Gastric cancer-derived mesenchymal stem cells promote gastric cancer cell lines migration by modulating CD276 expression.

CD276 has been studied in a variety of cancers and diseases, but its regulatory mechanisms in gastric cancer is still unclear. Mesenchymal stem cells (MSCs), one of the important members of tumor microenvironment, play an important role in the occurrence, development and metastasis of tumor, but the relationship between gastric cancer mesenchymal stem cells (GCMSCs) and CD276 in gastric cancer needs to be further explored. The differential expression of CD276 was identified via UCLAN and GEPIA databases. Then, the impacts of CD276 were calculated on clinical prognosis using the Kaplan-Meier plotter and Cox analysis. GO, KEGG and GSEA analysis were used to explore potential mechanism under CD276. Next, the expression of CD276 in gastric cell lines were detected by Western blot. Immunocoprecipitation was used to explore the association between CD276 and COL1A1. And the effect of condition medium (CM) from GCMSCs on gastric cell lines migration analyzed. GC-MSCs activated the AKT/c-Myc/mTOR pathway of gastric cell lines and upregulated CD276 expression. Moreover, the upregulation of CD276 promoted the migration of gastric cancer cells. Taken together, this study shown that GCMSCs could up-regulate the expression of CD276 of gastric cell lines to promote tumor migration. Our results provide a new basis for the treatment of gastric cancer.

Peripheral blood lymphocytes differentiation patterns in responses / outcomes to immune checkpoint blockade therapies in non-small cell lung cancer: a retrospective study.

OBJECTIVES: Programmed Cell Death-1/ Programmed Death-ligand 1 (PD-1 / PD-L1) inhibitor therapies targeting immunocytes induce persistent tumor remission in various cancers. However, the appropriate biomarkers for the therapeutic efficacy of PD-L1 and PD-1 blockade remain elusive. MATERIALS AND METHODS: For a comprehensive analysis of peri-treatment lymphocyte differentiation, in the current study, we enrolled 146 non-small cell lung cancer patients who received α-PD-1 therapies for exploring the peripheral blood lymphocyte differentiation pattern at baseline and post-treatment (dynamic changes) by flow cytometry. RESULTS: At baseline, CD4+ / CD8+ T cell ratio predicts good responses and outcomes, but activated T cell and cytotoxic T cell counts predict poor responses and outcomes. And for dynamic changes, after 6 weeks of immune checkpoint blockade (ICB) treatment, compared with baseline level, the elevation of total T and B cell counts indicate poor responses, and total T and TH cell counts indicate poor prognosis while activated T cell predicts good prognosis. And after 12 weeks, elevated total lymphocyte, cytotoxic T cell counts, and decreased total T cell counts and CD4+ / CD8+ T cell ratio predict good responses / outcomes. Our clinical predicting model shows good performance in predicting ICB treatment responses / outcomes. CONCLUSION: Patients with favorable clinical responses / outcomes have distinctive peripheral blood immunocyte differentiation characteristics, indicating the potential of utilizing the peripheral immunocyte differentiation patterns for predicting ICB responses / outcomes.

Relationship between plasma circulating cell-free DNA concentration and treatment outcomes including prognosis in patients with advanced non-small cell lung cancer.

BACKGROUND: Some research found that elevated plasma cell-free DNA (cfDNA) concentrations and poor prognosis are associated in non-small cell lung cancer (NSCLC). However, more studies need to be carried out to verify this conclusion. Therefore, this study investigated the relationship between cfDNA concentration and treatment outcomes including prognosis in patients with advanced NSCLC. METHODS: We retrospectively collected medical records and cfDNA data from 160 patients with advanced NSCLC. Progression-free survival (PFS) were calculated using the Kaplan-Meier method and were compared between groups using the log rank test. Cox regression analysis was used for estimating the independent predictors of PFS. And we used logistic regression to evaluate the relationship between baseline biomarkers and efficacy. In our study, BT1 cfDNA, BT2 cfDNA, and BT3 cfDNA were defined as cfDNA concentration before the first treatment (baseline cfDNA concentration), cfDNA concentration before the second treatment, and cfDNA concentration before the third treatment, respectively. RESULTS: Patients with low cfDNA (BT1 cfDNA < 15 (ng/mL)) were reported a significantly prolonged median progression-free survival (mPFS) compared with patients with patients with high cfDNA (BT1 cfDNA ≥ 15(ng/mL)) (mPFS: 14.6 vs. 8.3 months, P = 0.002), as well as patients with neutrophil/lymphocyte ratio (NLR)<2.98 (mPFS: 13.1 vs. 7.9 months, P = 0.023). In addition, Cox proportional hazards regression analysis identified independent indicators associated with PFS including BT1 cfDNA ≥ 15 (ng/mL), NLR ≥ 2.98 and extrapulmonary metastasis. The best cut-off value for BT3 cfDNA for predicting disease progression is 41.46 (ng/mL) (Area Under the Curve (AUC): 0.652, 95%CI: 0.516-0.788), achieving 90.7% sensitivity and 37.5% specificity for the prediction of disease progression. BT3 cfDNA (OR = 6.08, 95% CI: 1.94-19.57, P = 0.002) was an independent factor for disease progression in patients with advanced NSCLC. CONCLUSIONS: BT1 cfDNA may be a biomarker to assess the prognosis of advanced NSCLC. Patients with advanced NSCLC with lower cfDNA and NLR before treatment had a better prognosis. Increased BT3 cfDNA concentration was an independent factor of disease progression in advanced NSCLC patients. These findings may assist in identifying high-risk patients and guiding treatment strategies.

Four differentially expressed genes can predict prognosis and microenvironment immune infiltration in lung cancer: a study based on data from the GEO.

BACKGROUND: Lung cancer is among the major diseases threatening human health. Although the immune response plays an important role in tumor development, its exact mechanisms are unclear. MATERIALS AND METHODS: Here, we used CIBERSORT and ESTIMATE algorithms to determine the proportion of tumor-infiltrating immune cells (TICs) as well as the number of immune and mesenchymal components from the data of 474 lung cancer patients from the Gene Expression Omnibus database. And we used data from The Cancer Genome Atlas database (TCGA) for validation. RESULTS: We observed that immune, stromal, and assessment scores were only somewhat related to survival with no statistically significant differences. Further investigations revealed these scores to be associated with different pathology types. GO and KEGG analyses of differentially expressed genes revealed that they were strongly associated with immunity in lung cancer. In order to determine whether the signaling pathways identified by GO and KEGG signaling pathway enrichment analyses were up- or down-regulated, we performed a gene set enrichment analysis using the entire matrix of differentially expressed genes. We found that signaling pathways involved in hallmark allograft rejection, hallmark apical junction, hallmark interferon gamma response, the hallmark P53 pathway, and the hallmark TNF-α signaling via NF-ĸB were up-regulated in the high-ESTIMATE-score group. CIBERSORT analysis for the proportion of TICs revealed that different immune cells were positively correlated with the ESTIMATE score. Cox regression analysis of the differentially expressed genes revealed that CPA3, C15orf48, FCGR1B, and GNG4 were associated with patient prognosis. A prognostic model was constructed wherein patients with high-risk scores had a worse prognosis (p < 0.001 using the log-rank test). The Area Under Curve (AUC)value for the risk model in predicting the survival was 0.666. The validation set C index was 0.631 (95% CI: 0.580-0.652). The AUC for the risk formula in the validation set was 0.560 that confirmed predictivity of the signature. CONCLUSION: We found that immune-related gene expression models could predict patient prognosis. Moreover, high- and low-ESTIMATE-score groups had different types of immune cell infiltration.

Reducing language barriers, promoting information absorption, and communication using fanyi.

ABSTRACT: Interpreting genes of interest is essential for identifying molecular mechanisms, but acquiring such information typically involves tedious manual retrieval. To streamline this process, the fanyi package offers tools to retrieve gene information from sources like National Center for Biotechnology Information (NCBI), significantly enhancing accessibility. Additionally, understanding the latest research advancements and sharing achievements are crucial for junior researchers. However, language barriers often restrict knowledge absorption and career development. To address these challenges, we developed the fanyi package, which leverages artificial intelligence (AI)-driven online translation services to accurately translate among multiple languages. This dual functionality allows researchers to quickly capture and comprehend information, promotes a multilingual environment, and fosters innovation in academic community. Meanwhile, the translation functions are versatile and applicable beyond biomedicine research to other domains as well. The fanyi package is freely available at https://github.com/YuLab-SMU/fanyi .

The efficacy of neoadjuvant immunotherapy and lymphocyte subset predictors in locally advanced esophageal squamous cell carcinoma: A retrospective study.

BACKGROUND: Despite the recognized therapeutic potential of programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) inhibitors in advanced esophageal squamous cell carcinoma (ESCC), their role in neoadjuvant therapy and reliable efficacy biomarkers remain elusive. MATERIALS AND METHODS: We retrospectively analyzed locally advanced ESCC patients who underwent surgery following a 2-cycle platinum and paclitaxel-based treatment, with or without PD-1 inhibitors (January 2020-March 2023). We assessed peripheral blood indexes and tertiary lymphoid structures (TLS) density to evaluate their impact on pathological response and prognosis, leading to a clinical prediction model for treatment efficacy and survival. RESULTS: Of the 157 patients recruited, 106 received immunochemotherapy (ICT) and 51 received chemotherapy (CT) alone. The ICT group demonstrated a superior pathological response rate (PRR) (47.2% vs. 29.4%, p = 0.034) with comparable adverse events and postoperative complications. The ICT group also showed a median disease-free survival (DFS) of 39.8 months, unattained by the CT group. The 1-year DFS and overall survival (OS) rates were 73% and 91% for the ICT group, and 68% and 81% for the CT group, respectively. We found higher baseline activated T cells, lower baseline Treg cells, and a decreased posttreatment total lymphocyte and CD4+/CD8+ ratio predicted an enhanced PRR. Reduced posttreatment CD4+/CD8+ ratio and increased NK cells were associated with prolonged survival, while higher TLS density indicated poorer prognosis. Among ICT group, a lower posttreatment CD4+/CD8+ ratio indicated longer DFS and reduced posttreatment B cells indicated longer OS. A nomogram integrating these predictors was developed to forecast treatment efficacy and survival. CONCLUSION: The combination of PD-1 inhibitors and chemotherapy appears promising for locally advanced ESCC. Evaluating the differentiation status and dynamic changes of peripheral blood immune cells may provide valuable predictive insights into treatment efficacy and prognosis.

Identification of macrophage-related genes correlated with prognosis and immunotherapy efficacy in non-small cell lung cancer.

Background: Malignant tumours, particularly non-small cell lung cancer (NSCLC), pose a significant threat to human health due to their prevalence and lethality. Treatment methods for NSCLC vary greatly among individuals, making it crucial to identify predictive markers. Moreover, during tumour initiation and progression, tumour cells can release signaling molecules to induce polarization of macrophages towards a more tumour friendly M2 phenotype, which can promote tumour growth, metastasis, and drug resistance. Methods: We employed a comprehensive approach, combining bulk RNA-seq and single-cell sequencing analysis. Results: In our study, we used bulk RNA-seq and single-cell sequencing methods to analyze differential cells in NSCLC and adjacent tissues, searching for relevant marker genes that can predict prognosis and drug efficacy. We scrutinized biological phenomena such as macrophage-related gene methylation, copy number variation, and alternative splicing. Additionally, we utilized a co-culture technique of immune and tumour cells to explore the role of these genes in macrophage polarization. Our findings revealed distinct differences in macrophages between cancerous and adjacent tissues. We identified ANP32A, CCL20, ERAP2, MYD88, TMEM126B, TUBB6, and ZNF655 as macrophage-related genes that correlate with NSCLC patient prognosis and immunotherapy efficacy. Notably, ERAP2, TUBB6, CCL20, and TMEM126B can induce macrophage M0 to M2 polarization, promoting tumour proliferation. Conclusion: These findings significantly contribute to our understanding of the NSCLC tumour immune microenvironment. They pave the way for further research into the potential of these genes as targets for regulating tumour occurrence and development.

Resolving tumor evolution: a phylogenetic approach.

The evolutionary dynamics of cancer, characterized by its profound heterogeneity, demand sophisticated tools for a holistic understanding. This review delves into tumor phylogenetics, an essential approach bridging evolutionary biology with oncology, offering unparalleled insights into cancer's evolutionary trajectory. We provide an overview of the workflow, encompassing study design, data acquisition, and phylogeny reconstruction. Notably, the integration of diverse data sets emerges as a transformative step, enhancing the depth and breadth of evolutionary insights. With this integrated perspective, tumor phylogenetics stands poised to redefine our understanding of cancer evolution and influence therapeutic strategies.

SAA suppresses α-PD-1 induced anti-tumor immunity by driving TH2 polarization in lung adenocarcinoma.

Cancer stem cells (CSCs) are believed to be crucial in the initiation, progression, and recurrence of cancer. CSCs are also known to be more resistant to cancer treatments. However, the interaction between CSCs and the immune microenvironment is complex and not fully understood. In current study we used single cell RNA sequence (scRNA-Seq, public dataset) technology to identify the characteristic of CSCs. We found that the lung adenocarcinoma cancer stem population is highly inflammatory and remodels the tumor microenvironment by secreting inflammatory factors, specifically the acute phase protein serum amyloid A (SAA). Next, we developed an ex-vivo autologous patient-derived organoids (PDOs) and peripheral blood mononuclear cells (PBMCs) co-culture model to evaluate the immune biological impact of SAA. We found that SAA not only promotes chemoresistance by inducing cancer stem transformation, but also restricts anti-tumor immunity and promotes tumor fibrosis by driving type 2 immunity, and α-SAA neutralization antibody could restrict treatment resistant and tumor fibrosis. Mechanically, we found that the malignant phenotype induced by SAA is dependent on P2X7 receptor. Our data indicate that cancer stem cells secreted SAA have significant biological impact to promote treatment resistant and tumor fibrosis by driving cancer stemness transformation and type 2 immunity polarization via P2X7 receptor. Notably, α-SAA neutralization antibody shows therapeutic potential by restricting these malignant phenotypes.

Association between changes in thioredoxin reductase and other peripheral blood biomarkers with response to PD-1 inhibitor-based combination immunotherapy in non-small cell lung cancer: a retrospective study.

Background: Immunotherapy deeply changed the treatment paradigm of advanced non-small cell lung cancer (NSCLC) in the past years. However, the objective response rate (ORR) after immunotherapy is about 20-30% of NSCLC patients. Therefore, identification of predictive biomarkers is crucial for selecting patients with NSCLC who would most benefit from programmed cell death receptor protein 1 (PD-1) inhibitor-based immunotherapy. Methods: We retrospectively collected medical records and thioredoxin reductase (TrxR) data from 90 patients with a NSCLC who received PD-1 inhibitor-based combination therapy. Serum biomarkers were also measured at 6- and 12-week post-treatment and compared with their baseline values. Associations between changes in serum biomarkers, clinical characteristics and treatment efficacy were evaluated using univariate tests. The patients who were still alive were followed up remotely by phone or email to assess survival. The association between serum biomarkers and TrxR with overall survival (OS) and progression-free survival (PFS) were assessed by univariate and multivariate Cox proportional hazard regression. Nomogram prediction models were constructed using factors associated with PFS and OS, respectively. Results: The median follow-up time among the 90 patients was 19.7 (range, 13.6 to 25.8) months. Median PFS and OS were 13.6 [95% confidence interval (CI): 13.5 to 13.7] and 19.7 (95% CI: 13.6 to 25.8) months, respectively. Patients with decreased carcinoembryonic antigen (CEA), albumin (Alb), and TrxR values at 6- and 12-week post-treatment compared to baseline had statistically significantly improved disease remission rates (P<0.05). Patients with decreased white blood cell (WBC), neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR) at week 6, and decreased Alb, CEA, and lymphocyte-to-monocyte ratio (LMR) at week 12 had statistically significantly increased ORRs (P<0.05). According to the univariate and multivariate Cox regression analyses, we included adenocarcinoma, Eastern Cooperative Oncology Group performance status (ECOG PS), and CEA change at week 6 post-treatment as predictors for PFS, and adenocarcinoma, change in absolute lymphocyte count (ALC), and TrxR at week 6 as predictors for OS in the nomogram models. Each nomogram was also validated internally using a bootstrap method with 1,000 resamples. Conclusions: Change in TrxR at 6 weeks post-treatment in combination with other clinical and hematological biomarkers could be used as a predictor for treatment outcome and prognosis in NSCLC patients after PD-1 inhibitor-based combination immunotherapy.

Inhibition of CCCTC Binding Factor-Programmed Cell Death Ligand 1 Axis Suppresses Emergence of Chemoresistance Induced by Gastric Cancer-Derived Mesenchymal Stem Cells.

Background: Gastric cancer (GC) is the third leading cause of cancer-associated deaths worldwide. Stromal cells, especially mesenchymal stem cells (MSCs), play significant roles in the development of therapy resistance depending on their paracrine function. The PD-1/PD-L1 crosstalk between cancer and immune cells has been well studied. Emerging evidence suggests that PD-L1 also contributes to tumor resistance to therapy. Methods: Cell survival and apoptosis were assessed using CCK-8, colony formation, and flow cytometry assays. Protein alterations were analyzed via Western blot. Gene knockdown and overexpression were achieved with siRNA/shRNA and lentiviral infection, respectively. Drug effects on tumors in vivo were assessed with xenografts in nude mice. In addition, GC patient samples after chemotherapy treatment were collected to observe the relationship between chemotherapy effect and CTCF or PD-L1. Results: In response to 5-fluorouracil or paclitaxel treatment, GCMSC-CM enhanced the cell viability and decreased the apoptosis rate. Furthermore, blocking PD-L1 or CTCF in GC cells prevented GCMSC-induced drug resistance accompanied by a decline in cell stemness. Consistent with these in vitro observations, mice treated with GCMSC-CM showed a lower sensitivity to 5-fluorouracil. In addition, high expression of CTCF and PD-L1 was associated with poor chemotherapy progression in the clinic. Conclusion: Study results demonstrate a mechanism where GCMSC-CM promotes GC chemoresistance by upregulating CTCF-PD-L1 and provide strong evidence in support of targeting CTCF-PD-L1 signaling as a strategy to prevent resistance in the clinic.

Efficacy and safety of second-line therapy with apatinib combined with chemotherapy as second-line therapy in advanced gastric cancer: a single-arm, open-label, prospective, multicenter study.

Background: For advanced gastric cancer (GC) patients who fail first-line treatment, chemotherapy alone is of limited benefit. Ramucirumab combined with paclitaxel and apatinib combined with docetaxel provided clinical benefit in previous studies, but the feasibility of apatinib combined with other chemotherapy agents remains unknown. The aim of the present study was to evaluate the efficacy and safety of apatinib combined with chemotherapy as a second-line treatment for advanced GC. Methods: Patients aged 18-75 years with histologically or cytologically confirmed advanced or metastatic GC or gastroesophageal junction adenocarcinoma that had progressed with first-line treatment were recruited and received apatinib 250 or 500 mg oral apatinib and chemotherapy regimens, including docetaxel, paclitaxel, tegafur, oxaliplatin, and capecitabine. Each treatment cycle was 28 days (4 weeks). During post-discontinuation follow-up, all patients were followed for survival [every 8 weeks (+0 to 7 days)] until disease progression, death, or study completion. Overall survival (OS) was the primary endpoint. Secondary endpoints were overall response rate (ORR), disease control rate (DCR), and progression-free survival (PFS). Adverse events (AEs) were also noted. Tumor response and progression were assessed according to RECIST 1.1. AEs were graded following the National Cancer Institute common terminology criteria for AEs (NCI-CTCAE 4.0). Results: Between August 31, 2016 and February 17, 2020, a total of 32 patients were enrolled in the present study, and 29 were evaluable. At the time of data cut-off, median follow-up was 7.00 months (IQR, 4.60-12.23 months). The ORR and DCR were 18.52% and 92.59%, respectively. The median PFS was 3.06 months, and the median OS was 6.93 months. In the population receipt of apatinib plus docetaxel, the median OS was 6.51 months. AEs were observed in 22 patients. Leukopenia was the most common AE (24.1%), followed by hypertension (24.1%) and neutropenia (17.2%). Patients did not develop any AEs that were grade 4 or higher. Conclusions: The combination of apatinib and chemotherapy demonstrated clinical activity and acceptable toxicity as a second-line treatment for advanced GC, and may provide new second-line treatment options for advanced GC patients.

[Peripheral Blood Inflammation Indicators as Predictive Indicators in 
Immunotherapy of Advanced Non-small Cell Lung Cancer].

BACKGROUND: Lung cancer is the leading cause of cancer-related death, of which non-small cell lung cancer (NSCLC) is the most common type. Immune checkpoint inhibitors (ICIs) have now become one of the main treatments for advanced NSCLC. This paper retrospectively investigated the effect of peripheral blood inflammatory indexes on the efficacy of immunotherapy and survival of patients with advanced non-small cell lung cancer, in order to find strategies to guide immunotherapy in NSCLC. METHODS: Patients with advanced non-small cell lung cancer who were hospitalized in The Affiliated Cancer Hospital of Nanjing Medical University from October 2018 to August 2019 were selected to receive anti-PD-1 (pembrolizumab, sintilimab or toripalimab) monotherapy or combination regimens. And were followed up until 10 December 2020, and the efficacy was evaluated according to RECIST1.1 criteria. Progression-free survival (PFS) and overall survival (OS) were followed up for survival analysis. A clinical prediction model was constructed to analyze the predictive value of neutrophil-to-lymphocyte ratio (NLR) based on NLR data at three different time points: before treatment, 6 weeks after treatment and 12 weeks after treatment (0w, 6w and 12w), and the accuracy of the model was verified. RESULTS: 173 patients were finally included, all of whom received the above treatment regimen, were followed up for a median of 19.7 months. The objective response rate (ORR) was 27.7% (48/173), the disease control rate (DCR) was 89.6% (155/173), the median PFS was 8.3 months (7.491-9.109) and the median OS was 15.5 months (14.087-16.913). The chi-square test and logistic multi-factor analysis showed that NLR6w was associated with ORR and NLR12w was associated with ORR and DCR. Further Cox regression analysis showed that NLR6w and NLR12w affected PFS and NLR0w, NLR6w and NLR12w were associated with OS. CONCLUSIONS: In patients with advanced non-small cell lung cancer, NLR values at different time points are valid predictors of response to immunotherapy, and NLR <3 is often associated with a good prognosis.

Efficacy and safety of first-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) combined with chemotherapy or antiangiogenic therapy as first-line treatment in patients with EGFR-mutant non-small cell lung cancer: A systematic review and meta-analysis.

OBJECTIVE: We conducted a meta-analysis to synthesize the results of published randomized controlled trials conducted to evaluate the efficacy and safety of epidermal growth factor receptor - tyrosine kinase inhibitors (EGFR-TKIs) combined with chemotherapy or antiangiogenic therapy. METHODS: PubMed, EMBASE, Cochrane Library and ClinicalTrials.gov databases were searched and literatures from international conferences were read to identify eligible studies. The primary endpoints were objective response rate (ORR) and progression free survival (PFS). The secondary endpoints were disease control rate (DCR), overall survival (OS) and treatment-emergent adverse events (TEAEs). RESULTS: 10 studies, all on first-generation EGFR-TKI combination therapy, involving 2367 patients were included. Combination therapy resulted in significant improvements in ORR (RR: 1.11, 95% CI: 1.06-1.17, P < 0.001), DCR (RR: 1.03, 95% CI: 1.01-1.05, P = 0.007), PFS (HR: 0.56, 95% CI: 0.51-0.62, P < 0.001), OS (HR: 0.74, 95% CI: 0.64-0.84, P = 0.002) over monotherapy. This improvement was more apparent in the EGFR-TKIs combination chemotherapy group, and indirect comparisons revealed that EGFR-TKIs combined with chemotherapy appeared to be superior to combined with antiangiogenic therapy in ORR (RR: 1.19, 95% CI: 1.07-1.32), DCR (RR: 1.04, 95% CI: 1.02-1.08), and OS (HR: 0.79, 95% CI: 0.66-0.96). Of additional concern is the increased incidence of TEAEs in combination therapy. CONCLUSION: As a first-line treatment for patients with EGFR-mutated advanced non-small cell lung cancer (NSCLC), first-generation EGFR-TKIs combined with chemotherapy or antiangiogenic therapy was associated with significant improvement in ORR, DCR, PFS and OS compared with monotherapy.

Combination of Tertiary Lymphoid Structure and Neutrophil-to-Lymphocyte Ratio Predicts Survival in Patients With Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is the most common pathological type of primary liver cancer. The lack of prognosis indicators is one of the challenges in HCC. In this study, we investigated the combination of tertiary lymphoid structure (TLS) and several systemic inflammation parameters as a prognosis indicator for HCC. Materials and Methods: We retrospectively recruited 126 postoperative patients with primary HCC. The paraffin section was collected for TLS density assessment. In addition, we collected the systemic inflammation parameters from peripheral blood samples. We evaluated the prognostic values of those parameters on overall survival (OS) using Kaplan-Meier curves, univariate and multivariate Cox regression. Last, we plotted a nomogram to predict the survival of HCC patients. Results: We first found TLS density was positively correlated with HCC patients' survival (HR=0.16, 95% CI: 0.06 - 0.39, p < 0.0001), but the power of TLS density for survival prediction was found to be limited (AUC=0.776, 95% CI:0.772 - 0.806). Thus, we further introduced several systemic inflammation parameters for survival analysis, we found neutrophil-to-lymphocyte ratio (NLR) was positively associated with OS in univariate Cox regression analysis. However, the combination of TLS density and NLR better predicts patient's survival (AUC=0.800, 95% CI: 0.698-0.902, p < 0.001) compared with using any single indicator alone. Last, we incorporated TLS density, NLR, and other parameters into the nomogram to provide a reproducible approach for survival prediction in HCC clinical practice. Conclusion: The combination of TLS density and NLR was shown to be a good predictor of HCC patient survival. It also provides a novel direction for the evaluation of immunotherapies in HCC.

Corrigendum: Association of Dynamic Changes in Peripheral Blood Indexes With Response to PD-1 Inhibitor-Based Combination Therapy and Survival Among Patients With Advanced Non-Small Cell Lung Cancer.

[This corrects the article DOI: 10.3389/fimmu.2021.672271.].

Gastric Cancer Mesenchymal Stem Cells Inhibit NK Cell Function through mTOR Signalling to Promote Tumour Growth.

The dysfunction of natural killer (NK) cells has been increasingly reported in malignancies, especially in solid tumours. Mesenchymal stem cells (MSCs) exhibit pleiotropic functions that include mediating immune cell exhaustion which is implicated in cancer progression. However, the association of MSCs derived from gastric cancer (gastric cancer mesenchymal stem cells: GCMSCs) with the dysfunction of NK cells remains poorly understood. In this study, we demonstrated that GCMSCs effectively contributed to the exhaustion of NK cells through the release of soluble factors. Furthermore, passivation of the antitumour effect in NK cells was closely associated with their dysfunctional state. The GCMSC-conditioned medium prevented the frequency and effector function of infiltrating NK cells in tumour-bearing mouse models, thus promoting tumour growth. Mechanistically, mammalian target of rapamycin (mTOR) signalling, a critical regulator of cellular metabolism that mediates the function of immune cells, was inhibited in NK cells treated with GCMSCs. However, the checkpoint receptor PD-1 was still present at minimal levels with or without GCMSCs. The study results revealed that GCMSCs contributed to dysfunctional NK cells involved at least partially in the inhibition of mTOR signalling, suggesting potential directions for NK cell-based cancer immunotherapy.

Association of Dynamic Changes in Peripheral Blood Indexes With Response to PD-1 Inhibitor-Based Combination Therapy and Survival Among Patients With Advanced Non-Small Cell Lung Cancer.

Background: PD-1 inhibitors have been routinely used in the treatment of advanced non-small cell lung cancer (NSCLC), and have demonstrated to significantly improve survivorship when combining with other conventional therapies, such as chemotherapy and anti-angiogenesis therapy. PD-L1 is the most commonly used biomarker to select benefiting groups, while not all patients with high PD-L1 expression benefit from immunotherapy. Therefore, identifying other prognostic and predictive biomarkers, including peripheral blood indexes, is essential. Methods: We retrospectively collected medical records and hematological data of 151 patients with advanced NSCLC treated with PD-1 inhibitor-based combination therapy in our hospital. The peripheral blood indexes of interest were NLR, PLR, PAR, Hb, LDH, CEA, and NSE. The association between peripheral blood indexes and treatment responses or survival outcomes was examined by multivariable logistic regression and Cox regression, respectively. Results: The decreased CEA at week 6 (OR = 4.209, 95%CI: 1.287-13.758) or 12 (OR = 7.267, 95%CI: 1.508-35.006) post-treatment was related to a higher disease control rate. The decrease or NLR at week 6 (OR = 3.081, 95%CI: 1.464-6.483) or 12 (OR = 3.304, 95%CI: 1.560-7.001) post-treatment, or CEA at week 12 post-treatment (OR = 2.469, 95%CI: 1.134-5.375), was associated with a higher objective response rate. Patients whose NLR (HR = 0.610, 95%CI: 0.411-0.907) or CEA (HR = 0.477, 95%CI: 0.320-0.710) decreased at week 6 post-treatment tended to have longer progression-free survival, and similar results were found in those with decreased NLR (HR = 0.587, 95%CI: 0.388-0.886) or CEA (HR = 0.406, 95%CI: 0.270-0.609) at week 12 post-treatment. Patients whose CEA (HR = 0.543, 95%CI: 0.339-0.871) or NSE (HR = 0.619, 95%CI: 0.386-0.994) decreased after 6 weeks post-treatment appeared to have longer overall survival, and the same was found for those whoseCEA (HR = 0.620, 95%CI: 0.390-0.986) or NSE (HR = 0.578, 95%CI: 0.353-0.947) was decreased at 12 weeks after treatment. Conclusion: Post-treatment NLR, CEA and NSE changes are suggestive indicators for the prognosis of NSCLC patients after immunotherapy.