Background: Immunotherapy is effective in treating unresectable esophageal squamous cell carcinoma (ESCC), but little is known about its role in the preoperative setting. The aim of this study was to evaluate the safety, feasibility and efficacy of neoadjuvant treatment with camrelizumab plus chemotherapy in locally advanced ESCC.Methods: Patients diagnosed with locally advanced ESCC were retrospectively included if they had received neoadjuvant camrelizumab plus nab-paclitaxel and S1 capsule followed by radical esophagectomy between November, 2019 and June, 2020 at Sun Yat-sen University Cancer Center. Primary endpoints were safety and feasibility. In addition, pathological response and the relationship between tumor immune microenvironment (TIME)/tumor mutational burden (TMB) and treatment response were also investigated.Results: Twelve patients were included and they all received three courses of preoperative treatment with camrelizumab plus nab-paclitaxel/S1. No grade 3 or higher toxicities occurred. No surgical delay or perioperative death was reported. Nine patients (75%) responded to the treatment, four with a complete pathological response (pCR) and five with a major pathological response (MPR). Neither programmed death-ligand 1 (PD-L1) expression nor TMB was correlated with treatment response. TIME analysis revealed that a higher abundance of CD56dim natural killer cells was associated with better pathological response in the primary tumor, while lower density of M2-tumor-associated macrophages was associated with better pathological response in the lymph nodes (LNs).Conclusions: Neoadjuvant camrelizumab plus nab-paclitaxel and S1 is safe, feasible and effective in locally advanced ESCC and is worth further investigation.

Fabrication of Z-scheme heterojunctions and crystal facet engineering are effective strategies for enhancing visible-light photocatalytic redox ability.

BackgroundPoly (ADP-ribose) polymerases-1 (PARP1) alterations are associated with PARP1 inhibitor resistance, regulating the function of Treg cells and PDL1 expression in tumor cells, and high PARP1 expression is significantly associated with aggressive behavior and chemotherapeutic resistance in several tumors. However, a comprehensive analysis of the predictive values of PARP1 alteration for immune checkpoint inhibitor (ICI) effectiveness in tumors remains unclear, and the associations between its expression and immunotherapy signatures also needs to be explored further.MethodsWe performed some analyses with the cBioPortal online database (https://www.cbioportal.org), TIMER2.0 (Tumor Immune Estimation Resource 2.0, http://timer.comp-genomics.org/) and TCGA database (https://xenabrowser.net or https://portal.gdc.cancer.gov/). Survival analysis was conducted using Kaplan–Meier method, and the associations between PARP1 transcription levels and immune checkpoint gene expression, the number of neoantigens, tumor mutation burden (TMB) levels, and microsatellite instability (MSI) event are analyzed by spearman correlation analysis and visualization of those mentioned above is performed using R, version 3.6.3 (http://www.r-project.org/).ResultsWe found that PARP1 was altered in 1338 (2.9%) out of 45604 patients with diverse tumors, which was associated with markedly higher TMB levels in a variety of tumors (P < 0.01). Impressively, patients with PARP1 alterations in advanced tumors showed better overall survival (OS) in the ICI-treated cohort (P = 0.016). PARP1 altered group was substantially correlated with higher immune infiltrates across most tumors, including CD8+ T cells in colorectal adenocarcinoma (P = 0.0061), endometrial carcinoma (P = 0.0033), stomach cancer (P = 0.033), and cervical cancer (P = 0.026), respectively. The PARP1 altered group showed high expression in transcription (P < 0.001), and higher expression of LAG3, PDCD1, CTLA-4, and TIGIT (P < 0.05). Higher PARP1 expression was present in 27 tumor compared the corresponding normal tissues using the GTEx and TCGA databases and it had a worse OS in several tumors (P < 0.05). Further, high PARP1 expression was significantly associated with six immune cells (B cells, CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells) in most tumors, including colon adenocarcinoma (COAD), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), and liver hepatocellular carcinoma (LIHC) (P < 0.05). In particular, CD8+T cell infiltration, was also positively correlated with high PARP1 expression in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), kidney renal papillary cell carcinoma (KIRP), brain lower grade glioma (LGG), LIHC, pancreatic adenocarcinoma (PAAD), pheochromocytoma and paraganglioma (PCPG), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), testicular germ cell tumors (TGCT), thymoma (THYM), uterine corpus endometrial carcinoma (UCEC), uveal melanoma (UVM) (P < 0.05, no data shown), and PARP1 expression was significantly positively correlated with the transcription levels of some of the 47 immune checkpoint genes, such as CD274, CTLA4, and PDCD1 in several tumors, including PAAD, LIHC, KIRC, HNSC, and BLCA (P < 0.05). A significant positive association between PARP1 expression and the number of immune neoantigen was found within COAD, KIRC, lung adenocarcinoma (LUAD), PAAD and THYM (P < 0.05), and there were also significantly positive correlations between PARP1 expression and TMB in many tumors like adrenocortical carcinoma (ACC), COAD, kidney chromophobe (KICH), LGG, LUAD, READ, skin cutaneous melanoma (SKCM) and stomach adenocarcinoma (STAD) (P < 0.05). In addition, high PARP1 expression was positively associated with microsatellite instability event in COAD, KIRP, BRCA, glioblastoma multiforme (GBM), lung squamous cell carcinoma (LUSC), LGG, READ, UCEC, SKCM and LUAD (P < 0.05).ConclusionsOur results highlight the significance of PARP1 alterations as pan-cancer predictive biomarkers for ICI treatment, and its expression levels seem to be correlated with the status of immunotherapy-associated signatures, thus may be a promising biomarker for predicting ICI response in several tumors.

Background The neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) have been used to predict therapeutic response in different tumors. However, no assessments of their usefulness have been performed in esophageal squamous cell carcinoma (ESCC) patients receiving anti‑PD‑1 combined with neoadjuvant chemotherapy. Methods The respective data of 64 ESCC patients receiving anti‑PD‑1 combined with neoadjuvant chemotherapy were analyzed. Whether NLR, LMR, PLR, and SII at baseline and post-treatment might predict pathological response to anti‑PD‑1 plus neoadjuvant chemotherapy, and cutoff values of these parameters were all determined by ROC curve analysis. Results NLR (cutoff = 3.173, AUC = 0.644, 95% CI 0.500–0.788, P = 0.124, sensitivity = 1.000, specificity = 0.373), LMR (cutoff = 1.622, AUC = 0.631, 95% CI 0.477–0.784, P = 0.161, sensitivity = 0.917, specificity = 0.137), PLR (cutoff = 71.108, AUC = 0.712, 95% CI 0.575–0.849, P = 0.023, sensitivity = 1.000, specificity = 0.059), and SII at baseline (cutoff = 559.266, AUC = 0.681, 95% CI 0.533–0.830, P = 0.052, sensitivity = 0.373, specificity = 1.000) seemed to be a useful predictor for distinguishing responders from non-responders. Combining NLR with SII at baseline (AUC = 0.729, 95% CI 0.600–0.858, P = 0.014, sensitivity = 0.917, specificity = 0.510), LMR and SII at baseline (AUC = 0.735, 95% CI 0.609–0.861, P = 0.012, sensitivity = 1.000 specificity = 0.471), PLR and SII at baseline (AUC = 0.716, 95% CI 0.584–0.847, P = 0.021, sensitivity = 1.000 specificity = 0.431), and LMR and PLR at post-treatment in the third period (AUC = 0.761, 95% CI 0.605–0.917, P = 0.010, sensitivity = 0.800, specificity = 0.696) might slightly increase the prediction ability to determine patients who have response or no response. Finally, combining LMR at baseline, SII at post-treatment in the second period with PLR at post-treatment in the third period could be considered a better predictor for discriminating responders and non-responders than single or dual biomarkers (AUC = 0.879, 95% CI 0.788–0.969, P = 0.0001, sensitivity = 0.909, specificity = 0.800). Conclusions The models we constructed allowed for the accurate and efficient stratification of ESCC patients receiving anti-PD-1 plus chemotherapy and are easily applicable for clinical practice at no additional cost.

The development of programmed cell death-1 inhibitor (PD-1) has shed light on the treatment of tumors with deficiencies in DNA mismatch repair system or microsatellite instability (dMMR/MSI). However, predicting the subset in this group that will benefit from PD-1 blockade remains a challenge. In this study, we aimed to investigate the relationship between the degree of microsatellite instability and the responses to anti-PD-1 immunotherapy. 33 patients with colorectal adenocarcinoma who had a known MSI status and received anti-PD-1 immunotherapy were included. PCR results for MSI of the whole cohort were collected and treatment response was evaluated. Our data indicated that objective response rate (ORR) in instability-high group (instability loci ≥ 3) was significantly higher than ORR in instability-intermediate group (13/16 versus 6/17, P = 0.008). Besides, patients in instability-high group had significant longer progression-free survival (log-rank test, P = 0.004), and a significant increase in T lymphocyte infiltration and cytolytic activity in tumors. Future study might implement the intensity of microsatellite instability for more delicate selection for anti-PD-1 therapy in patient with dMMR/MSI-H tumors.