Efficacy Of Immunotherapy In Patients Research Articles

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.

Intratumoral heterogeneity as a predictive biomarker in immunotherapy for advanced bladder cancer.

e16619 Background: Previous studies have shown that intra-tumor heterogeneity (ITH) can lead to drug resistance to tumor therapy, which is associated with poor prognosis of solid tumors. However, studies on the correlation between ITH and immunotherapy efficacy in patients with advanced bladder cancer (BLCA) are still lacking. Methods: Bioconductor R package Maftools was used to analyze somatic variants of advanced BLCA from an independent cohort (Miao-249 study cohort, PMID: 30150660) with data from 27 patients who underwent whole-exome sequencing. The ITH score was measured using the mutant-allele tumor heterogeneity (MATH) algorithm to analyze the difference in the genetic profile between the ITH score high (ITH-H) and ITH score low (ITH-L) groups, its association with tumor mutational burden (TMB), and the effect of ITH on the prognosis of immunotherapy. Results: There were significant differences in gene mutation spectrum between ITH-H and ITH-L groups. The genes with the highest mutation frequency in ITH-H group were TP53 (57.14%), DNAH5 (38.1%), TNRC18 (38.1%), TTN (38.1%), CSMD3 (33.33%), MDN1 (33.33%), MRPL49 (33.33%), and MUC19 (33.33%), while the genes with the highest mutation frequency in ITH-L group were KDM6A (83.33%), TP53 (66.67%), CALN1 (50%), MICAL2 (50%), MTOR (50%), NINL (50%), PCDHA (50%), and RMIBP2 (50%). The objective response rate (ORR) of immunotherapy was 66.66% and 42.86% for the patients with ITH-L and ITH-H subgroup. The ITH-L patients had significantly improved median overall survival (mOS) than the ITH-H group (not reach versus 12.3 months, hazard ratio (HR) = 6.65, 95%CI 0.86−51.36, P = 0.037). There was no significant difference in median TMB levels between ITH-L and ITH-H groups (8 Muts/Mb versus 7.6 Muts/Mb, P = 0.97). The TMB high (TMB-H) patients had no significantly better mOS than the TMB low (TMB-L) group (not reach versus 9.07 months, HR = 0.33, 95%CI 0.07−1.49, P = 0.13). A pooled analysis of ITH and TMB show that mOS in the ITH-L+ TMB-H group was numerically better than that in the ITH-H+TMB-H, ITH-H+TMB-L, and ITH-L+TMB-L group (not reach versus 15.6 months versus 7.1 months versus not reach, HR-1.57, 95CI 0−Inf, P = 0.1). Conclusions: The results suggest that ITH may be independent of TMB and a positive predictor of immunotherapy in patients with advanced BLCA.

Clinical Benefit From Immunotherapy in Patients With SCLC Is Associated With Tumor Capacity for Antigen Presentation

IntroductionA small percentage of patients with SCLC experience durable responses to immune checkpoint blockade (ICB). Defining determinants of immune response may nominate strategies to broaden the efficacy of immunotherapy in patients with SCLC. Prior studies have been limited by small numbers or concomitant chemotherapy administration. MethodsCheckMate 032, a multicenter, open-label, phase 1/2 trial evaluating nivolumab alone or with ipilimumab was the largest study of ICB alone in patients with SCLC. We performed comprehensive RNA sequencing of 286 pretreatment SCLC tumor samples, assessing outcome on the basis of defined SCLC subtypes (SCLC-A, -N, -P, and -Y), and expression signatures associated with durable benefit, defined as progression-free survival more than or equal to 6 months. Potential biomarkers were further explored by immunohistochemistry. ResultsNone of the subtypes were associated with survival. Antigen presentation machinery signature (p = 0.000032) and presence of more than or equal to 1% infiltrating CD8+ T cells by immunohistochemistry (hazard ratio = 0.51, 95% confidence interval: 0.27–0.95) both correlated with survival in patients treated with nivolumab. Pathway enrichment analysis revealed the association between durable benefit from immunotherapy and antigen processing and presentation. Analysis of epigenetic determinants of antigen presentation identified LSD1 gene expression as a correlate of worse survival outcomes for patients treated with either nivolumab or the combination of nivolumab and ipilimumab. ConclusionsTumor antigen processing and presentation is a key correlate of ICB efficacy in patients with SCLC. As antigen presentation machinery is frequently epigenetically suppressed in SCLC, this study defines a targetable mechanism by which we might improve clinical benefit of ICB for patients with SCLC.

Outcome-Supervised Deep Learning on Pathologic Whole Slide Images for Survival Prediction of Immunotherapy in Patients with Non–Small Cell Lung Cancer

Although programmed death-(ligand) 1 (PD-(L)1) inhibitors are marked by durable efficacy in patients with non–small cell lung cancer (NSCLC), approximately 60% of the patients still suffer from recurrence and metastasis after PD-(L)1 inhibitor treatment. To accurately predict the response to PD-(L)1 inhibitors, we presented a deep learning model using a Vision Transformer (ViT) network based on hematoxylin and eosin (H&E)–stained specimens of patients with NSCLC. Two independent cohorts of patients with NSCLC receiving PD-(L)1 inhibitors from Shandong Cancer Hospital and Institute and Shandong Provincial Hospital were enrolled for model training and external validation, respectively. Whole slide images (WSIs) of H&E-stained histologic specimens were obtained from these patients and patched into 1024 × 1024 pixels. The patch-level model was trained based on ViT to identify the predictive patches, and patch-level probability distribution was performed. Then, we trained a patient-level survival model based on the ViT–Recursive Neural Network framework and externally validated it in the Shandong Provincial Hospital cohort. A total of 291 WSIs of H&E-stained histologic specimens from 198 patients with NSCLC in Shandong Cancer Hospital and 62 WSIs from 30 patients with NSCLC in Shandong Provincial Hospital were included in the model training and validation. The model achieved an accuracy of 88.6% in the internal validation cohort and 81% in the external validation cohort. The survival model also remained a statistically independent predictor of survival from PD-(L)1 inhibitors. In conclusion, the outcome-supervised ViT–Recursive Neural Network survival model based on pathologic WSIs could be used to predict immunotherapy efficacy in patients with NSCLC.

185P Influence of corticosteroids and antibiotics on the microbiota and the efficacy of immunotherapy in patients with non-small cell lung cancer (NSCLC)

185P Influence of corticosteroids and antibiotics on the microbiota and the efficacy of immunotherapy in patients with non-small cell lung cancer (NSCLC)

Histone acetylation-related IncRNA: Potential biomarkers for predicting prognosis and immune response in lung adenocarcinoma, and distinguishing hot and cold tumours.

Histone acetylation-related lncRNAs (HARlncRNAs) play significant roles in various cancers, but their impact on lung adenocarcinoma (LUAD) remains unclear. This study aimed to develop a new HARlncRNA-based prognostic model for LUAD and to explore its potential biological mechanisms. We identified 77 histone acetylation genes based on previous studies. HARlncRNAs related to prognosis were screened by co-expression, univariate and multivariate analyses, and least absolute shrinkage selection operator regression (LASSO). Afterward, a prognostic model was established based on the screened HARlncRNAs. We analysed the relationship between the model and immune cell infiltration characteristics, immune checkpoint molecule expression, drug sensitivity, and tumour mutational burden (TMB). Finally, the entire sample was divided into three clusters to further distinguish between hot and cold tumours. A seven-HARlncRNA-based prognostic model was established for LUAD. The area under the curve (AUC) of the risk score was the highest among all the analysed prognostic factors, indicating the accuracy and robustness of the model. The patients in the high-risk group were predicted to be more sensitive to chemotherapeutic, targeted, and immunotherapeutic drugs. It was worth noting that clusters could effectively identify hot and cold tumours. In our study, clusters 1 and 3 were considered hot tumours that were more sensitive to immunotherapy drugs. We developed a risk-scoring model based on seven prognostic HARlncRNAs that promises to be a new tool for evaluating the prognosis and efficacy of immunotherapy in patients with LUAD.

Intrinsic resistance and efficacy of immunotherapy in microsatellite instability-high colorectal cancer: A systematic review and meta-analysis

Some patients with microsatellite instability-high colorectal cancer (MSI-H CRC) have shown a poor response to immunotherapy in clinical trials. We investigated the intrinsic resistance to and efficacy of immunotherapy in patients with MSI-H CRC. The PubMed and Web of Science databases were searched using keywords such as “colorectal cancer,” “immunotherapy,” and “clinical experiment.” Random-effects models were used to generate the combined complete response, partial response, stable disease, progressive disease, objective response rate (ORR), disease control rate (DCR), and incidence of adverse events. We then performed a subgroup analysis based on the ORR and incidence of intrinsic resistance. The meta-analysis included seven clinical trials. The incidences of complete response, partial response, stable disease, and progressive disease summarized by the random-effects model were 8%, 37%, 26%, and 25%, respectively. The ORR and DCR were 45% and 71%, respectively. The ORRs of programmed cell death protein 1 inhibitor (anti-PD-1), programmed death ligand 1 inhibitor (anti-PD-L1), and anti-PD-1 combined with cytotoxic T lymphocyte-associated antigen 4 inhibitor (anti-CTLA-4) immunotherapy were 38%, 54%, and 57%, respectively. The ORR of immune checkpoint inhibitors for first- and third-line therapy was 56% and 32%, respectively. Dual-drug immunotherapy significantly reduced the incidence of intrinsic resistance to immunotherapy (12% vs 31%). The incidences of intrinsic resistance to first-line therapy and second-line and later therapy were 29% and 26%, respectively. Approximately 25% of patients with MSI-H CRC had intrinsic resistance to immunotherapy. Anti-PD-1 combined with anti-CTLA-4 significantly increased the ORR, thereby reducing the incidence of intrinsic resistance. Moving immunotherapy into earlier lines of therapy, although not reducing the incidence of intrinsic resistance, can improve the ORR in patients with MSI-H CRC.

Intrinsic resistance and efficacy of immunotherapy in microsatellite instability-high colorectal cancer: A systematic review and meta-analysis.

Some patients with microsatellite instability-high colorectal cancer (MSI-H CRC) have shown a poor response to immunotherapy in clinical trials. We investigated the intrinsic resistance to and efficacy of immunotherapy in patients with MSI-H CRC. The PubMed and Web of Science databases were searched using keywords such as "colorectal cancer," "immunotherapy," and "clinical experiment." Random-effects models were used to generate the combined complete response, partial response, stable disease, progressive disease, objective response rate (ORR), disease control rate (DCR), and incidence of adverse events. We then performed a subgroup analysis based on the ORR and incidence of intrinsic resistance. The meta-analysis included seven clinical trials. The incidences of complete response, partial response, stable disease, and progressive disease summarized by the random-effects model were 8%, 37%, 26%, and 25%, respectively. The ORR and DCR were 45% and 71%, respectively. The ORRs of programmed cell death protein 1 inhibitor (anti-PD-1), programmed death ligand 1 inhibitor (anti-PD-L1), and anti-PD-1 combined with cytotoxic T lymphocyte-associated antigen 4 inhibitor (anti-CTLA-4) immunotherapy were 38%, 54%, and 57%, respectively. The ORR of immune checkpoint inhibitors for first- and third-line therapy was 56% and 32%, respectively. Dual-drug immunotherapy significantly reduced the incidence of intrinsic resistance to immunotherapy (12% vs 31%). The incidences of intrinsic resistance to first-line therapy and second-line and later therapy were 29% and 26%, respectively. Approximately 25% of patients with MSI-H CRC had intrinsic resistance to immunotherapy. Anti-PD-1 combined with anti-CTLA-4 significantly increased the ORR, thereby reducing the incidence of intrinsic resistance. Moving immunotherapy into earlier lines of therapy, although not reducing the incidence of intrinsic resistance, can improve the ORR in patients with MSI-H CRC.

Construction of a prognostic model for HCC based on ferroptosis-related lncRNAs expression and its potential to predict the response and irAEs of immunotherapy.

Background: Ferroptosis is an iron-dependent programmed cell death process, and studies have confirmed that it plays an important regulatory role in the occurrence and development of various malignancies including hepatocellular carcinoma (HCC). In addition, the role of abnormally expressed long non-coding RNAs (lncRNAs) in regulating and driving the occurrence and development of HCC has attracted more and more attention. However, there is still a lack of research on the role of ferroptosis-related lncRNAs in the prognosis prediction of HCC patients. Method: In this study, we used the Pearson test method to analyze the association between differentially expressed lncRNAs and ferroptosis-related genes in HCC and normal tissues obtained from The Cancer Genome Atlas (TCGA), and found 68 aberrantly expressed and prognosis-related ferroptosis-related lncRNAs. Based on this, we established an HCC prognostic model composed of 12 ferroptosis-related lncRNAs. In addition, HCC patients were divided into a high-risk group and a low-risk group according to the risk score of this 12 ferroptosis-related lncRNAs prognostic model. Gene enrichment analysis indicated that ferroptosis-related lncRNA-based expression signatures may regulate HCC immune microenvironment signaling pathways through ferroptosis, chemical carcinogenesis-reactive oxygen species, and NK cell-mediated cytotoxicity pathways. In addition, immune cell correlation analysis showed that there were significant differences in immune infiltrating cell subtypes, such as Th cells, macrophages, monocytes, and Treg cells between the two groups. In addition, the expression of multiple immune checkpoint molecules was found to be significantly increased in the high-risk group (eg, PD1, CTLA-4, CD86, etc.). Results: Our research provides a new method for predicting prognosis using a ferroptosis-related lncRNA expression signature prognostic model in hepatocellular carcinoma. And it provides new tools for predicting patient response and adverse effects of immunotherapy. Conclusion: In conclusion, ferroptosis-related lncRNA expression signatures can be used to construct a prognostic prediction model to predict the overall survival of HCC patients, and can be used as an independent influencing factor for prognosis. Further analysis showed that ferroptosis-related lncRNAs may affect the efficacy of immunotherapy in patients with HCC by altering the tumor microenvironment, so this model may serve as a new indicator of the response and irAEs of HCC to immunotherapy.

The influence of metastatic patterns and tumor load on therapeutic efficacy of immunotherapy in patients with metastatic melanoma as determined by quantitative PET-parameters using [ 18 F]-fluorodeoxyglucose PET/computed tomography.

The introduction of immunotherapy was a revolution in the treatment of metastatic melanoma. Nevertheless, there are only few clinical parameters to predict response to immunotherapy. The purpose of this study was to identify metastatic patterns that can predict response by using noninvasive 18 F-FDG PET/CT imaging. In 93 immunotherapy-treated patients, total metabolic tumor volume (MTV) was measured before and after treatment. The differences were compared to quantify therapy response. Patients were divided into seven subgroups regarding the affected organ systems. The results as well as clinical factors were evaluated in multivariate analyses. No subgroup of metastatic patterns had a significant difference in response rates, but with a trend towards poorer response regarding osseous and hepatic metastases. Osseous metastases presented with significant lower disease-specific survival (DSS) ( P = 0.001). Sole lymph node metastases were the only subgroup with MTV reduction and with significant higher DSS (57.6 months; P = 0.033). Patients, who ever developed brain metastases, showed a high progression of MTV of 201 ml ( P = 0.583) and poor DSS of 49.7 months ( P = 0.077). Lower numbers of affected organs indicated significantly higher DSS (hazard ratio, 1.346; P = 0.006). Osseous metastases represented a negative predictive factor for response to immunotherapy and survival. Cerebral metastases, especially when nonresponsive to immunotherapy, predicted poor survival and high increase of MTV. A high number of affected organ systems was identified as a negative factor for response and survival. Patients with only lymph node metastases showed a better response and survival.

Organ-specific immune checkpoint inhibitor treatment in lung cancer: a systematic review and meta-analysis

ObjectivesBased on the acknowledged organ-specific immune microenvironment, little is known regarding the efficacy of immunotherapy in patients with lung cancer according to metastatic sites. This meta-analysis aimed to explore the...

Spatial multi-omics revealed the impact of tumor ecosystem heterogeneity on immunotherapy efficacy in patients with advanced non-small cell lung cancer treated with bispecific antibody

BackgroundImmunotherapy for malignant tumors has made great progress, but many patients do not benefit from it. The complex intratumoral heterogeneity (ITH) hindered the in-depth exploration of immunotherapy. Conventional bulk sequencing...

Identification of a tumour immune barrier in the HCC microenvironment that determines the efficacy of immunotherapy

The tumour microenvironment (TME) is a crucial mediator of cancer progression and therapeutic outcome. The TME subtype correlates with patient response to immunotherapy in multiple cancers. Most previous studies have focused on the role of different cellular components in the TME associated with immunotherapy efficacy. However, the specific structure of the TME and its role in immunotherapy efficacy remain largely unknown. We combined spatial transcriptomics with single-cell RNA-sequencing and multiplexed immunofluorescence to identify the specific spatial structures in the TME that determine the efficacy of immunotherapy in patients with hepatocellular carcinoma (HCC) receiving anti-PD-1 treatment. We identified a tumour immune barrier (TIB) structure, a spatial niche composed of SPP1+ macrophages and cancer-associated fibroblasts (CAFs) located near the tumour boundary, which is associated with the efficacy of immune checkpoint blockade. Furthermore, we dissected ligand‒receptor networks among malignant cells, SPP1+ macrophages, and CAFs; that is, the hypoxic microenvironment promotes SPP1 expression, and SPP1+ macrophages interact with CAFs to stimulate extracellular matrix remodelling and promote TIB structure formation, thereby limiting immune infiltration in the tumour core. Preclinically, the blockade of SPP1 or macrophage-specific deletion of Spp1 in mice led to enhanced efficacy of anti-PD-1 treatment in mouse liver cancer, accompanied by reduced CAF infiltration and increased cytotoxic T-cell infiltration. We identified that the TIB structure formed by the interaction of SPP1+ macrophages and CAFs is related to immunotherapy efficacy. Therefore, disruption of the TIB structure by blocking SPP1 may be considered a relevant therapeutic approach to enhance the therapeutic effect of immune checkpoint blockade in HCC. Only a limited number of patients with hepatocellular carcinoma (HCC) benefit from tumour immunotherapy, which significantly hinders its application. Herein, we used multiomics to identify the spatial structure of the tumour immune barrier (TIB), which is formed by the interaction of SPP1+ macrophages and cancer-associated fibroblasts in the HCC microenvironment. This structure constrains immunotherapy efficacy by limiting immune cell infiltration into malignant regions. Preclinically, we revealed that blocking SPP1 or macrophage-specific deletion of Spp1 in mice could destroy the TIB structure and sensitize HCC cells to immunotherapy. These results provide the first key steps towards finding more effective therapies for HCC and have implications for physicians, scientists, and drug developers in the field of HCC.

Circulating tumor cells PD-L1 expression detection and correlation of therapeutic efficacy of immune checkpoint inhibition in advanced non-small-cell lung cancer.

This study investigated whether programmed death-ligand 1 (PD-L1) expression of circulating tumor cells (CTCs) in peripheral blood can serve as a predictive biomarker for immunotherapy efficacy in patients with advanced non-small-cell lung cancer (NSCLC). We employed a negative enrichment method to isolate CTCs. We identified PD-L1 + CTCs as PD-L1+/4',6-diamidino-2-phenylindole (DAPI)+/CD45-circulating tumor cells through an immunofluorescence method. Tumor tissue PD-L1 expression was determined by immunohistochemical staining. The correlation between CTC PD-L1 expression and patients' prognostic features was estimated through the Kaplan-Meier method. CTCs released a higher detection rate of PD-L1 expression than tumor tissues (53.0% vs. 42.1%). No correlation was observed between them. Forty-nine NSCLC patients received anti-PD-1/PD-L1 immunotherapy (three with combined anti-PD-1/PD-L1 and cytotoxic T lymphocyte-associated antigen-4 (CTLA-4), two with four cycles of combined immune checkpoint inhibitors [ICIs] plus chemotherapy and ICI monotherapy for maintenance). Patients with PD-L1 expression on tissue or CTCs had a median progression-free survival (mPFS) of 5.6months (n=36, 95% confidence interval [CI] 3.6-7.5months), significantly longer than those without PD-L1 detection (n=9, mPFS of 1.4months, 95% CI 1.3-1.5months, log-rank p=0.032). The multivariable Cox proportional-hazard model suggested that the tissue or CTC PD-L1 expression was associated with a lower risk of progression (hazard ratio 0.45, 95% CI 0.21-0.98, p=0.043). CTCs and tumor tissues reveal heterogeneous expression of PD-L1 in NSCLC patients. Patients with baseline PD-L1 expression on CTCs or tissue showed prolonged mPFS and may help to identify the subsets of patients who potentially benefit from immunotherapy.

Study of Immunotherapy and Intestinal Flora Changes in Patients with Liver Cancer

Hepatocellular carcinoma (HCC) is one of the common major malignancies worldwide and has the third highest mortality rate of any malignancy. The current field of treatment for hepatocellular carcinoma is multidisciplinary in involvement and a combination of therapeutic approaches, among which immunotherapy is the treatment modality for advanced hepatocellular carcinoma. This review provides new ideas for developing immunotherapy regimens and improving the efficacy of immunotherapy for patients with advanced liver cancer by summarising the progress of intestinal flora in the immunotherapy of patients with liver cancer.

CXCL14 as a potential marker for immunotherapy response prediction in renal cell carcinoma.

Epigenetic mechanisms play vital roles in the activation, differentiation, and effector function of immune cells. The breast and kidney-expressed chemokine (CXCL14) mainly contributes to the regulation of immune cells. However, its role in shaping the tumor immune microenvironment (TIME) is yet to be elucidated in renal cell carcinoma (RCC). This study aimed to elucidate the role of CXCL14 in predicting the efficacy of immunotherapy in patients with RCC. CXCL14 expression and RNA-sequencing, single-cell RNA-sequencing (scRNA-seq), and survival datasets of RCC from public databases were analyzed, and survival was compared between different CXCL14 levels. The correlation between CXCL14 and immune infiltration and human leukocyte antigen (HLA) gene expression was analyzed with TIMER2.0 and gene expression profiling interactive analysis. Institutional scRNA-seq and immunohistochemical staining analyses were used to verify the relationship between CXCL14 expression level and the efficacy of immunotherapy. CXCL14 was expressed in fibroblast and malignant cells in RCC, and higher expression was associated with better survival. Enrichment analysis revealed that CXCL14 is involved in immune activation, primarily in antigen procession, antigen presentation, and major histocompatibility complex assemble. CXCL14 expression was positively correlated with T-cell infiltration as well as HLA-related gene expression. Among the RCC cohort receiving nivolumab in Checkmate 025, the patients with CXCL14 high expression had better overall survival than those with CXCL14 low expression after immunotherapy. scRNA-seq revealed a cluster of CXCL14+ fibroblast in immunotherapy responders. Immunohistochemistry analysis verified that the patients with high CXCL14 expression had an increased proportion of high CD8 expression simultaneously. The expression level of CXCL14 was associated with CXCR4 expression in RCC. CXCL14 expression is associated with immunotherapy response in RCC. It is a promising biomarker for immunotherapy response prediction and may be an effective epigenetic modulator in combination with immunotherapy approaches.

Immune-related gene-based prognostic index for predicting survival and immunotherapy outcomes in colorectal carcinoma.

Colorectal cancer shows high incidence and mortality rates. Immune checkpoint blockade can be used to treat colorectal carcinoma (CRC); however, it shows limited effectiveness in most patients. To identify patients who may benefit from immunotherapy using immune checkpoint inhibitors, we constructed an immune-related gene prognostic index (IRGPI) for predicting the efficacy of immunotherapy in patients with CRC. Transcriptome datasets and clinical information of patients with CRC were used to identify differential immune-related genes between tumor and para-carcinoma tissue. Using weighted correlation network analysis and Cox regression analysis, the IRGPI was constructed, and Kaplan-Meier analysis was used to evaluate its predictive ability. We also analyzed the molecular and immune characteristics between IRGPI high-and low-risk subgroups, performed sensitivity analysis of ICI treatment, and constructed overall survival-related receiver operating characteristic curves to validate the IRGPI. Finally, IRGPI genes and tumor immune cell infiltration in CRC model mice with orthotopic metastases were analyzed to verify the results. The IRGPI was constructed based on the following 11 hub genes: ADIPOQ, CD36, CCL24, INHBE, UCN, IL1RL2, TRIM58, RBCK1, MC1R, PPARGC1A, and LGALS2. Patients with CRC in the high-risk subgroup showed longer overall survival than those in the low-risk subgroup, which was confirmed by GEO database. Clinicopathological features associated with cancer progression significantly differed between the high- and low-risk subgroups. Furthermore, Kaplan-Meier analysis of immune infiltration showed that the increased infiltration of naïve B cells, macrophages M1, and regulatory T cells and reduced infiltration of resting dendritic cells and mast cells led to a worse overall survival in patients with CRC. The ORC curves revealed that IRGPI predicted patient survival more sensitive than the published tumor immune dysfunction and rejection and tumor inflammatory signature. Thus, the low-risk subgroup is more likely to benefit from ICIs than the high-risk subgroup. CRC model mice showed higher proportions of Tregs, M1 macrophages, M2 macrophages and lower proportions of B cells, memory B cell immune cell infiltration, which is consistent with the IRGPI results. The IRGPI can predict the prognosis of patients with CRC, reflect the CRC immune microenvironment, and distinguish patients who are likely to benefit from ICI therapy.

A six lipid metabolism related gene signature for predicting the prognosis of hepatocellular carcinoma

Globally, hepatocellular carcinoma (HCC) is one of the most lethal malignant tumors. Studies have shown that alterations in the tumor immune microenvironment (TIME) play a significant role in the pathogenesis and progression of HCC, and notably, lipid metabolism has been shown to regulate TIME. Therefore, in predicting the prognosis and efficacy of immunotherapy in patients with HCC, lipid metabolism-related prognostic factors are highly relevant. mRNA expression data of HCC were obtained from the Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and gene expression omnibus (GEO) databases. and lipid metabolism-related genes were also obtained from the GSEA databases. Least absolute shrinkage and selection operator regression analysis, univariate and multivariate Cox proportional hazards analysis were used to explore lipid metabolism-related prognostic genes and further construct a prognostic signature in the training set, ICGC and GSE54236 were used to validate the accuracy of the signature. qRT-PCR was used to detect the mRNA levels of lipid metabolism-related prognostic genes in HCC tissues and their paired adjacent tissues. Nile red staining was used to demonstrate lipid content in HCC tissues. Immunofluores-cence and ELISA were used to detect immune cells and immune responses in HCC tissues and serum. Six lipid metabolism-related genes (ADH1C, APEX1, ME1, S100A10, ACACA and CYP2C9) were identified as independent prognostic factors, which were used for risk model construction for HCC patients. The areas under the 1-, 2-, and 3-year ROC curves for the TCGA cohort were 0.758, 0.701 and 0.671, respectively. Compared with paired paracancerous tissues, qRT-PCR revealed that APEX1, ME1, S100A10 and ACACA were up-regulated in HCC tissues, whereas ADH1C and CYP2C9 were down-regulated in HCC tissues. Nile red staining indicated that this study showed that both the HCC tissue and serum of patients in the high-risk group exhibited lipid accumulation. Our identified prognostic model comprising six lipid metabolism-related genes could provide survival prediction. Moreover, HCC drug therapy target selection and molecular marker research can be guided by our predictive model.