Effect of NCOR1 Mutations on Immune Microenvironment and Efficacy of Immune Checkpoint Inhibitors in Patient with Bladder Cancer

Prediction of immunotherapy response using mutations to cancer protein assemblies

While immune checkpoint inhibitors have revolutionized cancer therapy, many patients exhibit poor outcomes. Here, we show immunotherapy responses in bladder and non-small cell lung cancers are effectively predicted by factoring tumor mutation burden (TMB) into burdens on specific protein assemblies. This approach identifies 13 protein assemblies for which the assembly-level mutation burden (AMB) predicts treatment outcomes, which can be combined to powerfully separate responders from nonresponders in multiple cohorts (e.g., 76% versus 37% bladder cancer 1-year survival). These results are corroborated by (i) engineered disruptions in the predictive assemblies, which modulate immunotherapy response in mice, and (ii) histochemistry showing that predicted responders have elevated inflammation. The 13 assemblies have diverse roles in DNA damage checkpoints, oxidative stress, or Janus kinase/signal transducers and activators of transcription signaling and include unexpected genes (e.g., PIK3CG and FOXP1) for which mutation affects treatment response. This study provides a roadmap for using tumor cell biology to factor mutational effects on immune response.

Toxicity profiles of immune checkpoint inhibitors in nervous system cancer: a comprehensive disproportionality analysis using FDA adverse event reporting system

BACKGROUND

Immune-related adverse events (irAEs) always occur during treatment with immune checkpoint inhibitors (ICIs). Patients with nervous system cancer (NSC) may gain clinical benefit from ICIs, but irAEs in NSC patients are rarely examined. Therefore, our study systematically summarized reports of irAEs in NSC.

METHODS

We obtained information from the FDA adverse event reporting system from the first quarter (Q1) of 2013 to the fourth quarter (Q4) of 2022. We examined use of a combination of ICIs and chemotherapy (ICI_Chemo) or chemotherapy only (ICI_Chemo) for patients with NSC. Multiple disproportionality analyses were applied to assess irAEs. Multiomics data from the gene expression omnibus (GEO) database were analyzed to explore potential molecular mechanisms associated with irAEs in NSC patients.

RESULTS

Fourteen irAEs were identified in 8,357 NSC patients after removing duplicates; the top five events were seizure, confused state, encephalopathy, muscular weakness and gait disturbance. Older patients were more likely to develop irAEs than were younger patients. From the start of ICIs_Chemo to irAE occurrence, there was a significant difference in the time to onset of irAEs between age groups. irAEs may occur via mechanisms involving the inflammatory response, secretion of inflammatory mediators, and aberrant activation of pathologic pathways.

CONCLUSIONS

This study helps to characterize irAEs in NSC patients treated with ICIs. We combined GEO database analysis to explore the potential molecular mechanisms of irAEs. The results of this study provide a basis for improving the toxic effects of ICIs in NSC patients.

The establishment of kidney cancer organoid line in drug testing

INTRODUCTION

Kidney cancer is a common urological malignancy worldwide with an increasing incidence in recent years. Among all subtypes, renal cell carcinoma (RCC) represents the most predominant malignancy in kidney. Clinicians faced a major challenge to select the most effective and suitable treatment regime for patients from a wide range of modalities, despite improved understanding and diagnosis of RCC.

OBJECTIVE

Recently, organoid culture gained more interest as the 3D model is shown to be highly patient specific which is hypothetically beneficial to the investigation of precision medicine. Nonetheless, the development and application of organotypic culture in RCC is still immature, therefore, the primary objective of this study was to establish an organoid model for RCC.

MATERIALS AND METHODS

Patients diagnosed with renal tumor and underwent surgical intervention were recruited. RCC specimen was collected and derived into organoids. Derived organoids were validated by histological examminations, sequencing and xenograft. Drug response of organoids were compared with resistance cell line and patients' clinical outcomes.

RESULTS

Our results demonstrated that organoids could be successfully derived from renal tumor and they exhibited high concordance in terms of immunoexpressional patterns. Sequencing results also depicted concordant mutations of driver genes in both organoids and parental tumor tissues. Critical and novel growth factors were discovered during the establishment of organoid model. Besides, organoids derived from renal tumor exhibited tumorigenic properties in vivo. In addition, organoids recapitulated patient's in vivo drug resistance and served as a platform to predict responsiveness of other therapeutic agents.

CONCLUSION

Our RCC organoid model recaptiluated histological and genetic features observed in primary tumors. It also served as a potential platform in drug screening for RCC patients, though future studies are necessary before translating the outcomes into clinical practices.

Age-dependent molecular variations in osteosarcoma: implications for precision oncology across pediatric, adolescent, and adult patients

Background

Osteosarcoma is a leading subtype of bone tumor affecting adolescents and adults. Comparative molecular characterization among different age groups, especially in pediatric, adolescents and adults, is scarce.

Methods

We collected samples from 194 osteosarcoma patients, encompassing pediatric, adolescent, and adult cohorts. Genomic analyses were conducted to reveal prevalent mutations and compare molecular features in pediatric, adolescent, and adult patients.

Results

Samples from 194 osteosarcoma patients across pediatric to adult ages were analyzed, revealing key mutations such as TP53, FLCN, NCOR1, and others. Children and adolescents showed more gene amplifications and HRD mutations, while adults had a greater Tumor Mutational Burden (TMB). Mutations in those over 15 were mainly in cell cycle and PI3K/mTOR pathways, while under 15s had more in cell cycle and angiogenesis with higher VEGFA, CCND3, TFEB mutations. CNV patterns varied with age: VEGFA and XPO5 amplifications more in under 25s, and CDKN2A/B deletions in over 25s. Genetic alterations in genes like MCL1 and MYC were associated with poor prognosis, with VEGFA mutations also indicating worse outcomes. 58% of patients had actionable mutations, suggesting opportunities for targeted therapies. Age-specific patterns were observed, with Multi-TKI mutations more common in younger patients and CDK4/6 inhibitor mutations in adults, highlighting the need for personalized treatment approaches in osteosarcoma. In a small group of patients with VEGFR amplification, postoperative treatment with multi-kinase inhibitors resulted in a PR in 3 of 13 cases, especially in patients under 15. A significant case involved a 13-year-old with a notable tumor size reduction achieving PR, even with other genetic alterations present in some patients with PD.

Conclusion

This study delineates the molecular differences among pediatric, adolescent, and adult osteosarcoma patients at the genomic level, emphasizing the necessity for precision diagnostics and treatment strategies, and may offer novel prognostic biomarkers for patients with osteosarcoma. These findings provide a significant scientific foundation for the development of individualized treatment approaches tailored to patients of different age groups.

Role of body mass index and weight change in the risk of cancer: A systematic review and meta-analysis of 66 cohort studies

Background

This study was designed to evaluate the effects of body mass index (BMI) and weight change on the risk of developing cancer overall and cancer at different sites.

Methods

We searched PubMed and other databases up to July 2023 using the keywords related to 'risk', 'cancer', 'weight', 'overweight', and 'obesity'. We identified eligible studies, and the inclusion criteria encompassed cohort studies in English that focused on cancer diagnosis and included BMI or weight change as an exposure factor. Multiple authors performed data extraction and quality assessment, and statistical analyses were carried out using RevMan and R software. We used random- or fixed-effects models to calculate the pooled relative risk (RR) or hazard ratio along with 95% confidence intervals (CIs). We used the Newcastle-Ottawa Scale to assess study quality.

Results

Analysis included 66 cohort studies. Compared to underweight or normal weight, overweight or obesity was associated with an increased risk of endometrial cancer, kidney cancer, and liver cancer but a decreased risk of prostate cancer and lung cancer. Being underweight was associated with an increased risk of gastric cancer and lung cancer but not that of postmenopausal breast cancer or female reproductive cancer. In addition, weight loss of more than five kg was protective against overall cancer risk.

Conclusions

Overweight and obesity increase the risk of most cancers, and weight loss of >5 kg reduces overall cancer risk. These findings provide insights for cancer prevention and help to elucidate the mechanisms underlying cancer development.

Registration

Reviewregistry1786.

Potential anti-tumor effects of regulatory T cells in the tumor microenvironment: a review

Regulatory T cells (Tregs) expressing the transcription factor FoxP3 are essential for maintaining immunological balance and are a significant component of the immunosuppressive tumor microenvironment (TME). Single-cell RNA sequencing (ScRNA-seq) technology has shown that Tregs exhibit significant plasticity and functional diversity in various tumors within the TME. This results in Tregs playing a dual role in the TME, which is not always centered around supporting tumor progression as typically believed. Abundant data confirms the anti-tumor activities of Tregs and their correlation with enhanced patient prognosis in specific types of malignancies. In this review, we summarize the potential anti-tumor actions of Tregs, including suppressing tumor-promoting inflammatory responses and boosting anti-tumor immunity. In addition, this study outlines the spatial and temporal variations in Tregs function to emphasize that their predictive significance in malignancies may change. It is essential to comprehend the functional diversity and potential anti-tumor effects of Tregs to improve tumor therapy strategies.

GBP5 Expression Predicted Prognosis of Immune Checkpoint Inhibitors in Small Cell Lung Cancer and Correlated with Tumor Immune Microenvironment

Background

The discovery and development of immune checkpoint inhibitors (ICIs) has significantly enhanced the arsenal of immunotherapy treatments available for cancer patients. The identification of biomarkers that are indicative of an individual's sensitivity to treatment with ICIs is useful for screening SCLC patients prior to commencement of any ICIs based immunotherapy. However, the relationship between GBP5 and the prognosis of SCLC immunotherapy is still unclear and requires further study.

Methods

We downloaded two SCLC datasets, namely the George-SCLC and Jiang-SCLC cohorts. We used the TIDE algorithm to predict the efficacy of immunotherapy for SCLC patients. The QuanTIseq, MCPcounter, and EPIC algorithms are used to calculate the proportions of immune cells in SCLC patients. Additionally, we retrospectively collected 35 SCLC samples from the first affiliated hospital of the Hengyang Medical school.

Results

Patients in each cohort were devided into two groups with high (GBP5-High) and low (GBP5-Low) expression of GBP5. In both cohorts, the GBP5-High population had a higher proportion of patients that responded well to immunotherapy (responders) (p < 0.05). In addition, both GBP5-High subgroups had significantly increased cytotoxicity, chemokines, antigen presenting, and TNF family related genes. We also determined that GBP5 was related to high-level infiltration of B cells, CD4+T cells, CD8+T cells and NK cells.

Conclusion

In this study, we found that GBP5 has the potential to be used as a biomarker of ICIs efficacy for SCLC patients. GBP5 is related to the quantity of inflammatory molecules, a high level of immune infiltration, and a highly activated immune response pathway.

Multimodal molecular landscape of response to Y90-resin microsphere radioembolization followed by nivolumab for advanced hepatocellular carcinoma

BACKGROUND

Combination therapy with radioembolization (yttrium-90)-resin microspheres) followed by nivolumab has shown a promising response rate of 30.6% in a Phase II trial (CA209-678) for advanced hepatocellular carcinoma (HCC); however, the response mechanisms and relevant biomarkers remain unknown.

METHODS

By collecting both pretreatment and on-treatment samples, we performed multimodal profiling of tissue and blood samples and investigated molecular changes associated with favorable responses in 33 patients from the trial.

RESULTS

We found that higher tumor mutation burden, NCOR1 mutations and higher expression of interferon gamma pathways occurred more frequently in responders. Meanwhile, non-responders tended to be enriched for a novel Asian-specific transcriptomic subtype (Kaya_P2) with a high frequency of chromosome 16 deletions and upregulated cell cycle pathways. Strikingly, unlike other cancer types, we did not observe any association between T-cell populations and treatment response, but tumors from responders had a higher proportion of CXCL9+/CXCR3+ macrophages. Moreover, biomarkers discovered in previous immunotherapy trials were not predictive in the current cohort, suggesting a distinctive molecular landscape associated with differential responses to the combination therapy.

CONCLUSIONS

This study unraveled extensive molecular changes underlying distinctive responses to the novel treatment and pinpointed new directions for harnessing combination therapy in patients with advanced HCC.

Case report: durable complete response to pembrolizumab plus lenvatinib in a metastatic upper tract urothelial carcinoma patient with high tumor mutational burden and an immune-active tumor microenvironment

Immune checkpoint inhibitors (ICIs) have been approved as an emerging first-line treatment option for advanced and metastatic urothelial carcinoma whose tumors express programmed death-ligand 1 (PD-L1). However, the efficacy of immunotherapy in PD-L1-negative urothelial carcinoma patients remains unclear, and biomarkers beyond PD-L1 expression to predict response to immunotherapy need investigation. Here, we report a metastatic renal pelvis urothelial carcinoma patient with PD-L1 negative expression that responded dramatically to first-line pembrolizumab plus lenvatinib. By the recent follow-up in March 2022, the patient had a complete radiological response for 3.4 years, with no recurrence even during the 23-month drug-withdrawal period. The results of the next-generation sequencing using the tumor sample revealed a high tumor mutational burden (TMB), which may be independently driven by the pathogenic mutation in TP53 , TERT , NCOR1 , and TSC2 genes. Besides, the tumor microenvironment exhibited an immune-active signature with relatively abundant CD8+ cells and M1 tumor-associated macrophages but scarce regulatory T cells may also explain the great benefit of the combination therapy. Our case provides a direction for identifying biomarkers beyond PD-L1 expression to screen urothelial carcinoma patients who benefit from ICI as well as ICI-based therapy.

Identification of a novel defined inflammation-related long noncoding RNA signature contributes to predicting prognosis and distinction between the cold and hot tumors in bladder cancer

Purpose

Bladder cancer (BLCA) is one of the most frequently diagnosed urological malignancies and is the 4th most common cancer in men worldwide. Molecular targets expressed in bladder cancer (BLCA) are usually used for developing targeted drug treatments. However, poor prognosis and poor immunotherapy efficacy remain major challenges for BLCA. Numerous studies have shown that long non-coding RNAs (LncRNAs) play an important role in the development of cancer. However, the role of lncRNAs related to inflammation in BLCA and their prognostic value remain unclear. Therefore, this study is aimed to explore new potential biomarkers that can predict cancer prognosis.

Methods

We downloaded BLCA-related RNA sequencing data from The Cancer Genome Atlas (TCGA) and searched for inflammation-related prognostic long non-coding RNAs (lncRNAs) by univariate Cox (uniCox) regression and co-expression analysis. We used the least absolute shrinkage and selection operator (LASSO) analysis to construct an inflammation-related lncRNA prognosis risk model. Samples were divided into high-risk score (HRS) group and low-risk score (LRS) group based on the median value of risk scores. The independent variable factors were identified by univariate Cox (uni-Cox) and multivariate Cox (multi-Cox) regression analyses, and receiver operating characteristic (ROC) curves were used to compare the role of different factors in predicting outcomes. Nomogram and Calibration Plot were generated by the R package rms to analyze whether the prediction results are correct and show good consistency. Correlation coefficients were calculated by Pearson analysis. The Kaplan-Meier method was used to assess the prognostic value. The expression of 7 lncRNAs related with inflammation was also confirmed by qRT-PCR in BLCA cell lines. Kyoto Encyclopedia of Gene and Genome (KEGG) pathways that were significantly enriched (P &lt; 0.05) in each risk group were identified by the GSEA software. The R package pRRophetic was used to predict the IC50 of common chemotherapeutic agents. TIMER, XCELL, QUANTISEQ, MCPCOUNTER, EPIC and CIBERSORT were applied to quantify the relative proportions of infiltrating immune cells. We also used package ggpubr to evaluate TME scores and immune checkpoint activation in LRS and HRS populations. R package GSEABase was used to analyze the activity of immune cells or immune function. Different clusters of principal component analysis (PCA), t-distribution random neighborhood embedding (t-SNE), and Kaplan-Meier survival were analyzed using R package Rtsne’s. The R package ConsensesClusterPlus was used to class the inflammation-related lncRNAs.

Results

In this study, a model containing 7 inflammation-related lncRNAs was constructed. The calibration plot of the model was consistent with the prognosis prediction outcomes. The 1-, 3-, and 5-year ROC curve (AUC) were 0.699, 0.689, and 0.699, respectively. High-risk patients were enriched in lncRNAs related with tumor invasion and immunity, and had higher levels of immune cell infiltration and immune checkpoint activation. Hot tumors and cold tumors were effectively distinguished by clusters 2 and 3 and cluster 1, respectively, which indicated that hot tumors are more susceptible to immunotherapy.

Conclusion

Our study showed that inflammation-related LncRNAs are closely related with BLCA, and inflammation-related lncRNA can accurately predict patient prognosis and effectively differentiate between hot and cold tumors, thus improving individualized immunotherapy for BLCA patients. Therefore, this study provides an effective predictive model and a new therapeutic target for the prognosis and clinical treatment of BLCA, thus facilitating the development of individualized tumor therapy.

Adverse reactions associated with immune checkpoint inhibitors and bevacizumab: A pharmacovigilance analysis

Immune checkpoint inhibitors (ICIs) combined with the anti-angiogenesis drug bevacizumab is one of the future directions of immunotherapy. However, the potential adverse drug reactions (ADRs) caused by combination therapy remain unclear. Current research on ADRs of combination therapy in cancer patients is extremely limited. Our study aims to help determine the safety of combination therapy. We downloaded the ADR reports on combination therapy, from the first quarter of 2012 to the fourth quarter of 2021, from the FDA adverse event reporting system (FAERS) database and conducted a large-scale retrospective study. The ADR signals were monitored by reporting odds ratio (ROR) and analyzing the risk of different ADRs in patients with Pan-cancer. A total of 2094 cases were selected, after excluding duplicate data and the use of chemotherapy drugs. We evaluated the risk of ADR in Pan-cancer patients. Combination therapy was an independent risk factor for adverse drug reactions associated with interstitial lung disease (OR: 8.62; 95% CI: 6.14-12.10, P < .0001), hypertension (OR: 1.35; 95% CI: 1.11-1.65, P < .01) and gastrointestinal bleeding (OR: 3.16; 95% CI: 2.21-4.51, P < .0001). A subgroup analysis revealed that the risk of endocrine system-related ADRs was elevated in patients receiving different combination therapies or with certain tumor types. We retrospectively studied the ADR of combination therapy in Pan-cancer patients and analyzed the distribution characteristics of ADR from the perspectives of treatment strategy and cancer types to provide recommendations for the individualized management of patients receiving combination therapy.

MYCBP2 expression correlated with inflammatory cell infiltration and prognosis immunotherapy in thyroid cancer patients

Introduction

Immune checkpoint inhibitors (ICIs) have shown promising results for the treatment of multiple cancers. ICIs and related therapies may also be useful for the treatment of thyroid cancer (TC). In TC, Myc binding protein 2 (MYCBP2) is correlated with inflammatory cell infiltration and cancer prognosis. However, the relationship between MYCBP2 expression and ICI efficacy in TC patients is unclear.

Methods

We downloaded data from two TC cohorts, including transcriptomic data and clinical prognosis data. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to predict the efficacy of ICIs in TC patients. MCPcounter, xCell, and quanTIseq were used to calculate immune cell infiltration scores. Gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA) were used to evaluate signaling pathway scores. Immunohistochemical (IHC) analysis and clinical follow up was used to identify the MYCBP2 protein expression status in patients and associated with clinical outcome.

Results

A higher proportion of MYCBP2-high TC patients were predicted ICI responders than MYCBP2-low patients. MYCBP2-high patients also had significantly increased infiltration of CD8+ T cells, cytotoxic lymphocytes (CTLs), B cells, natural killer (NK) cells and dendritic cells (DC)s. Compared with MYCBP2-low patients, MYCBP2-high patients had higher expression of genes associated with B cells, CD8+ T cells, macrophages, plasmacytoid dendritic cells (pDCs), antigen processing and presentation, inflammatory stimulation, and interferon (IFN) responses. GSEA and ssGSEA also showed that MYCBP2-high patients had significantly increased activity of inflammatory factors and signaling pathways associated with immune responses.In addiation, Patients in our local cohort with high MYCBP2 expression always had a better prognosis and greater sensitivity to therapy while compared to patients with low MYCBP2 expression after six months clinic follow up.

Conclusions

In this study, we found that MYCBP2 may be a predictive biomarker for ICI efficacy in TC patients. High MYCBP2 expression was associated with significantly enriched immune cell infiltration. MYCBP2 may also be involved in the regulation of signaling pathways associated with anti-tumor immune responses or the production of inflammatory factors.

Analysis of prognostic oncogene filaggrin (FLG) wild-type subtype and its implications for immune checkpoint blockade therapy in bladder urothelial carcinoma

BACKGROUND

Bladder urothelial carcinoma (BLCA) is one of the most common urinary tract malignant tumors. Immune checkpoint blockade (ICB) therapy has significantly progressed the treatment of BLCA. This study aimed to investigate the role of specific genetic mutations that may serve as immune biomarkers for ICB therapy in BLCA.

METHODS

Mutation information and expression profiles were acquired from The Cancer Genome Atlas (TCGA) database. Integrated bioinformatics analysis was carried out to explore the subtypes with poor prognosis of BLCA. Functional enrichment analysis was also conducted. The infiltrating immune cells and the prediction of ICB response between different subtypes were explored using the immuCellAI algorithm. Cell Counting Kit-8 (CCK-8) and flow cytometry assays were conducted to explore the effect of filaggrin (FLG) knockdown in BLCA 5637 and T24 cell lines.

RESULTS

An overview of mutation information in BLCA patients was shown. FLG was identified to be strongly associated with the prognosis of BLCA patients and FLG wild-type was associated with poorer outcome. Prognostic FLG wild-type was divided into 2 subtypes (Sub1 and Sub2). Following an investigation of the subtypes, Sub2 of FLG wild-type was found to be associated with poorer outcome in BLCA. The differentially expressed genes (DEGs) between Sub1 and Sub2 were screened out and the DEGs were enriched in malignant tumor proliferation, DNA damage repair, and immune-related pathways. Furthermore, Sub2 of FLG wild-type was associated with infiltrated immune cells, and responded worse to ICB. Sub2 of FLG wild-type may be used as a biomarker to predict the prognosis of BLCA patients receiving ICB. The cellular experiments revealed that knockdown of FLG could suppress BLCA cell proliferation and promote apoptosis.

CONCLUSIONS

FLG is an oncogene that may affect the prognosis of BLCA patients through mutation. Sub2 of FLG wild-type is associated with poor prognosis and can be used to predict ICB response for BLCA treatment. This research provides a new basis and ideas for guiding the clinical application of BLCA immunotherapy.

Comprehensive germline and somatic genomic profiles of Chinese patients with biliary tract cancer

Background

Biliary tract cancer (BTC) is an uncommon but highly lethal malignancy with poor clinical outcomes. To promote the development of precision medicine for BTC, uncovering its genomic profile becomes particularly important. However, studies on the genomic feature of Chinese BTC patients remain insufficient.

Methods

A total of 382 Chinese patients with BTC were enrolled in this study, including 71 with intrahepatic cholangiocarcinoma (ICC), 194 with extrahepatic cholangiocarcinoma (ECC), and 117 with gallbladder carcinoma (GBC). Genetic testing was performed by utilizing the next-generation sequencing (NGS) of 499 cancer-related genes and the results were compared to those of Western BTC patients (MSKCC cohorts).

Results

The most prevalent genes were TP53 (51.6%), ARID1A (25.9%), KMT2C (24.6%), NCOR1 (17%), SMAD4 (15.2%), KRAS (14.9%), KMT2D (14.9%), ATM (14.1%), and APC (13.9%) in Chinese BTC patients. TP53, SMAD4, and APC were more prevalent in GBC, ECC, and ICC, respectively. In addition, 10.5% of Chinese BTC patients harbored pathogenic or likely pathogenic (P/LP) germline alterations in 41 genes, which were mainly related to DNA damage repair (DDR). Additionally, the genomic features of Chinese and Western BTC tumors were similar, with the exception of the notable difference in the prevalence of TP53, KRAS, IDH1, KMT2C, and SMAD4. Notably, Chinese BTC patients had high prevalence (57.1%) of actionable alterations, especially for those with ECC, and half (192/382) of them had somatic DDR alterations, with the prevalence of deleterious ones being significantly higher than their Western counterparts. Twenty-three percent of patients had a higher tumor mutational burden (TMB-H, over 10 mutations/MB), and TMB was significantly higher in those with deleterious DDR alterations and/or microsatellite instability-high. The most common mutational signature in BTC patients was Signature 1, and interestingly, Signatures 1, 4, and 26 were significantly associated with higher TMB level, but not with the survival of patients who had received immunotherapy in pan-cancer.

Conclusion

Our study elaborated the distinct germline and somatic genomic characteristics of Chinese BTC patients and identified clinically actionable alterations, highlighting the possibility for the development and application of precision medicine.

Activation of the chemokine receptor 3 pathway leads to a better response to immune checkpoint inhibitors in patients with metastatic urothelial carcinoma

Immune checkpoint inhibitors (ICIs) have made important breakthrough in anti-tumor therapy, however, no single biomarker can accurately predict their efficacy. Studies have found that tumor microenvironment is a key factor for determining the response to ICI therapy. Cytokine receptor 3 (C-X-C Motif Chemokine Receptor 3, CXCR3) pathway has been reported to play an important role in the migration, activation, and response of immune cells. We analyzed survival data, genomics, and clinical data from patients with metastatic urothelial carcinoma (mUC) who received ICI treatment to explore the relationship between CXCR3 pathway activation and the effectiveness of ICIs. The Cancer Genome Atlas Bladder Urothelial Carcinoma cohort and six other cohorts receiving ICI treatment were used for mechanism exploration and validation. In the ICI cohort, we performed univariate and multivariate COX analyses and discovered that patients in the CXCR3-high group were more sensitive to ICI treatment. A Kaplan–Meier analysis demonstrated that patients in the high CXCR3-high group had a better prognosis than those in the CXCR3-low group (P = 0.0001, Hazard Ratio = 0.56; 95% CI 0.42−0.75). CIBERSORT analysis found that mUC patients in the CXCR3-high group had higher levels of activated CD8+ T cells, M1 macrophages, and activated NK cells and less regulatory T cell (Treg) infiltration. Immunogenicity analysis showed the CXCR3-high group had higher tumor neoantigen burden (TNB). Our study suggests that CXCR3 pathway activation may be a novel predictive biomarker for the effectiveness of immunotherapy in mUC patients.

TCR Coexpression Signature Predicts Immunotherapy Resistance in NSCLC

Background: Lung cancer has the highest morbidity and mortality rate among types of malignant tumors, and as such, research into prolonging the survival time of patients is vital. The emergence of immune checkpoint inhibitors (ICIs) has greatly improved the survival of patients with non-small cell lung cancer (NSCLC), however, the lack of effective biomarkers to predict the prognosis of immunotherapy has made it difficult to maximize the benefits. T cell receptor (TCR) is one of the most important components for recognizing tumor cells, and with this study we aim to clarify the relationship between TCR coexpression and the prognosis of NSCLC patients receiving immunotherapy.

Methods: Univariate COX regression, logistics regression, and KM survival analysis were used to evaluate the relationship between TCR coexpression and the prognosis of immunotherapy. Additionally, CIBERSORT, Gene Set Enrichment Analysis (GSEA), and single-sample GSEA (ssGSEA) algorithms were used to evaluate the tumor immune microenvironment (TIME) of NSCLC patients.

Results: Univariate Cox regression analysis showed that the TCR coexpression signature can be used as a clinical prognostic indicator for NSCLC patients receiving immunotherapy (p = 0.0205). In addition, those in the NSCLC group with a high TCR coexpression signature had significantly improved progression-free survival (PFS) (p = 0.014). In the ICI treatment cohort (GSE35640). In addition, there was a high infiltration of CD8+T cells, activated memory CD4+T cells, and M1 macrophages in the TIME of those with a high TCR coexpression signature. The results of pathway enrichment analysis showed that patients with a high TCR coexpression signature had significantly activated signal pathways such as lymphocyte proliferation and activation, chemokine binding, and inflammatory cytokine production. Also, we found that patients with a high TCR coexpression signature had an elevated T cell inflammation gene expression profile (GEP).

Conclusion: We show that the TCR coexpression signature may be useful as a new biomarker for the prognosis of NSCLC patients undergoing immunotherapy, with high signatures indicating better treatment response. Additionally, we found that patients with a high TCR coexpression signature had tumor immune microenvironments with beneficial anti-tumor characteristics.

CAMOIP: a web server for comprehensive analysis on multi-omics of immunotherapy in pan-cancer

Immune checkpoint inhibitors (ICIs) have completely changed the approach pertaining to tumor diagnostics and treatment. Similarly, immunotherapy has also provided much needed data about mutation, expression and prognosis, affording an unprecedented opportunity for discovering candidate drug targets and screening for immunotherapy-relevant biomarkers. Although existing web tools enable biologists to analyze the expression, mutation and prognostic data of tumors, they are currently unable to facilitate data mining and mechanism analyses specifically related to immunotherapy. Thus, we effectively developed our own web-based tool, called Comprehensive Analysis on Multi-Omics of Immunotherapy in Pan-cancer (CAMOIP), in which we are able to successfully screen various prognostic markers and analyze the mechanisms involved in biomarker expression and function, as well as immunotherapy. The analyses include information relevant to survival analysis, expression analysis, mutational landscape analysis, immune infiltration analysis, immunogenicity analysis and pathway enrichment analysis. This comprehensive analysis of biomarkers for immunotherapy can be carried out by a click of CAMOIP, and the software should greatly encourage the further development of immunotherapy. CAMOIP provides invaluable evidence that bridges the information between the data of cancer genomics based on immunotherapy, providing comprehensive information to users and assisting in making the value of current ICI-treated data available to all users. CAMOIP is available at https://www.camoip.net.

MMP9 Expression Correlates With Cisplatin Resistance in Small Cell Lung Cancer Patients

Background: Cisplatin is the basis of the primary treatment for SCLC chemotherapy. However, the limited objective response rate and definite drug resistance greatly restrict the clinical potential and therapeutic benefits of cisplatin use. Therefore, it is essential to identify biomarkers that can discern the sensitivity of SCLC patients to cisplatin treatment.

Methods: We collected two SCLC cohorts treated with cisplatin that included mutation data, prognosis data and expression data. The sensitivity of cisplatin was evaluated by the pRRophetic algorithm. MCPcounter, quanTIseq, and xCell algorithms were used to evaluate immune cell score. GSEA and ssGSEA algorithms were used to calculate immune-related pathway scores. Univariate and multivariate Cox regression models were employed, and survival analysis was used to evaluate the prognostic value of the candidate genes.

Results: MMP9-High is related to improved clinical prognoses of patients with SCLC (HR = 0.425, p = 0.0085; HR = 0.365, p = 0.0219). Multivariate results showed that MMP-High could be used as an independent predictor of the prognosis of SCLC after cisplatin treatment (HR = 0.216, p = 0.00153; HR = 0.352; p = 0.0199). In addition, MMP9-High displayed a significantly lower IC50 value of cisplatin and higher immunogenicity than MMP9-Low SCLC. Compared with MMP9-Low SCLC, MMP9-High included significantly increased levels of T-cells, cytoxic lymphocytes, B-cells, NK-cells, and dense cells (DCS). Similarly, the activity of cytokine binding, B-cell, NK-cell mediated immune response chemokine binding, and antigen presentation pathways in MMP9-High was significantly higher than that in MMP9-Low.

Conclusion: In this study, we identified that MMP9-High could be potentially considered a novel biomarker used to ascertain the improved prognosis of SCLC patients after cisplatin treatment. Furthermore, we indicated that the tumor immune microenvironment of MMP9-High SCLC is mainly characterized by a large number of infiltrated activated immune cells as well as activated immune-related pathways.

Case Report: Complete Remission With Anti-PD-1 and Anti-VEGF Combined Therapy of a Patient With Metastatic Primary Splenic Angiosarcoma

Primary splenic angiosarcoma (PSA) is a rare malignancy with poor prognosis. At present, little study is available on immunotherapy in PSA. Here, we report a case of a patient with metastatic PSA who was treated with programmed death-1 (PD-1) inhibitors and vascular endothelial growth factor (VEGF) tyrosine kinase inhibitors combined therapy and achieved complete response (CR). The patient was a 57−year−old woman with three liver metastases. She was treated with seven cycles of toripalimab plus anlotinib. Programmed death-ligand 1 (PD-L1) immunohistochemistry and next-generation sequencing was performed, and the PD-L1 tumor proportion score was 75%. Finally, she achieved CR after six cycles of the combined therapy regimen. No serious adverse events were detected. To the best of our knowledge, this is the first clinical evidence that anti-PD-1 plus anti-VEGF therapy might be a promising option for patients with metastatic PSA. However, more clinical trials are needed to verify this conclusion.

Immunological Classification of Tumor Types and Advances in Precision Combination Immunotherapy

Immunity is an important physiological function acquired throughout evolution as a defense system against the invasion of pathogenic microorganisms. The immune system also eliminates senescent cells and maintains homeostasis, monitoring cell mutations and preventing tumor development via the action of the immune cells and molecules. Immunotherapy often relies on the interaction of immune cells with the tumor microenvironment (TME). Based on the distribution of the number of lymphocytes (CD3 and CD8) in the center and edge of the tumor and the expression level of B7-H1/PD-L1, tumors are divided into hot tumors, cold tumors, and intermediate tumors (including immune-suppressed and isolated). This review focuses on the advances in precision combination immunotherapy, which has been widely explored in recent years, and its application in different tumor types.

Comprehensive Analysis of the Immune Microenvironment in Checkpoint Inhibitor Pneumonitis

Background

While immune checkpoint inhibitors (ICIs) are a beacon of hope for non-small cell lung cancer (NSCLC) patients, they can also cause adverse events, including checkpoint inhibitor pneumonitis (CIP). Research shows that the inflammatory immune microenvironment plays a vital role in the development of CIP. However, the role of the immune microenvironment (IME) in CIP is still unclear.

Methods

We collected a cohort of NSCLC patients treated with ICIs that included eight individuals with CIP (CIP group) and 29 individuals without CIP (Control group). CIBERSORT and the xCell algorithm were used to evaluate the proportion of immune cells. Gene set enrichment analysis (GSEA) and single-sample GSEA (ssGSEA) were used to evaluate pathway activity. The ridge regression algorithm was used to analyze drug sensitivity.

Results

CIBERSORT showed significantly upregulated memory B cells, CD8+ T cells, and M1 Macrophages in the CIP group. The number of memory resting CD4+ T cells and resting NK cells in the CIP group was also significantly lower than in the Control group. The XCell analysis showed a higher proportion of Class-switched memory B-cells and M1 Macrophages in the CIP group. Pathway analysis showed that the CIP group had high activity in their immune and inflammatory response pathways and low activity in their immune exhaustion related pathway.

Conclusions

In this study, we researched CIP patients who after ICIs treatment developed an inflammatory IME, which is characterized by significantly increased activated immune cells and expression of inflammatory molecules, as well as downregulated immunosuppressive lymphocytes and signaling pathways. The goal was to develop theoretical guidance for clinical guidelines for the treatment of CIP in the future.

Molecular mechanisms governing circulating immune cell heterogeneity across different species revealed by single-cell sequencing

BACKGROUND

Immune cells play important roles in mediating immune response and host defense against invading pathogens. However, insights into the molecular mechanisms governing circulating immune cell diversity among multiple species are limited.

METHODS

In this study, we compared the single-cell transcriptomes of immune cells from 12 species. Distinct molecular profiles were characterized for different immune cell types, including T cells, B cells, natural killer cells, monocytes, and dendritic cells.

RESULTS

Our data revealed the heterogeneity and compositions of circulating immune cells among 12 different species. Additionally, we explored the conserved and divergent cellular crosstalks and genetic regulatory networks among vertebrate immune cells. Notably, the ligand and receptor pair VIM-CD44 was highly conserved among the immune cells.

CONCLUSIONS

This study is the first to provide a comprehensive analysis of the cross-species single-cell transcriptome atlas for peripheral blood mononuclear cells (PBMCs). This research should advance our understanding of the cellular taxonomy and fundamental functions of PBMCs, with important implications in evolutionary biology, developmental biology, and immune system disorders.

CTNNB1 Alternation Is a Potential Biomarker for Immunotherapy Prognosis in Patients With Hepatocellular Carcinoma

Background

The emergence of immune checkpoint inhibitors (ICIs) marks the beginning of a new era of immunotherapy for hepatocellular carcinoma (HCC), however, not all patients respond successfully to this treatment. A major challenge for HCC immunotherapy is the development of ways to screen for those patients that would benefit from this type of treatment and determine the optimal treatment plan for individual patients. Therefore, it is important to find a biomarker which allows for the stratification of HCC patients, which distinguishes responders from non-responders, thereby further improving the clinical benefits for those undergoing immunotherapy.

Methods

We used univariate and multivariate Cox risk proportional regression models to evaluate the relationship between non-synonymous mutations with a mutation frequency greater than 10%. We made a prognosis of an immunotherapy HCC cohort using mutation and prognosis data. An additional three HCC queues from the cbioportal webtool were used for further verification. The CIBERSORT, IPS, quanTIseq, and MCPcounter algorithms were used to evaluate the immune cells. PCA and z-score algorithm were used to calculate immune-related signature with published gene sets. Gene set enrichment analysis (GSEA) was used to compare the differences in the pathway-based enrichment scores of candidate genes between mutant and wild types.

Results

Univariate and multivariate Cox results showed that only CTNNB1-Mutant(CTNNB1-MUT) was associated with progression-free survival (PFS) of HCC patients in the immunotherapy cohort. After excluding the potential bias introduced by other clinical features, it was found that CTNNB1-MUT served as an independent predictor of the prognosis of HCC patients after immunotherapy (P < 0.05; HR > 1). The results of the tumor immune microenvironment (TIME) analysis showed that patients with CTNNB1-MUT had significantly reduced activated immune cells [such as T cells, B cells, M1-type macrophages, and dendritic cells (DCs)], significantly increased M2-type macrophages, a significantly decreased expression of immunostimulating molecules, low activity of the immune activation pathways (cytokine pathway, immune cell activation and recruitment) and highly active immune depletion pathways (fatty acid metabolism, cholesterol metabolism, and Wnt pathway).

Conclusions

In this study, we found CTNNB1-MUT to be a potential biomarker for HCC immunotherapy patients, because it identified those patients are less likely to benefit from ICIs.

TNF-Alpha Pathway Alternation Predicts Survival of Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer

Translational research on immune checkpoint inhibitors (ICIs) has been underway. However, in the unselected population, only a few patients benefit from ICIs. Therefore, screening predictive markers of ICI efficacy has become the current focus of attention. We collected mutation and clinical data from an ICI-treated non-small cell lung cancer (NSCLC) cohort. Then, a univariate Cox regression model was used to analyze the relationship between tumor necrosis factor α signaling mutated (TNFα-MT) and the prognosis of immunotherapy for NSCLC. We retrospectively collected 36 NSCLC patients (local-cohort) from the Zhujiang Hospital of Southern Medical University and performed whole-exome sequencing (WES). The expression and mutation data of The Cancer Genome Atlas (TCGA)-NSCLC cohort were used to explore the association between TNFα-MT and the immune microenvironment. A local cohort was used to validate the association between TNFα-MT and immunogenicity. TNFα-MT was associated with significantly prolonged overall survival (OS) in NSCLC patients after receiving immunotherapy. Additionally, TNFα-MT is related to high immunogenicity (tumor mutational burden, neoantigen load, and DNA damage response signaling mutations) and enrichment of infiltrating immune cells. These results suggest that TNFα-MT may serve as a potential clinical biomarker for NSCLC patients receiving ICIs.

Effect of TTN Mutations on Immune Microenvironment and Efficacy of Immunotherapy in Lung Adenocarcinoma Patients

Immune checkpoint inhibitors (ICIs) effectively treat lung adenocarcinoma (LUAD) with fewer side effects. However, for LUAD patients, the lack of predictive markers for ICIs makes their clinical benefits less than ideal. Despite reports suggesting that a TTN (titin) mutation plays an important role in immunotherapy of solid tumors and gastric cancer, the relationship between the TTN mutation and LUAD immunotherapy has not been determined. We collected a LUAD cohort with whole-exome sequencing (WES) and immunotherapy prognosis. The ICI cohort was used to explore the relationship between TTN mutation status and prognosis. Then, the Cancer Genome Atlas (TCGA)-LUAD and Chen-LUAD cohorts were downloaded from the cbioportal website. We also used CIBERSORT, gene-set enrichment analysis (GSEA), and single-sample GSEA (ssGSEA) to evaluate the proportion of immune cells and the degree of pathway activation in LUAD patients, respectively. DDR signaling pathways obtained from the Molecular Signatures Database (MSigDB), tumor mutation burden (TMB), and NAL were used to evaluate the immunogenicity of LUAD patients. In the ICI cohort, TTN-mutant (TTN-MT) had significantly longer overall survival (OS) than TTN-wildtype (TTN-WT) (P = 0.009). Univariate and multivariate COX models showed that TTN mutation status can independently predict immunotherapy prognosis. Notably, the results of tumor immune microenvironment (TIME) analysis showed that TTN-MT patients had inflammatory TIME, which showed enriched activated immune cells and higher immune scores. Immunogenicity analysis showed higher immunogenicity in TTN-MT patients, which indicated high levels of gene mutations in TMB, NAL, and DDR pathways. GSEA and ssGSEA results showed that TTN-MT was substantially enriched in chemokine secretion, inflammatory factor secretion, and antigen presentation. Some pathways related to immunosuppression and immune depletion were significantly downregulated. TTN-MT is associated with significantly prolonged OS in LUAD patients. Additionally, TTN-MT is related to high immunogenicity and inflammatory TIME, suggesting that TTN-MT may be a potential predictive marker for patients with LUAD to accept ICIs.