different sensitivity to PD-L1 blockade were established. In addition, we found that PD-1 blockade also had efficacy on the PD-L1 knockout tumors. RT-PCR and immunofluorescence analysis were used to detect the expression of PD-L1. It was observed that both mouse and human PD-L1 expressed among three types of MC38 tumors. These results suggest that PD-L1 on tumor cells affect the efficacy, but it on host myeloid cells might be essential for checkpoint blockade. Moreover, anti-PD-1 treatment activates tumor-reactive CD103+ CD39+ CD8+T cells (TILs) in tumor microenvironment.

Background: Tissue-resident memory T (T_RM) cells can reside in the tumor microenvironment and are considered the primary response cells to immunotherapy. Heterogeneity in functional status and spatial distribution may contribute to the controversial role of T_RM cells but we know little about it. Methods: Through multiplex immunofluorescence (mIF) (CD8, CD103, PD-1, Tim-3, GZMB, CK), the quantity and spatial location of T_RM cell subsets were recognized in the tissue from 274 patients with NSCLC after radical surgery. By integrating multiple machine learning methods, we constructed a T_RM-based spatial immune signature (T_RM-SIS) to predict the prognosis. Furthermore, we conducted a CD103-related gene set enrichment analysis (GSEA) and verified its finding by another mIF panel (CD8, CD103, CK, CD31, Hif-1α). Results: The density of T_RM cells was significantly correlated with the expression of PD-1, Tim-3 and GZMB. Four types of T_RM cell subsets was defined, including T_RM1 (PD-1⁻Tim-3⁻T_RM), T_RM2 (PD-1⁺Tim-3⁻T_RM), T_RM3 (PD-1⁻Tim-3⁺T_RM) and T_RM4 (PD-1⁺Tim-3⁺T_RM). The cytotoxicity of T_RM2 was the strongest while that of T_RM4 was the weakest. Compare with T_RM1 and T_RM2, T_RM3 and T_RM4 had better infiltration and stronger interaction with cancer cells. The T_RM-SIS was an independent prognostic factor for disease-free survival [HR = 2.43, 95%CI (1.63–3.60), P < 0.001] and showed a better performance than the TNM staging system for recurrence prediction. Furthermore, by CD103-related GSEA and mIF validation, we found a negative association between tumor angiogenesis and infiltration of T_RM cells. Conclusions: These findings reveal a significant heterogeneity in the functional status and spatial distribution of T_RM cells, and support it as a biomarker for the prognosis of NSCLC patients. Regulating T_RM cells by targeting tumor angiogenesis may be a potential strategy to improve current immunotherapy.

Background: Tumor shape is strongly associated with some tumor’s genomic subtypes and patient outcomes. Our purpose is to find the relationship between risk stratification and the shape of GISTs. Methods: A total of 101 patients with primary GISTs were confirmed by pathology and immunohistochemistry and underwent enhanced CT examination. All lesions’ pathologic sizes were 1 to 10 cm. Points A and B were the extremities of the longest diameter (LD) of the tumor and points C and D the extremities of the small axis, which was the longest diameter perpendicular to AB. The four angles of the quadrangle ABCD were measured and each angle named by its summit (A, B, C, D). For regular lesions, we took angles A and B as big angle (BiA) and small angle (SmA). For irregular lesions, we compared A/B ratio and D/C ratio and selected the larger ratio for analysis. The chi-square test, t test, ROC analysis, and hierarchical or binary logistic regression analysis were used to analyze the data. Results: The BiA/SmA ratio was an independent predictor for risk level of GISTs (p = 0.019). With threshold of BiA at 90.5°, BiA/SmA ratio at 1.35 and LD at 6.15 cm, the sensitivities for high-risk GISTs were 82.4%, 85.3%, and 83.8%, respectively; the specificities were 87.1%, 71%, and 77.4%, respectively; and the AUCs were 0.852, 0.818, and 0.844, respectively. LD could not effectively distinguish between intermediate-risk and high-risk GISTs, but BiA could (p < 0.05). Shape and Ki-67 were independent predictors of the mitotic value (p = 0.036 and p < 0.001, respectively), and the accuracy was 87.8%. Conclusions: Quantifying tumor shape has better predictive efficacy than LD in predicting the risk level and mitotic value of GISTs, especially for high-risk grading and mitotic value > 5/50HPF. Key Points: • The BiA/SmA ratio was an independent predictor affecting the risk level of GISTs. LD could not effectively distinguish between intermediate-risk and high-risk GISTs, but BiA could. • Shape and Ki-67 were independent predictors of the mitotic value. • The method for quantifying the tumor shape has better predictive efficacy than LD in predicting the risk level and mitotic value of GISTs.