Efficacy Of Immunotherapy In Patients Research Articles

A novel immune-related gene signature for predicting immunotherapy outcomes and survival in clear cell renal cell carcinoma

Clear cell renal carcinoma (ccRCC) is one of the most common cancers worldwide. In this study, a new model of immune-related genes was developed to predict the overall survival and immunotherapy efficacy in patients with ccRCC. Immune-related genes were obtained from the ImmPort database. Clinical data and transcriptomics of ccRCC samples were downloaded from GSE29609 and The Cancer Genome Atlas. An immune-related gene-based prognostic model (IRGPM) was developed using the least absolute shrinkage and selection operator regression algorithm and multivariate Cox regression. The reliability of the developed models was evaluated by Kaplan–Meier survival curves and time-dependent receiver operating characteristic curves. Furthermore, we constructed a nomogram based on the IRGPM and multiple clinicopathological factors, along with a calibration curve to examine the predictive power of the nomogram. Overall, this study investigated the association of IRGPM with immunotherapeutic efficacy, immune checkpoints, and immune cell infiltration. Eleven IRGs based on 528 ccRCC samples significantly associated with survival were used to construct the IRGPM. Remarkably, the IRGPM, which consists of 11 hub genes (SAA1, IL4, PLAUR, PLXNB3, ANGPTL3, AMH, KLRC2, NR3C2, KL, CSF2, and SEMA3G), was found to predict the survival of ccRCC patients accurately. The calibration curve revealed that the nomogram developed with the IRGPM showed high predictive performance for the survival probability of ccRCC patients. Moreover, the IRGPM subgroups showed different levels of immune checkpoints and immune cell infiltration in patients with ccRCC. IRGPM might be a promising biomarker of immunotherapeutic responses in patients with ccRCC. Overall, the established IRGPM was valuable for predicting survival, reflecting the immunotherapy response and immune microenvironment in patients with ccRCC.

The Characteristics of Transcription Factors Regulating T Cell Exhaustion Were Analyzed to Predict the Prognosis and Therapeutic Effect in Patients with HCC.

Hepatocellular carcinoma (HCC) ranks as the third leading cause of cancer-related deaths, posing a significant threat to people in diverse regions. T-cell exhaustion (Tex) can hinder the efficacy of immunotherapy in patients with HCC, and the transcription factors that regulate Tex in HCC have not yet been fully elucidated. We used the single sample gene set enrichment analysis (ssGSEA) method to define the transcription factor pathway that regulates Tex and employed LASSO regression analysis to establish Tex related genes (TEXRS). To predict differences in immunotherapy efficacy between the two groups, we used the immunophenotype score and submap algorithm. RT-qPCR was used to detect the expression levels of the model genes in 21 pairs of HCC tissues. Finally, we assessed the cell communication strength and identified ligand receptors using the "CellChat" R package. Nine Tex transcription factors were identified as regulators of the HCC immune microenvironment, with Tex scores affecting patient survival. Patients with a high Tex Risk Score (TEXRS) had significantly worse overall survival compared to patients with low TEXRS. After adjusting for confounding factors, TEXRS remained an independent prognostic factor. Importantly, TEXRS performed well in multiple independent external validation cohorts. Various algorithms have shown that patients in the low-TEXRS group might benefit more from immunotherapy. Finally, RT-qPCR analysis of 21 HCC samples showed that C7, CD5L, and SDS were significantly downregulated in HCC tissues, consistent with the bioinformatics analysis results. TEXRS proved to be a valuable predictor of immunotherapy and transcatheter arterial chemoembolization efficacy in patients with HCC. This holds promise for enhancing the prognosis and treatment outcomes of patients with HCC.

The influence of plasma sPD-L1 concentration on the effectiveness of immunotherapy in advanced NSCLC patients

IntroductionPD-L1 (Programmed Cell Death Ligand 1) is currently the only recognised marker of response to immunotherapy with anti-PD-1 or anti-PD-L1 antibodies in patients with advanced non-small cell lung cancer (NSCLC). However, this marker is not perfect. Soluble PD-L1 (sPD-L1) may be a novel predictor of immunotherapy efficacy in NSCLC patients.Material and methodsWe enrolled 120 patients (median age 68 ± 6.81 years, 70 males and 50 females) with locally advanced (stage IIIB; 10 patients) or advanced (stage IV; 110 patients) NSCLC. PD-L1 expression in tumour cells was assessed by immunohistochemistry (IHC) in 117 (97.5%) patients. The soluble PD-L1 concentration in plasma samples was measured using enzyme-linked immunosorbent assay (ELISA). The response to immunotherapy, progression-free survival (PFS), and overall survival (OS), calculated from the start of immunotherapy, were assessed in 119 patients.ResultsPatients with disease control had significantly lower (p = 0.0006) concentrations of sPD-L1 in blood plasma than patients with progression during the first months of immunotherapy or chemoimmunotherapy Patients with ≥ 6 month progression-free survival had a significantly higher (p = 0.013) percentage of tumor cells with PD-L1 expression than patients with shorter PFS. Patients with ≥ 6 months OS had significantly lower (p = 0.0142) plasma sPD-L1 concentrations than those with shorter overall survival. The median PFS was significantly higher in patients with low sPD-L1 concentrations than in those with high concentrations of this protein (5.8 vs. 2.5 months, HR = 0.6021, p = 0.0156). Similarly, patients with low sPD-L1 levels had a significantly higher median overall survival than those with sPD-L1 levels above the median (16.5 vs. 7 months, HR = 0.5354, p = 0.0071). There was no significant correlation between the percentage of tumour cells expressing PD-L1 and the concentration of sPD-L1 in the blood plasma.ConclusionHigh sPD-L1 concentration is a negative predictor of immunotherapy efficacy in patients with NSCLC. It is worthwhile to determine sPD-L1 concentration to predict the risk of resistance to anti-PD-1 or anti-PD-L1 antibodies with greater certainty.

Fibrinogen Levels in Patients with Metastatic Renal Cell Carcinoma Treated with Nivolumab: Results of a Multicenter Prospective Trial

Background: Introduction of immune checkpoint inhibitors in the standard of care for metastatic renal cell carcinoma (mRCC) requires robust but yet simple biomarkers to predict efficacy of immunotherapy. Objective: The aim of this study was to evaluate the association between fibrinogen levels and efficacy of second-line therapy with nivolumab in mRCC. Methods: This is a prospective multicenter biomarker study. Fibrinogen levels were measured one week prior to second-line nivolumab therapy and six times monthly. A high fibrinogen level was defined as ≥5 g/L. Patients were divided into two cohorts: high (H) and normal (N) fibrinogen levels. The primary endpoint was overall survival (OS). Results: The median OS was 31.5 months (95% confidence interval [CI], 27.9 to 35.1) in cohort N vs. 20.9 months (95% CI, 18.1 to 23.7) in cohort H (hazard ratio [HR], 0.39; 98.5% CI, 0.21 to 0.7; P = 0.002). The median progression-free survival was 9.4 months (95% CI, 5.5 to 14.1) in cohort N and 4.0 months (95% CI, 2.9 to 5.1) in cohort H (HR, 0.65; 95% CI, 0.51 to 0.72; P < 0.001). The objective response rate was higher in N cohort (33% vs. 17% ; P = 0.012). No statistically significant changes of fibrinogen concentration during nivolumab therapy were found. Conclusion: The study demonstrated an association of hyperfibrinogenemia with worse clinical outcomes of second-line nivolumab monotherapy in patients with mRCC. Further validation of fibrinogen as a predictive biomarker for immunotherapy efficacy in patients with mRCC is warranted.

Classification of the tumor immune microenvironment and associations with outcomes in patients with metastatic melanoma treated with immunotherapies

BackgroundTumor microenvironment (TME) characteristics are potential biomarkers of response to immune checkpoint inhibitors in metastatic melanoma. This study developed a method to perform unsupervised classification of TME of metastatic melanoma.MethodsWe...

Plasma Exosomal miRNAs as Response Biomarkers of Immunotherapy in Extensive-Stage Small-Cell Lung Cancer

Immunotherapy combined with chemotherapy has become the first-line standard treatment for patients with extensive-stage small-cell lung cancer (ES-SCLC). The reliable biomarkers stratifying true responders of immunotherapy effectively are unknown, and it is urgent to identify novel biomarkers in clinical. Exosomal miRNAs are considered to play a role in intercellular communication among immune cells and interaction between immune cells and tumor cells. The purpose of this study was to explore the possibility of using plasma-derived exosomal miRNAs as potential biomarkers for identifying responses to immunotherapy in ES-SCLC. From March 2020 to September 2021, 24 patients with ES-SCLC who received PD-L1 inhibitors were enrolled. Tumor assessments were conducted after every two treatment cycles according to RECIST 1.1. Plasma samples of these patients were collected before administering PD-L1 inhibitors as the baseline, and after every four cycles until the occurrence of disease progression. Plasma exosomes were isolated by ultracentrifugation, then total RNA was extracted. The miRNA profile was analyzed with small RNA next-generation sequencing followed by differential expression analysis. Of the 24 patients, 15 underwent immunotherapy maintenance after completing four cycles of PD-L1 inhibitor plus chemotherapy. In order to identify biomarkers for a better response to immunotherapy, all five responders (patients achieving PR) and four non-responders (patients achieving PD) at tumor assessment within eight cycles of the maintenance phase were included for differential expression analysis. Surprisingly, hsa-miR-320c, hsa-miR-320d, and hsa-miR-320e showed a trend of increased expression in the non-responders compared with the responders at baseline and were significantly downregulated in the post-treatment plasma exosomes compared with pre-treatment samples of the responders. Exosomal miRNA profiles are discordant between responders and non-responders of anti-PD-L1 treatment. Hsa-miR-320c, hsa-miR-320d, and hsa-miR-320e were identified as potential biomarkers for predicting the efficacy of immunotherapy in patients with ES-SCLC.

YAP1 expression is associated with survival and immunosuppression in small cell lung cancer

Immunotherapy is considered a major breakthrough in the treatment of small cell lung cancer (SCLC), although its anti-tumor efficacy is limited. With a high degree of malignancy and high heterogeneity, SCLC is difficult to treat in the clinic. A new combination strategy is urgently needed to further improve the efficacy of immunotherapy in patients with SCLC. By immunofluorescence, 100 SCLC patients in a local cohort were classified into the SCLC-A (high ASCL1 expression; n = 36), SCLC-N (high NEUROD1 expression; n = 32), SCLC-P (high POU2F3 expression; n = 14), and SCLC-Y (high YAP1 expression; n = 18) subtypes. Each SCLC molecular subtype represented different prognoses, tumor microenvironment traits, and immunotherapy sensitivities. Analysis of both the local and public cohorts suggested that the SCLC-Y subtype exhibited the worst clinical outcome (p < 0.05) when compared with other subtypes. SCLC with high YAP1 expression was characterized by high PD-L1 expression, high stromal score, T-cell functional impairment, and a close relationship with immune-related pathways. YAP1 upregulated PD-L1 expression and suppressed T cell activation, thus leading to immune evasion. In in vitro experiments, blockade of YAP1 promoted cancer cell apoptosis, immune cell proliferation, T-cell activation, and cytotoxic T-cell infiltration, thus further potentiating the efficacy of immunotherapy in patients with the SCLC-Y subtype.

COVID-19 vaccination is associated with enhanced efficacy of anti-PD-(L)1 immunotherapy in advanced NSCLC patients: a real-world study

BackgroundCoronavirus disease 2019 (COVID-19) vaccine has played a major role in ending the pandemic. However, little is known about the influence of COVID-19 vaccine on the efficacy of immunotherapy in patients with non-small cell lung cancer (NSCLC).ObjectivesThe goal of this study is to explore whether COVID-19 vaccine impacts the efficacy of immune checkpoint inhibitors (ICIs) in NSCLC patients.MethodsWe retrospectively analyzed the survival data of ICI-treated 104 patients with stage III–IV NSCLC, who either received COVID-19 vaccination (n = 25) or no vaccination (n = 79). The potential risk factors, in particular roles of COVID-19 vaccination in the efficacy of ICIs in these patients, were evaluated.ResultsOur results showed significantly improved ORR (28.0% vs. 11.39%, p = 0.05) and DCR (88.0% vs. 54.43%, p = 0.005) in the COVID-19 vaccinated group compared with the non-vaccinated group. Regarding the long-term survival benefits, COVID-19 vaccine showed profound influence both on the PFS (HR = 0.16, p = 0.021) and OS (HR = 0.168, p = 0.019) in patients with NSCLC under ICIs treatment. The PFS (p < 0.001) or OS (p < 0.001) was significantly improved in the COVID-19 vaccinated group, compared with the non-vaccinated group. Moreover, CD4 T cell (p = 0.047) level was higher in the COVID-19 vaccinated group than in the non-vaccinated group.ConclusionsCOVID-19 vaccination enhances anti-PD-1 immunotherapy efficacy in patients with stage III–IV NSCLC, suggesting that COVID-19 vaccination may provide additional benefit to NSCLC patients.

Music therapy, quality of life and efficacy of immunotherapy for NSCLC

ObjectiveOur study examines how non-small cell lung cancer (NSCLC) survivors undergoing immunotherapy can experience reduced anxiety and psychological distress, improved quality of life (QOL) and increased immunotherapy efficacy.Methods133 men and...

Analysis of the prognostic value of uric acid on the efficacy of immunotherapy in patients with primary liver cancer

PurposeUric acid (UA) plays a dual role as an antioxidant and a prooxidant in patients with malignant tumors; however, the relationship between serum UA and malignancy is currently unclear. This study aims to investigate the prognostic value of serum uric acid level before immunotherapy on the efficacy of primary liver cancer (PLC) immunotherapy, which might provide a basis for optimizing the comprehensive treatment scheme.MethodsPatients with PLC who were admitted to the First Affiliated Hospital of Gannan Medical College from January 2019 to June 2022 and underwent immunotherapy were collected retrospectively. The difference between serum UA levels in patients with PLC, the correlation between serum UA levels, and the clinical characteristics of patients with PLC were analyzed using the chi-square test, and the survival was estimated using the Kaplan–Meier analysis. To further assess the prognostic significance of UA concentrations, univariate and multivariate Cox regression analyses were performed.ResultsNinety-nine patients were included in this study cohort. The median follow-up was 7 months (range: 1–29 months), and 76 (76.8%) of the 99 patients with PLC died as of December 31, 2022. Serum UA concentrations ranged from 105 to 670 μmol/l, with a median of 269 μmol/l. The results showed that the serum UA level of patients with PLC was higher than that of healthy subjects (P < 0.001). After subgroup analyses, only male patients with liver cancer had higher serum UA levels than healthy men (P = 0.001). The results of the Kaplan–Meier analysis showed that higher UA levels were associated with poor overall survival (OS) (P = 0.005). In univariate analysis, the OS rate of patients with elevated serum UA levels was significantly lower than the cut-off value (hazard ratio [HR]: 3.191, 95% confidence interval [CI]: 1.456–6.993, P = 0.004), with a median survival time of 151 and 312 days in the high and low serum UA groups, respectively. The results of multivariate analysis showed that the UA level was an independent prognostic factor for immunotherapy in patients with PLC (HR: 3.131, 95% CI: 1.766–5.553, P < 0.001).ConclusionsThe serum UA level is a reliable biomarker for predicting the prognosis of patients undergoing immunotherapy for PLC, and might provide a basis for the individualized treatment of these patients. Dynamic monitoring of the serum UA level may compensate for the deficiency of the current liver cancer staging system.

A novel defined risk signature of cuproptosis-related long non-coding RNA for predicting prognosis, immune infiltration, and immunotherapy response in lung adenocarcinoma.

Background: Cuproptosis is a newly discovered non-apoptotic form of cell death that may be related to the development of tumors. Nonetheless, the potential role of cuproptosis-related lncRNAs in tumor immunity formation and patient-tailored treatment optimization of lung adenocarcinoma (LUAD) is still unclear. Methods: RNA sequencing and survival data of LUAD patients were downloaded from The Cancer Genome Atlas (TCGA) database for model training. The patients with LUAD in GSE29013, GSE30219, GSE31210, GSE37745, and GSE50081 were used for validation. The proofed cuproptosis-related genes were extracted from the previous studies. The Pearson correlation was applied to select cuproptosis-related lncRNAs. We chose differentially expressed cuproptosis-related lncRNAs in the tumor and normal tissues and allowed them to go to a Cox regression and a LASSO regression for a lncRNA signature that predicts the LUAD prognosis. Kaplan-Meier estimator, Cox model, ROC, tAUC, PCA, nomogram predictor, decision curve analysis, and real-time PCR were further deployed to confirm the model's accuracy. We examined this model's link to other regulated cell death forms. Applying TMB, immune-related signatures, and TIDE demonstrated the immunotherapeutic capabilities of signatures. We evaluated the relationship of our signature to anticancer drug sensitivity. GSEA, immune infiltration analysis, and function experiments further investigated the functional mechanisms of the signature and the role of immune cells in the prognostic power of the signature. Results: An eight-lncRNA signature (TSPOAP1-AS1, AC107464.3, AC006449.7, LINC00324, COLCA1, HAGLR, MIR4435-2HG, and NKILA) was built and demonstrated owning prognostic power by applied to the validation cohort. Each signature gene was confirmed differentially expressed in the real world by real-time PCR. The eight-lncRNA signature correlated with 2321/3681 (63.05%) apoptosis-related genes, 11/20 (55.00%) necroptosis-related genes, 34/50 (68.00%) pyroptosis-related genes, and 222/380 (58.42%) ferroptosis-related genes. Immunotherapy analysis suggested that our signature may have utility in predicting immunotherapy efficacy in patients with LUAD. Mast cells were identified as key players that support the predicting capacity of the eight-lncRNA signature through the immune infiltrating analysis. Conclusion: In this study, an eight-lncRNA signature linked to cuproptosis was identified, which may improve LUAD management strategies. This signature may possess the ability to predict the effect of LUAD immunotherapy. In addition, infiltrating mast cells may affect the signature's prognostic power.

Intermediate endpoints as surrogates for outcomes in cancer immunotherapy: a systematic review and meta-analysis of phase 3 trials

Cancer immunotherapy shows unique efficacy kinetics that differs from conventional treatment. These characteristics may lead to the prolongation of trial duration, hence reliable surrogate endpoints are urgently needed. We aimed to systematically evaluate the study-level performance of commonly reported intermediate clinical endpoints for surrogacy in cancer immunotherapy. We searched the Embase, PubMed, and Cochrane databases, between database inception and October 18, 2022, for phase 3 randomised trials investigating the efficacy of immunotherapy in patients with advanced solid tumours. An updated search was done on July, 15, 2023. No language restrictions were used. Eligible trials had to set overall survival (OS) as the primary or co-primary endpoint and report at least one intermediate clinical endpoint including objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and 1-year overall survival. Other key inclusion and exclusion criteria included: (1) adult patients (>18 years old) with advanced solid tumour; (2) no immunotherapy conducted in the control arms; (3) follow-up is long enough to achieve OS; (4) data should be public available. A two-stage meta-analytic approach was conducted to evaluate the magnitude of the association between these intermediate endpoints and OS. A surrogate was identified if the coefficient of determination (R2) was 0.7 or greater. Leave-one-out cross-validation and pre-defined subgroup analysis were conducted to examine the heterogeneity. Potential publication bias was evaluated using the Egger's and Begg's tests. This trial was registered with PROSPERO, number CRD42022381648. 52,342 patients with 15 types of tumours from 77 phase 3 studies were included. ORR (R2=0.11; 95% CI, 0.00-0.24), DCR (R2=0.01; 95% CI, 0.00-0.01), and PFS (R2=0.40; 95% CI, 0.23-0.56) showed weak associations with OS. However, a strong correlation was observed between 1-year survival and clinical outcome (R2=0.74; 95% CI, 0.64-0.83). These associations remained relatively consistent across pre-defined subgroups stratified based on tumour types, masking methods, line of treatments, drug targets, treatment strategies, and follow-up durations. No significant heterogeneities or publication bias were identified. 1-year milestone survival was the only identified surrogacy endpoint for outcomes in cancer immunotherapy. Ongoing investigations and development of new endpoints and incorporation of biomarkers are needed to identify potential surrogate markers that can be more robust than 1-year survival. This work may provide important references in assisting the design and interpretation of future clinical trials, and constitute complementary information in drafting clinical practice guidelines. None.

Screening biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression

PurposeImmunotherapy plays an important role in non-small cell lung cancer (NSCLC); in particular, immune checkpoint inhibitors (ICIs) therapy has good therapeutic effects in PD-L1-positive patients. This study aims to screen NSCLC patients with PD-L1-positive expression and select effective biomarkers for ICI immunotherapy.MethodsCollected tumor samples from the Affiliated Cancer Hospital of Xinjiang Medical University and 117 patients with stage III–IV NSCLC were included in the study. All patients were on first- or second-line therapy and not on targeted therapy. Based on the molecular profiles and clinical features, we screened biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression.Results117 NSCLC patients receiving ICIs immunotherapy were enrolled. First, we found that immunotherapy was more effective in patients with positive PD-L1 expression. Second, we found that ROS1 gene mutations, KRAS gene mutations, tumor stage, and the endocrine system diseases history are independent prognostic factors for PD-L1 positive patients. Then we combined independent risk factors and constructed a new Nomogram to predict the therapeutic efficacy of ICIs immunotherapy in PD-L1 positive patients. The Nomogram integrates these factors into a prediction model, and the predicted C-statistic of 3 months, 6 months and 12 months are 0.85, 0.84 and 0.85, which represents the high predictive accuracy of the model.ConclusionsWe have established a model that can predict the efficacy of ICIs immunotherapy in PD-L1 positive patients. The model consists of ROS1 gene mutations, KRAS gene mutations, tumor staging, and endocrine system disease history, and has good predictive ability.

ATP2C2 as a novel immune-related marker that defines the tumor microenvironment in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive cancer that affects about 13/100,000 women yearly. Patients with TNBC are often resistant to endocrine and molecular targeted therapy, making clinical treatment challenging. Researches indicate that tumor microenvironment (TME) is related to prognosis in many cancers. Therefore, we aim to identify TME immune-related biomarkers to enhance the prognosis and immunotherapy efficacy in patients with TNBC. The bulk mRNA transcriptome data and clinical information of the (GSE58812) and (GSE25055) datasets were downloaded from the Gene Expression Omnibus (GEO) database, and the ESTIMATE algorithm was used to calculate the ImmuneScore, StromalScore, and ESTIMATEScore. Patients were divided into low and high groups according to the quartiles of ImmuneScore, StromalScore, and the median of ESTIMATEScore to filter differential expression genes (DEGs), respectively. The DEGs were then evaluated using univariate and multivariate Cox regression to identify TME-related genes and its association with survival rate for the construction of a TMErisk model with three biomarkers. Then Gene Expression Profiling Interactive Analysis (GEPIA) and The Cancer Genome Atlas (TCGA) data were used to compare the gene expression in cancer and normal tissues. xCell analysis calculated the proportion of tumor-infiltrating immune cells in low and high expression of ATPase Secretory Pathway Ca2+ Transporting 2 (ATP2C2). In addition, samples from 20 TNBC patients admitted to our institution were used for immunohistochemical (IHC) examination. Three immune-related DEGs were identified, including prolyl 3-hydroxylase 2 (P3H2), sodium voltage-gated channel beta subunit 3 (SCN3B), and ATP2C2 and a TMErisk model was constructed and validated. However, only ATP2C2 was selected for further analysis. ATP2C2 mRNA level of TNBC patients was higher than that of normal breast tissue. Survival analysis showed that patients with high expression of ATP2C2 had a bad prognosis. xCell analysis demonstrated that the expression of ATP2C2 was associated with 16 kinds of tumor-infiltrating immune cells. Protein expression of ATP2C2 in TNBC tissues was higher compared to paired normal tissues in IHC. This study constructed and validated a TMErisk model that can effectively predict 3- and 5-year survival rate for TNBC patients. TNBC patients with lower expression of ATP2C2 had a good prognosis.

Tumor-infiltrating lymphocytes predict efficacy of immunotherapy in advanced non-small cell lung cancer: a single-center retrospective cohort study

Background/Purpose The current study aimed to investigate the correlation between tumor-infiltrating lymphocytes (TILs) and immunotherapy efficacy in patients with advanced non-small cell lung cancer (NSCLC). Materials and methods Eighty-nine patients with advanced NSCLC who received immune checkpoint inhibitors (ICIs) monotherapy were retrospectively enrolled in this study. The density of TILs in paraffin-embedded pathological tissues taken before receiving ICIs was quantitatively analyzed by immunohistochemical staining. The density of TILs was treated as a dichotomous variable using the median as the cutoff value. The Kaplan–Meier analysis was used to assess survival differences between groups. Univariate and multivariate Cox analyses were applied to screen out independent prognostic factors and further construct a nomogram prediction model to predict survival. Results Survival analysis showed that CD8+ TILs, CD4+ TILs, and IFN-γ+ Th1 were significant positive indicators for predicting progression-free survival (PFS) and overall survival (OS) (p < 0.05), whereas Foxp3+ Treg were a significant negative predictor (p < 0.05). The predictive role of IL-4+ Th2 was not apparent in this study and requires further investigation and exploration (p > 0.05). The nomogram prediction model exhibited good discriminative ability, with C-index values of 0.723 (95% CI 0.682-0.764) and 0.793 (95% CI, 0.738-0.848) in the training cohort and validation cohort, respectively. The AUC values indicated that the nomogram prediction model had high predictive value and the calibration curve presented good prediction accuracy. Conclusions TILs could predict the efficacy of immunotherapy and may become a promising predictor.

A meta-analysis of application of PD-1/PD-L1 inhibitor-based immunotherapy in unresectable locally advanced triple-negative breast cancer.

Aims: The purpose of this study was to explore the efficacy of immunotherapy for patients with triple-negative breast cancer (TNBC). Materials & methods: Randomized clinical trials comparing immunotherapy with chemotherapy for advanced TNBC patients were included. Results: A total of sixarticles (3183 patients) were eligible for this meta-analysis. PD-1/PD-L1 inhibitor-based immunotherapy combined with chemotherapy can significantly increase the progression-free survival(hazard ratio [HR]=0.82;95% CI=0.76-1.14; p<0.001) of unresectable locally advanced or metastatic TNBC patients without effect on overall survival, compared with chemotherapy. Conclusion: PD-1/PD-L1 inhibitors-based immunotherapy can safely improve progression-free survival in patients with unresectable locally advanced or metastatic TNBC, but has no effect on overall survival.

Exploring the complex and multifaceted interplay of the gut microbiome and cancer prevention and therapy.

Recent scientific research has indicated that the gut microbiota constitutes a nuanced, diverse ecosystem of microorganisms that have gained significant attention due to its crucial involvement in shaping human health and diseases. In particular, the gut microbiota plays a pivotal role in cancer prevention, and disturbances in its composition and function, known as dysbiosis, that have been linked to an increased risk of developing various malignancies. The gut microbiota exerts a myriad of effects on the production of anti-cancer compounds, the host's immune system and inflammation, underscoring its crucial involvement in cancer. Additionally, recent studies have shown that the gut microbiota has a role in the development of cancer, influencing cancer risk, co-infections, disease progression, and treatment response. The observation of reduced efficacy of immunotherapy in patients receiving antibiotic treatment indicates a substantial influence of the microbiota in mediating the toxicity and response ofcancer therapy, notably immunotherapy, and its immune-related side effects. A growing body of research has focused on cancer treatments that target the microbiome, including probiotics, dietary modifications, and faecal microbiota transplantation (FMT). The forthcoming era of personalised cancer therapies is anticipated to prioritise tumor evolution, molecular and phenotypic heterogeneity, and immunological profiling, with gut microbiota assuming a pivotal position in this domain. This review aims to offer clinicians a comprehensive perspective on the microbiota-cancer axis, including its influence on cancer prevention and therapy and highlights the importance of integrating microbiome science into the design and implementation of cancer therapies.

Beta-Blocker Use Is Associated With Worse Relapse-Free Survival in Patients With Head and Neck Cancer.

Although beta-blockers (BBs) have been hypothesized to exert a beneficial effect on cancer survival through inhibition of beta-adrenergic signaling pathways, clinical data on this issue have been inconsistent. We investigated the impact of BBs on survival outcomes and efficacy of immunotherapy in patients with head and neck squamous cell carcinoma (HNSCC), non-small-cell lung cancer (NSCLC), melanoma, or squamous cell carcinoma of the skin (skin SCC), independent of comorbidity status or cancer treatment regimen. Patients (N = 4,192) younger than 65 years with HNSCC, NSCLC, melanoma, or skin SCC treated at MD Anderson Cancer Center from 2010 to 2021 were included. Overall survival (OS), disease-specific survival (DSS), and disease-free survival (DFS) were calculated. Kaplan-Meier and multivariate analyses adjusting for age, sex, TNM staging, comorbidities, and treatment modalities were performed to assess the effect of BBs on survival outcomes. In patients with HNSCC (n = 682), BB use was associated with worse OS and DFS (OS: adjusted hazard ratio [aHR], 1.67; 95% CI, 1.06 to 2.62; P = .027; DFS: aHR, 1.67; 95% CI, 1.06 to 2.63; P = .027), with DSS trending to significance (DSS: aHR, 1.52; 95% CI, 0.96 to 2.41; P = .072). Negative effects of BBs were not observed in the patients with NSCLC (n = 2,037), melanoma (n = 1,331), or skin SCC (n = 123). Furthermore, decreased response to cancer treatment was observed in patients with HNSCC with BB use (aHR, 2.47; 95% CI, 1.14 to 5.38; P = .022). The effect of BBs on cancer survival outcomes is heterogeneous and varies according to cancer type and immunotherapy status. In this study, BB intake was associated with worse DSS and DFS in patients with head and neck cancer not treated with immunotherapy, but not in patients with NSCLC or skin cancer.

Tobacco exposure primes the secretion of CCL21 positively associated with tertiary lymphoid structure and response to immunotherapy

BackgroundIt has been reported that smoking history as a predictor of immunotherapy efficacy in patients with advanced lung cancer, however, the underlying mechanisms of this phenomenon remain largely unknown.MethodsThe patients...

Correlation of low B7-H6 expression with efficacy of immunotherapy inpatients with melanoma.

e21556 Background: B7-H6 (NCR3LG1) can bind to NKp30 to trigger antitumor NK cell activation and cytokine secretion. Our previous studies have shown that in gastric cancer, B7-H6 high expression was associated with better prognosis and the low expression of B7-H6 group was correlated with better immune microenvironment. However, the effect of B7-H6 expression on immunotherapy is unknown. Herein, we used the data from a clinically annotated cohort of melanoma patients treated with ICI to analyze the influence of B7-H6 expression on immunotherapy. Methods: The gene expression profile, gene mutation information and clinical data were extracted from the supplementary data in melanoma cohort (PMID: 31792460). Maximally selected rank statistics was used to select the optimum threshold for B7-H6 expression, and the patients was divided into two groups according to the expression of B7-H6, high group and low group. Kaplan-Meier survival analysis was used to evaluate the influence of B7-H6 expression on OS prognosis. Associations between variables and OS survival were tested using univariate and multivariate Cox and displayed by forest (R package). Results: We selected 3.14 as the optimum threshold of B7-H6 expression, and the patients was divided into high group (B7-H6 expression＞3.14) and low group (B7-H6 expression≤3.14). The results showed that low group was significantly associated with longer overall survival (p value = 0.048) in cohort of melanoma patients treated with anti-PD1 ICI, which was consistent with our previous results that low expression of B7-H6 group was correlated with better immune microenvironment. We selected primary lesion type, TMB and the expression of B7-H6 factors for univariate and multivariate analysis. TMB-H (top 25%) (p value = 0.051) and B7-H6 (p value = 0.051) low expression were associated with a better OS. Then the patients were divided into four groups according to the TMB and B7-H6 expression and analyzed the difference in the four groups. The results showed that in patients with TMB-L, B7-H6 low group had significant better OS than the B7-H6 high group (p value = 0.032). Conclusions: The low B7-H6 expression was correlated with better efficacy immunotherapy. The effect of B7-H6 expression on immunotherapy needs to be further prospective trial validation.