Cancer Immunotherapy Response Research Articles

An immune-related exosome signature predicts the prognosis and immunotherapy response in ovarian cancer

BackgroundCancer-derived exosomes contribute significantly in intracellular communication, particularly during tumorigenesis. Here, we aimed to identify two immune-related ovarian cancer-derived exosomes (IOCEs) subgroups in ovarian cancer (OC) and establish a prognostic model for OC patients based on immune-related IOCEs.MethodsThe Cancer Genome Atlas (TCGA) database was used to obtain RNA-seq data, as well as clinical and prognostic information. Consensus clustering analysis was performed to identify two IOCEs-associated subgroups. Kaplan-Meier analysis was used to compare the overall survival (OS) between IOCEs-high and IOCEs-low subtype. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to investigate the mechanisms and biological effects of differentially expressed genes (DEGs) between the two subtypes. Besides, an IOCE-related prognostic model of OC was constructed by Lasso regression analysis, and the signature was validated using GSE140082 as the validation set.ResultsIn total, we obtained 21 differentially expressed IOCEs in OC, and identified two IOCE-associated subgroups by consensus clustering. IOCE-low subgroup showed a favorable prognosis while IOCE-high subgroup had a higher level of immune cell infiltration and immune response. GSEA showed that pathways in cancer and immune response were mainly enriched in IOCE-high subgroup. Thus, IOCE-high subgroup may benefit more in immunotherapy treatment. In addition, we constructed a risk model based on nine IOCE-associated genes (CLDN4, AKT2, CSPG5, ALDOC, LTA4H, PSMA2, PSMA5, TCIRG1, ANO6).ConclusionWe developed a novel stratification system for OV based on IOCE signature, which could be used to estimate the prognosis as well as immunotherapy for OC patient.

Aberrant RBMX expression is relevant for cancer prognosis and immunotherapy response.

Cancer accounts for the highest rates of morbidity and mortality worldwide. RNA binding motif protein X-linked (RBMX) is a nuclear RNA-binding protein, associated with certain types of cancer by participating in the integration of sister chromatids and a combination of ribonucleoprotein complexes. However, the specific role of RBMX in cancer immunity remains unknown. This study presents the aberrant expression levels, single-cell distributions, effective prognostic roles, immune cell infiltration associations, and immunotherapy responses of RBMX as a biomarker in various types of cancer. Moreover, it validates the aberrant expression of RBMX in clinical cancer samples. Furthermore, we also evaluated the relationships between RBMX expression and myeloid-derived suppressor cells in clinical samples by immunofluorescent staining. The results showed that knockdown of RBMX can impair the proliferation, migration, and invasion of liver cancer cells. Finally, we indicated that RBMX may play an immunoregulatory role in cancer progression, affecting the therapeutic effects of immune checkpoint inhibitors in patients with cancer.

Epigenetic modulation of antitumor immunity and immunotherapy response in breast cancer: biological mechanisms and clinical implications.

Breast cancer (BC) is the most common non-skin cancer and the second leading cause of cancer death in American women. The initiation and progression of BC can proceed through the accumulation of genetic and epigenetic changes that allow transformed cells to escape the normal cell cycle checkpoint control. Unlike nucleotide mutations, epigenetic changes such as DNA methylation, histone posttranslational modifications (PTMs), nucleosome remodeling and non-coding RNAs are generally reversible and therefore potentially responsive to pharmacological intervention. Epigenetic dysregulations are critical mechanisms for impaired antitumor immunity, evasion of immune surveillance, and resistance to immunotherapy. Compared to highly immunogenic tumor types, such as melanoma or lung cancer, breast cancer has been viewed as an immunologically quiescent tumor which displays a relatively low population of tumor-infiltrating lymphocytes (TIL), low tumor mutational burden (TMB) and modest response rates to immune checkpoint inhibitors (ICI). Emerging evidence suggests that agents targeting aberrant epigenetic modifiers may augment host antitumor immunity in BC via several interrelated mechanisms such as enhancing tumor antigen presentation, activation of cytotoxic T cells, inhibition of immunosuppressive cells, boosting response to ICI, and induction of immunogenic cell death (ICD). These discoveries have established a highly promising basis for using combinatorial approaches of epigenetic drugs with immunotherapy as an innovative paradigm to improve outcomes of BC patients. In this review, we summarize the current understanding of how epigenetic processes regulate immune cell function and antitumor immunogenicity in the context of the breast tumor microenvironment. Moreover, we discuss the therapeutic potential and latest clinical trials of the combination of immune checkpoint blockers with epigenetic agents in breast cancer.

Disulfidptosis-related prognostic signature correlates with immunotherapy response in colorectal cancer

Disulfidptosis (DSP), a form of cell death caused by disulphide stress, plays an important role in tumour progression. However, the mechanisms by which DSP regulates the tumour microenvironment remain unclear. Thus, we analysed the transcriptome profiles and clinical data, which were obtained from the TCGA database, of 540 patients with colorectal cancer. Compared with the patients with low DSP expression, those with high DSP expression exhibited significantly better survival outcomes; lower stromal and ESTIMATE scores; significantly higher numbers of CD4+ T cells, M2 macrophages, dendritic cells, and neutrophils; higher expression of immune checkpoint-related genes; and lower Tregs and HLA-DQB2 levels. A prognostic signature established based on DSP-related genes demonstrated an increase in risk score with a higher clinical stage. Risk scores negatively correlated with dendritic cells, eosinophils, and CD4+ T cells and significantly positively correlated with Treg cells. Patients with higher risk scores experienced significantly worse survival outcomes and immunotherapy non-response. Our nomogram model, combining clinicopathological features and risk scores, exhibited robust prognostic and predictive power. In conclusion, DSP-related genes actively participated in regulating the tumour microenvironment. Thus, they can serve as biomarkers to provide targeted treatment for colorectal cancer.

Lymphatic system regulation of anti-cancer immunity and metastasis.

Cancer dissemination to lymph nodes (LN) is associated with a worse prognosis, increased incidence of distant metastases and reduced response to therapy. The LN microenvironment puts selective pressure on cancer cells, creating cells that can survive in LN as well as providing survival advantages for distant metastatic spread. Additionally, the presence of cancer cells leads to an immunosuppressive LN microenvironment, favoring the evasion of anti-cancer immune surveillance. However, recent studies have also characterized previously unrecognized roles for tumor-draining lymph nodes (TDLNs) in cancer immunotherapy response, including acting as a reservoir for pre-exhausted CD8+ T cells and stem-like CD8+ T cells. In this review, we will discuss the spread of cancer cells through the lymphatic system, the roles of TDLNs in metastasis and anti-cancer immune responses, and the therapeutic opportunities and challenges in targeting LN metastasis.

A Novel Signature Based on Angiogenesis-Related Genes Predicts the Prognosis and Immunotherapy Response in HER2-Positive Breast Cancer.

Background: HER2-positive breast cancer is one of the most prevalent subtypes of breast cancer and represents a significant health concern for women worldwide due to its high morbidity and mortality rates. Recent studies have consistently underscored the pivotal role of angiogenesis in the development and progression of HER2-positive breast cancer. Here, we developed a prognostic signature based on angiogenesis-related genes (ARGs) to categorize HER2-positive breast cancer patients and provide insights into their survival outcomes. Methods: Kaplan-Meier survival curve, time-dependent receiver operating characteristic (ROC) and nomogram were performed to investigate the prognostic performance of the signature. In addition, we comprehensively analyzed the correlation of the prognostic signature with immune cell infiltration, immune checkpoint inhibitors (ICIs) therapy. Finally, Immunohistochemistry (IHC) and immunoblotting were used to investigate XBP1 expression in HER2-positive breast cancer tissues. Colony formation assay was performed to examine cell proliferation of HER2-positive breast cancer cells. Results: The Kaplan-Meier curves and the ROC curves demonstrated that the ARGs had good performance in predicting the prognosis of HER2-positive breast cancer patients. In addition, we observed that the low-risk group was remarkably associated with immune infiltration and better response to ICIs. Further experimental results show that XBP1 is upregulated in human HER2-positive breast cancer, and its knockdown significantly inhibited cell proliferation. Conclusions: Our study demonstrated that the ARGs could serve as a novel biomarker for predicting the prognosis of patients with HER2-positive breast cancer and providing new insights into immunotherapy strategies for these patients.

GLS and GOT2 as prognostic biomarkers associated with dendritic cell and immunotherapy response in breast cancer

Breast cancer is the females' most common cancer. Targeting the immune microenvironment is a new and promising treatment method for breast cancer. Nevertheless, only a small section of patients can profit by immunotherapy, and improving the ability to accurately predict the potential for immunotherapy response is still awaiting further exploration. In this study, we found that the key factors of glutamine metabolism, glutaminase 1 (GLS) and mitochondrial aspartate transaminase (GOT2), showed opposite expression patterns in breast cancer samples. Based on the expression level of GLS and GOT2, we divided the breast cancer samples into two clusters: Cluster 2 showed GLS expressed higher and GOT2 expressed lower, whereas Cluster 1 showed GOT2 expressed higher and GLS expressed lower. GSEA showed that the clusters were related to pathways of immunity. Further analysis showed that Cluster 2 was positively associated with immunity infiltration. Through WGCNA, we identified a module strongly correlated with glutamine metabolism and immunity and identified 11 dendritic cell-associated genes involved in dendritic cell development, maturation, activation and other functions. In addition, Cluster 2 also showed higher immune checkpoint gene expression, which suggest the Cluster 2 had even better response to immunotherapy. The validation dataset could also be clustered into two groups. Cluster 2 (GLS expressed higher and GOT2 expressed lower) of the validation dataset was also positively associated with dendritic cells and a better immunotherapy response. Thus, these data indicate that GLS and GOT2 are prognostic biomarkers which closely related to dendritic cells and better reacted to immunotherapy in breast cancer.

Stem-Immunity Hubs Are Associated with Immunotherapy Response in Lung Cancer

Stem-Immunity Hubs Are Associated with Immunotherapy Response in Lung Cancer

Association between Atopic Dermatitis and Colorectal Cancer: TET2 as a Shared Gene Signature and Prognostic Biomarker.

Background: Recent studies have linked atopic dermatitis (AD) to colorectal cancer (CRC) risk. Their causality and potential molecular mechanisms remain unclear. Methods: We performed Mendelian randomization (MR) analysis to evaluate the causality between AD and CRC. Summary statistic data-based Mendelian randomization (SMR) analysis was used to identify CRC-related causal genes. Transcriptome analyses and immunohistochemical methods were applied to investigate the shared gene signature and potential mechanisms that contribute to the pathogenesis of both AD and CRC. A predictive analysis was performed to examine the shared gene signature associated with immunotherapy response in CRC. Results: MR analysis indicated a causal association between AD and a decreased risk of CRC. SMR analysis uncovered TET2 as a CRC-related causal gene, showing an inverse relationship with the risk of CRC. Transcriptome analyses identified TET2 as a shared gene signature between AD and CRC. Decreased TET2 expression is associated with impaired demethylation and worse prognosis in CRC patients. We observed ten pathways related to the inflammatory response and immune regulation that may be shared mechanisms underlying both AD and CRC. These findings were validated through single-cell analysis. TET2 shows promise as a powerful predictive biomarker for cancer prognosis and immunotherapy response in CRC. Conclusion: There is a causal association between AD and a decreased risk of CRC. AD may influence the occurrence of CRC by modulating immune and inflammatory responses. TET2 could serve as a potential biomarker for prognosis and may be considered a novel therapeutic target for methylation and immune-related interventions.

Preparation of glycopeptide-modified pH-sensitive liposomes for promoting antigen cross-presentation and induction of antigen-specific cellular immunity.

Cross-presentation, exogenous antigen presentation onto major histocompatibility complex class I molecules on antigen presenting cells, is crucially important for inducing antigen-specific cellular immune responses for cancer immunotherapy and for the treatment of infectious diseases. One strategy to induce cross-presentation is cytosolic delivery of an exogenous antigen using fusogenic or endosomolytic molecule-introduced nanocarriers. Earlier, we reported liposomes modified with pH-responsive polymers to achieve cytosolic delivery of an antigen. Polyglycidol-based or polysaccharide-based pH-responsive polymers can provide liposomes with delivery performance of antigenic proteins into cytosol via membrane fusion with endosomes responding to acidic pH, leading to induction of cross-presentation. Mannose residue was introduced to pH-responsive polysaccharides to increase uptake selectivity to antigen presenting cells and to improve cross-presentation efficiency. However, direct introduction of mannose residue into pH-responsive polysaccharides suppressed cytoplasmic delivery performance of liposomes. To avoid such interference, for this study, mannose-containing glycans were incorporated separately into pH-responsive polysaccharide-modified liposomes. Soybean agglutinin-derived glycopeptide was used as a ligand for lectins on antigen presenting cells. Incorporation of glycopeptide significantly increased the cellular uptake of liposomes by dendritic cell lines and increased cross-presentation efficiency. Liposomes incorporated both glycopeptide and pH-responsive polysaccharides exhibited strong adjuvant effects in vitro and induced the increase of dendritic cells, M1 macrophages, and effector T cells in the spleen. Subcutaneous administration of these liposomes induced antigen-specific cellular immunity, resulting in strong therapeutic effects in tumor-bearing mice. These results suggest that separate incorporation of glycopeptides and pH-responsive polysaccharides into antigen-loaded liposomes is an effective strategy to produce liposome-based nanovaccines to achieve antigen cross-presentation and induction of cellular immunity towards cancer immunotherapy.

Multiplex analysis for the identification of plasma protein biomarkers for predicting lung cancer immunotherapy response.

Programmed death-ligand (PD-L1) expression serves as a predictive biomarker for immune checkpoint inhibitor (ICI) sensitivity in non-small cell lung cancer (NSCLC). Nevertheless, the development of biomarkers that reliably predict ICI response remains an ongoing endeavor due to imperfections in existing methodologies. ICIs have led to a new paradigm in the treatment of NSCLC. The current companion PD-L1 diagnostics are insufficient in predicting ICI response. Therefore, we sought whether the Olink platform could be applied to predict response to ICIs in NSCLC. We collected blood samples from patients with NSCLC before ICI treatment and retrospectively analyzed proteomes based on their response to ICI. Overall, 76 NSCLC patients' samples were analyzed. Proteomic plasma analysis was performed using the Olink platform. Intraplate reproducibility, validation, and statistical analyses using elastic net regression and generalized linear models with clinical parameters were evaluated. Intraplate coefficient of variation (CV) assays ranged from 3% to 6%, and the interplate CV was 14%. In addition, the Pearson correlation coefficient of the Olink Normalized Protein eXpression data was validated. No statistical differences were observed in the analyses of progressive disease and response to ICIs. Furthermore, no single proteome showed prognostic value in terms of progression-free survival. In this study, the proximity extension assay-based approach of the Olink panel could not predict the patient's response to ICIs. Our proteomic analysis failed to achieve predictive value in both response or progression to ICIs and progression-free survival (PFS).

Identification and validation of telomerase related lncRNAs signature to predict prognosis and tumor immunotherapy response in bladder cancer

Telomerase allows eukaryotic cells to proliferate indefinitely, an important characteristic of tumor cells. Telomerase-related long no coding RNAs (TERLs) are involved in prognosis and drug sensitivity prediction; however, their association with bladder cancer (BLCA) is still unreported. The objective of this research is to determine a predictive prognostic TERL signature for OS and to provide an efficient treatment option for BLCA. The RNA sequence, clinical information, and mutational data of BLCA patients were acquired from The Cancer Genome Atlas (TCGA) database. With the help of the data from least absolute shrinkage and selection operator (LASSO) regression and Cox regression, a prognostic signature was established including 14 TERLs, which could divide BLCA patients into low-risk (L-R) and high-risk (H-R) cohorts. The time-dependent receiver operating characteristic (ROC) curve demonstrated the greater predictive power of the model. By combing the TERLs-based signature and clinical risk factors (age, sex, grade, and stage), a prognostic nomogram was constructed to forecast the survival rates of patients with BLCA at 1-, 3-, and 5-years, which was well matched by calibration plots C-index and Decision curve analysis (DCA). Furthermore, the L-R cohort showed higher tumor mutation burden (TMB) and lower tumor immune dysfunction and exclusion (TIDE) than the H-R cohort, as well as substantial variability in immune cell infiltration and immune function between the two cohorts was elucidated. As for external validation, LINC01711 and RAP2C-AS1 were identified as poor prognostic factors by survival analysis from the Kaplan–Meier Plotter database, which were validated in BLCA cell lines (EJ, 253J, T24, and 5637) and SV-HUC-1 cells as the control group using qRT-PCR. In addition, interference with the expression of RAP2C-AS1 suppresses the proliferation and migration of BLCA cells, and RAP2C-AS1 could affect the expression of CD274 and CTLA4, which could serve as prognostic markers and characterize the tumor microenvironment in BLCA. Overall, the model based on the 14-TERLs signature can efficiently predict the prognosis and drug treatment response in individuals with bladder cancer.

Inflammatory response signature score model for predicting immunotherapy response and pan-cancer prognosis

BackgroundInflammatory responses influence the outcome of immunotherapy and tumorigenesis by modulating host immunity. However, systematic inflammatory response assessment models for predicting cancer immunotherapy (CIT) responses and survival across human cancers remain unexplored. Here, we investigated an inflammatory response score model to predict CIT responses and patient survival in a pan-cancer analysis. MethodsWe retrieved 12 CIT response gene expression datasets from the Gene Expression Omnibus database (GSE78220, GSE19423, GSE100797, GSE126044, GSE35640, GSE67501, GSE115821 and GSE168204), Tumor Immune Dysfunction and Exclusion database (PRJEB23709, PRJEB25780 and phs000452.v2.p1), European Genome-phenome Archive database (EGAD00001005738), and IMvigor210 cohort. The tumor samples from six cancers types: metastatic urothelial cancer, metastatic melanoma, gastric cancer, primary bladder cancer, renal cell carcinoma, and non-small cell lung cancer.We further established a binary classification model to predict CIT responses using the least absolute shrinkage and selection operator (LASSO) computational algorithm. FindingsThe model had high predictive accuracy in both the training and validation cohorts. During sub-group analysis, area under the curve (AUC) values of 0.82, 0.80, 0.71, 0.7, 0.67, and 0.64 were obtained for the non-small cell lung cancer, gastric cancer, metastatic urothelial cancer, primary bladder cancer, metastatic melanoma, and renal cell carcinoma cohorts, respectively. CIT response rates were higher in the high-scoring training cohort subjects (51%) than the low-scoring subjects (27%). The five-year survival rates in the high- and low score groups of the training cohorts were 62% and 21%, respectively, while those of the validation cohorts were 54% and 22%, respectively (P < 0·001 in all cases). Inflammatory response signature score derived from on-treatment tumor specimens are highly predictive of response to CIT in patients with metastatic melanoma. A significant correlation was observed between the inflammatory response scores and tumor purity. Regardless of the tumor purity, patients in the low score group had a significantly poorer prognosis than those in the high score group. Immune cell infiltration analysis indicated that in the high score cohort, tumor-infiltrating lymphocytes were significantly enriched, particularly effector and natural killer cells. Inflammatory response scores were positively correlated with immune checkpoint genes, suggesting that immune checkpoint inhibitors may have benefited patients with high scores. Analysis of signature scores across different cancer types from The Cancer Genome Atlas revealed that the prognostic performance of inflammatory response scores for survival in patients who have not undergone immunotherapy can be affected by tumor purity. Interleukin 21 (IL21) had the highest weight in the inflammatory response model, suggesting its vital role in the prediction mode. Since the number of metastatic melanoma patients (n = 429) was relatively large among CIT cohorts, we further performed a co-culture experiment using a melanoma cell line and CD8 + T cell populations generated from peripheral blood monocytes. The results showed that IL21 therapy combined with anti-PD1 (programmed cell death 1) antibodies (trepril monoclonal antibodies) significantly enhanced the cytotoxic activity of CD8 + T cells against the melanoma cell line. ConclusionIn this study, we developed an inflammatory response gene signature model that predicts patient survival and immunotherapy response in multiple malignancies. We further found that the predictive performance in the non-small cell lung cancer and gastric cancer group had the highest value among the six different malignancy subgroups. When compared with existing signatures, the inflammatory response gene signature scores for on-treatment samples were more robust predictors of the response to CIT in metastatic melanoma.

Identification and validation of a T cell marker gene-based signature to predict prognosis and immunotherapy response in gastric cancer

Although the role of T cells in tumor immunity and modulation of the tumor microenvironment (TME) has been extensively studied, their precise involvement in gastric adenocarcinoma remains inadequately explored. In this work, we analyzed the single-cell RNA sequencing data set in GSE183904 and identified 322 T cell marker genes using the “FindAllMarkers” method of the R package “Seurat”. STAD patients in the TCGA database were divided into high-risk and low-risk categories based on risk scores. The five-gene prediction signature based on T cell marker genes can predict the prognosis of gastric cancer patients with high accuracy. In the training cohort, the areas under the receiver operating characteristic (ROC) curve were 0.667, 0.73, and 0.818 at 1, 3, and 5 years. External validation of the predictive signature was also performed using multiple clinical subgroups and GEO cohorts. To help with practical application, a diagnostic model was created that shows values of 0.732, 0.752, and 0.816 for the relevant areas under the ROC curve at 1, 3, and 5 years. The T cell marker genes identified in this study may serve as potential therapeutic targets, and the developed predictive signatures and nomograms may aid in the clinical management of gastric cancer.

STAT4 facilitates PD-L1 level via IL-12R/JAK2/STAT3 axis and predicts immunotherapy response in breast cancer.

Signal transducer and activator of transcription 4 (STAT4) is a critical transcription factor for T helper cell differentiation and tumor cells. Although its prognostic role and gene function have been reported in several carcinomas, the role of STAT4 in vitro and in vivo in breast cancer remains poorly understood. The effect of STAT4 in immunotherapy is also unclear. Therefore, we integrated bulk transcriptomics, experiments, and single-cell transcriptomics to systematically analyze its function in prognosis and signaling pathway. Several clinical breast cancer cohorts confirmed STAT4 as a T-cell relevant prognostic biomarker. Overexpressed STAT4 increased programmed cell death ligand 1 (PD-L1) and major histocompatibility complex class II levels in breast cancer cells. In molecular mechanism, transcriptional synergy between STAT4 and STAT3 transactivated interleukin (IL)-12R and involved a positive feedback loop: STAT4/IL-12R/JAK2-STAT3-STAT4, which contributed to the upregulation of PD-L1 expression. The above signaling axis was defined as the STAT4-related pathway and its score was used to predict T-cell expansion and anti-PD1 treatment response. These findings highlight a novel molecular mechanism indirectly regulating PD-L1 through the STAT4-related pathway: IL-12R/JAK2-STAT3-STAT4/PD-L1, and it has potential application in predicting anti-PD-1 immunotherapy response, which may pave the way for stratified immunotherapy in breast cancer.

Abstract A018: Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations

Abstract Identifying patients that are likely to respond to cancer immunotherapy is an important, yet highly challenging clinical need. Using 3139 patients across 17 different cancer types, we comprehensively studied the ability of two common copy-number alteration (CNA) scores—the tumor aneuploidy score (AS) and the fraction of genome single nucleotide polymorphism encompassed by copy-number alterations (FGA)—to predict survival following immunotherapy in both pan-cancer and individual cancer types. First, we show that choice of cutoff during CNA calling significantly influences the predictive power of AS and FGA for patient survival following immunotherapy. Remarkably, by using proper cutoff during CNA calling, AS and FGA can predict pan-cancer survival following immunotherapy for both high-TMB and low-TMB patients. However, at the individual cancer level, our data suggest that the use of AS and FGA for predicting immunotherapy response is currently limited to only a few cancer types. Therefore, larger sample sizes are needed to evaluate the clinical utility of these measures for patient stratification in other cancer types. Finally, we propose a simple, non-parameterized, elbow-point-based method to help determine the cutoff used for calling CNAs. Citation Format: Tian-Gen Chang, Yingying Cao, Eldad D Shulman, Uri Ben-David, Alejandro A. Schäffer, Eytan Ruppin. Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A018.

Development and validation of a circulating tumor cells-related signature focusing on biochemical recurrence and immunotherapy response in prostate cancer

BackgroundStudies have shown that the circulating tumor cells (CTCs) play a key role for invasion and formation of distant metastases in prostate cancer (PCa). However, few CTCs-related genes (CRGs) have been developed for biochemical recurrence (BCR) prediction and clinical applications of PCa patients. Materials and methodsBioinformatics analysis with public PCa datasets were used to investigate the relationship between the differentially expressed CRGs and BCR. Lasso-COX regression analysis was used to constructed and validated a CRGs-based BCR prediction signature for PCa. Single-cell data were used to validate the expression levels of signature genes in different cell types and then explored the cell-cell communication relationships. Finally, the expression levels of signature genes were verified and the CRGs involved in immunotherapy response were further identified. ResultsThirteen CRGs were differentially expressed and closely associated with BCR in PCa. Then we constructed and validated a BCR prediction signature for PCa patients based on 3 differentially expressed CRGs (EMID1, SPP1 and UBE2C), and the signature was an independent factor to predict BCR for PCa. Single-cell data showed the specific expression patterns of the signature genes, while the SPP1 pathway plays an important role in cell-cell communication. Further analyses suggested UBE2C was highly expressed in BCR group and high expression of UBE2C had a better response for patients who received immunotherapy. Moreover, the expression levels of UBE2C in CTCs were higher than other cells and tissues, indicated that UBE2C may affect the BCR event of PCa patients through CTCs. ConclusionOur findings demonstrated that CRGs were significantly associated with BCR and immunotherapy efficacy in PCa and CRGs may influence the BCR event through CTCs.

Classification of SLC family-related genes involved in ferroptosis predicts lung cancer prognosis and immunotherapy response

Lung adenocarcinoma, the most frequent type of lung cancer, is the leading cause of cancer-related deaths worldwide. Ferroptosis, controlled cell death that involves a high degree of iron-dependent lipid peroxidation, has been linked to tumor therapy sensitivity, patient prognosis, and cancer development. The solute carrier superfamily has over 400 members and comprises the largest class of transporters in the human genome. Solute carrier proteins can facilitate the movement of different substrates across biological membranes, which is crucial for physiological activities, including ferroptosis. Here, we developed a new model to further explore the role of the solute carrier family in ferroptosis in the lung adenocarcinoma immunological milieu. We used consensus clustering to classify patients with lung cancer into two subgroups (cluster1 and cluster2). Patients in the cluster1 subtype had a better prognosis and higher immune cell infiltration ratios than those in the cluster2 subtype. Furthermore, to evaluate the prognosis, the immune cell infiltration ratio, and the medication sensitivity of patients with lung adenocarcinoma, we developed gene scores related to the solute carrier family. In conclusion, we successfully developed a model incorporating the solute carrier family and ferroptosis to predict survival and the impact of immunotherapy on patients with lung cancer.

Immune activity score to assess the prognosis, immunotherapy and chemotherapy response in gastric cancer and experimental validation.

Gastric cancer (GC) is an extremely heterogeneous malignancy with a complex tumor microenvironment (TME) that contributes to unsatisfactory prognosis. The overall activity score for assessing the immune activity of GC patients was developed based on cancer immune cycle activity index in the Tracking Tumor Immunophenotype (TIP). Genes potentially affected by the overall activity score were screened using weighted gene co-expression network analysis (WGCNA). Based on the expression profile data of GC in The Cancer Genome Atlas (TCGA) database, COX analysis was applied to create an immune activity score (IAS). Differences in TME activity in the IAS groups were analyzed. We also evaluated the value of IAS in estimating immunotherapy and chemotherapy response based on immunotherapy cohort. Gene expression in IAS model and cell viability were determined by real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) and Cell Counting Kit-8 (CCK-8) assay, respectively. WGCAN analysis screened 629 overall activity score-related genes, which were mainly associated with T cell response and B cell response. COX analysis identified AKAP5, CTLA4, LRRC8C, AOAH-IT1, NPC2, RGS1 and SLC2A3 as critical genes affecting the prognosis of GC, based on which the IAS was developed. Further RT-qPCR analysis data showed that the expression of AKAP5 and CTLA4 was downregulated, while that of LRRC8C, AOAH-IT1, NPC2, RGS1 and SLC2A3 was significantly elevated in GC cell lines. Inhibition of AKAP5 increased cell viability but siAOAH-IT1 promoted viability of GC cells. IAS demonstrated excellent robustness in predicting immunotherapy outcome and GC prognosis, with low-IAS patients having better prognosis and immunotherapy. In addition, resistance to Erlotinib, Rapamycin, MG-132, Cyclopamine, AZ628, and Sorafenib was reduced in patients with low IAS. IAS was a reliable prognostic indicator. For GC patients, IAS showed excellent robustness in predicting GC prognosis, immune activity status, immunotherapy response, and chemotherapeutic drug resistance. Our study provided novel insights into the prognostic assessment in GC.

Immunotherapy response in microsatellite stable metastatic colorectal cancer is influenced by site of metastases

BackgroundPrior studies indicate that colorectal cancer patients with liver metastases did not benefit from regorafenib, nivolumab (REGONIVO) or regorafenib, ipilimumab, nivolumab (RIN) treatments, while those without liver metastases showed significant response. This study explores the impact of metastatic sites on treatment outcomes. MethodsChemotherapy-refractory colorectal cancer patients treated with REGONIVO or RIN were evaluated, focusing on 2-month organ-specific response, ORR, PFS and OS based on metastatic sites. ResultsOf the 96 patients analyzed (58 REGONIVO, 38 RIN), liver or peritoneal metastases led to poor outcomes, with 0 % ORR, and median PFS of 2.0 and 1.5 months respectively. In contrast, lung-only metastases had an ORR of 56.3 % and a PFS of 14 months. The presence of concurrent LN or other extrahepatic metastatic disease in patients with lung metastatic disease diminished but did not prohibit responses. The 2-month response assessment revealed activity in the lungs, soft tissues, and distant lymph nodes. ConclusionsREGONIVO and RIN were most active in lung-only metastases. Liver and peritoneal metastases were resistant. Future checkpoint inhibitor trials in MSS colorectal cancer should stratify patients based on metastatic locations.