A comprehensive pan-cancer analysis of prognostic value and potential clinical implications of FTH1 in cancer immunotherapy.

BACKGROUND: Numerous studies have highlighted the crucial value of the heavy chain of ferritin (FTH1) as a key regulator of iron metabolism and a suppressor of ferroptosis, intimately tied to the tumor immune microenvironment (TIME). Nevertheless, the precise impact of FTH1 on cancer immunotherapy remains vague. Our study aims to systematically explore the prognostic significance and immune role of FTH1 in pan-cancers immunotherapy. METHODS: Our study delves into the potential of FTH1 as an immunotherapeutic target within the TIME of various solid cancers. The immune landscape and underlying mechanisms of FTH1 in the TIME were investigated by multiple algorithms and bioinformatics methods. Single-cell sequencing analysis and multiplex immunofluorescence staining techniques are applied to observe FTH1 co-expression on both tumor and immune cells. RESULTS: FTH1 exhibited aberrant expression patterns across multiple cancers, which is strongly correlated with immunotherapy resistance. Patients with high FTH1 expression levels tended to derive less benefit from immunotherapies. Moreover, FTH1 demonstrated a significant correlation with TIME infiltration, immune checkpoint molecules, and immune-related pathways. Notably, FTH1 showed a positive association with macrophage infiltrations, its expression was particularly noteworthy in malignant cells and macrophages. Inhibiting FTH1-related signaling pathways appeared to be a potential strategy to counteract tumor immunotherapy resistance. CONCLUSION: Our comprehensive analyses may offer valuable insights into the role of FTH1 in tumor immunotherapy. The observed correlations pave the way for further functional experiments, fostering an enhanced understanding that could shape future research endeavors.

Making the Best Use of Available Weapons for the Inevitable Rivalry-Resistance to EGFR-TKIs.

The emergence of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) revolutionized the treatment of advanced-stage non-small cell lung cancer (NSCLC). Detected in more than 50% of late-stage lung adenocarcinoma in Asian patients, the EGFR mutation was regarded as a golden mutation for Asians. However, resistance to TKIs seems inevitable and severely hinders patients from getting further benefits from treatment. Even though resistance caused by EGFR T790M could be effectively managed by third-generation EGFR-TKIs currently, resistance to third-generation EGFR-TKIs is still a troublesome issue faced by both clinicians and patients. Various efforts have been made to maximize the benefits of patients from EGFR-TKIs therapy. Thus, new requirements and challenges have been posed to clinicians of this era. In this review, we summarized the clinical evidence on the efficacy of third-generation EGFR-TKIs in patients with EGFR-mutated NSCLC. Then, we discussed advancements in sequential treatment aiming to delay the onset of resistance. Moreover, the resistance mechanisms and features were depicted to help us better understand our enemies. Lastly, we put forward future strategies, including recent approaches involving the utilization of antibody drug conjugates against resistance and research directions about shaping the evolution of NSCLC as a core idea in the management of NSCLC.

Profile of treatment-related adverse events of PD-1 blockade-based therapies in advanced esophageal cancer: A systematic review and meta-analysis.

PD-1 blockade-based therapies are the most promising treatment for advanced esophageal cancer (EC). It is crucial to investigate the corresponding toxicity profiles of treatment-related adverse events (TRAEs). We conducted a systematic review and meta-analysis to explore toxicity profiles across different PD-1 blockade-based treatments in EC. A total of 5595 patients from 10 clinical trials were included. The overall rates of TRAEs were 88 % (95 % CI 72.0-95.0), 98.0 % (97.0-99.0), and 79.5 % (74.6-83.7) for all grade TRAEs, 24.0 % (15.0-36.0), 64.0 % (56.0-71.0), and 34.2 % (29.1-39.7) for grade 3 or higher TRAEs in PD-1 blockade alone, PD-1 blockade plus chemotherapy, and dual blockade group, respectively. Compared to chemotherapy, RRs for patients receiving PD-1 blockade-based treatments for all grade TRAEs were 0.96 (93.0-100.0) and 0.75 (60.0-94.0) for grade 3 or higher TRAEs. We exhibited comprehensive statistics on the toxicity of the PD-1 blockade-based regimens, providing useful references for clinicians.

Costimulatory molecule expression profile as a biomarker to predict prognosis and chemotherapy response for patients with small cell lung cancer.

Owing to the paucity of specimens, progress in identifying prognostic and therapeutic biomarkers for small cell lung cancer (SCLC) has been stagnant for decades. Considering that the costimulatory molecules are essential elements in modulating immune responses and determining therapeutic response, we systematically revealed the expression landscape and identified a costimulatory molecule-based signature (CMS) to predict prognosis and chemotherapy response for SCLCs for the first time. We found T cell activation was restrained in SCLCs, and costimulatory molecules exhibited widespread abnormal genetic alterations and expression. Using a LASSO Cox regression model, the CMS was built with a training cohort of 77 cases, which successfully divided patients into high- or low-risk groups with significantly different prognosis and chemotherapy benefit (both P < 0.001). The CMS was well validated in an independent cohort containing 131 samples with qPCR data. ROC and C-index analysis confirmed the superior predictive performance of the CMS in comparison with other clinicopathological parameters from different cohorts. Importantly, the CMS was confirmed as a significantly independent prognosticator for clinical outcomes and chemotherapy response in SCLCs through multivariate Cox analysis. Further analysis revealed that low-risk patients were characteristic by an activated immune phenotype with distinct expression of immune checkpoints. In summary, we firstly uncovered the expression heterogeneity of costimulatory molecules in SCLC and successfully constructed a novel predictive CMS. The identified signature contributed to more accurate patient stratification and provided robust prognostic value in estimating survival and the clinical response to chemotherapy, allowing optimization of treatment and prognosis management for patients with SCLC.

Comprehensive analyses of N6 -methyladenosine-related long noncoding RNA profiles with prognosis, chemotherapy response, and immune landscape in small cell lung cancer.

Small cell lung cancer (SCLC) is the most devastating subtype of lung cancer with no clinically available prognostic biomarkers. N6 -methyladenosine (m6 A) and noncoding RNAs play critical roles in cancer development and treatment response. However, little is known about m6 A-related long noncoding RNAs (lncRNAs) in SCLC. We used 206 limited-stage SCLC (LS-SCLC) samples from two cohorts to undertake the first and most comprehensive exploration of the m6 A-related lncRNA profile in SCLC and constructed a relevant prognostic signature. In total, 289 m6 A-related lncRNAs were screened out. We then built a seven-lncRNA-based signature in the training cohort with 48 RNA sequencing data using univariate and multivariate Cox regression models. The signature was well validated in an independent cohort containing 158 cases with quantitative PCR data. In both cohorts, the signature divided patients into high- and low-risk groups with significantly different survival rates (both p < 0.001). Our signature predicted chemotherapy survival benefit in patients with LS-SCLC. Receiver operating characteristic and C-index analyses indicated that the signature was better at predicting prognosis and chemotherapy benefit than other clinicopathologic features. Moreover, the signature was identified as an independent predictor of prognosis and chemotherapy response in different cohorts. Furthermore, functional analysis showed that multiple activated immune-related pathways were enriched in the low-risk group. Additionally, the signature was also closely related to various immune checkpoints and inflammatory responses. We generated the first clinically available m6 A-related lncRNA signature to predict prognosis and chemotherapy benefit in patients with LS-SCLC. Our findings could help optimize the clinical management of patients with LS-SCLC and inform future therapeutic targets for SCLC.

A novel immune checkpoints-based signature to predict prognosis and response to immunotherapy in lung adenocarcinoma.

BACKGROUND: Except for B7-CD28 family members, more novel immune checkpoints are being discovered. They are closely associated with tumor immune microenvironment and regulate the function of many immune cells. Various cancer therapeutic studies targeting these novel immune checkpoints are currently in full swing. However, studies concerning novel immune checkpoints phenotypes and clinical significance in lung adenocarcinoma (LUAD) are still limited. METHODS: We enrolled 1883 LUAD cases from nine different cohorts. The samples from The Cancer Genome Atlas (TCGA) were used as a training set, whereas seven microarray data cohorts and an independent cohort with 102 qPCR data were used for validation. The immune profiles and potential mechanism of the system were also explored. RESULTS: After univariate Cox proportional hazards regression and stepwise multivariable Cox analysis, a novel immune checkpoints-based system (LTA, CD160, and CD40LG) were identified from the training set, which significantly stratified patients into high- and low-risk groups with different survivals. Furthermore, this system has been well validated in different clinical subgroups and multiple validation cohorts. It also acted as an independent prognostic factor for patients with LAUD in different cohorts. Further exploration suggested that high-risk patients exhibited distinctive immune cells infiltration and suffered an immunosuppressive state. Additionally, this system is closely linked to various classical immunotherapy biomarkers. CONCLUSION: we constructed a novel immune checkpoints-based system for LUAD, which predicts prognosis and immunotherapeutic implications. We believe that these findings will not only aid in clinical management but will also shed some light on screening appropriate patients for immunotherapy.

The potential role of N7-methylguanosine (m7G) in cancer.

N7-methylguanosine (m7G), one of the most prevalent RNA modifications, has recently attracted significant attention. The m7G modification actively participates in biological and pathological functions by affecting the metabolism of various RNA molecules, including messenger RNA, ribosomal RNA, microRNA, and transfer RNA. Increasing evidence indicates a critical role for m7G in human disease development, especially cancer, and aberrant m7G levels are closely associated with tumorigenesis and progression via regulation of the expression of multiple oncogenes and tumor suppressor genes. Currently, the underlying molecular mechanisms of m7G modification in cancer are not comprehensively understood. Here, we review the current knowledge regarding the potential function of m7G modifications in cancer and discuss future m7G-related diagnostic and therapeutic strategies.

The combination of novel immune checkpoints HHLA2 and ICOSLG: A new system to predict survival and immune features in esophageal squamous cell carcinoma.

Studies on immune checkpoint inhibitors targeting B7-CD28 family pathways in esophageal squamous cell carcinoma (ESCC) have shown promising results. However, a comprehensive understanding of B7-CD28 family members in ESCC is still limited. This study aimed to construct a novel B7-CD28 family-based prognosis system to predict survival in patients with ESCC. We collected 179 cases from our previously published microarray data and 86 cases with qPCR data. Specifically, 119 microarray data (GSE53624) were used as a training set, whereas the remaining 60 microarray data (GSE53622), all 179 microarray data (GSE53625) and an independent cohort with 86 qPCR data were used for validation. The underlying mechanism and immune landscape of the system were also explored using bioinformatics and immunofluorescence. We examined 13 well-defined B7-CD28 family members and identified 2 genes (ICSOLG and HHLA2) with the greatest prognostic value. A system based on the combination HHLA2 and ICOSLG (B7-CD28 signature) was constructed to distinguish patients as high- or low-risk of an unfavorable outcome, which was further confirmed as an independent prognostic factor. As expected, the signature was well validated in the entire cohort and in the independent cohort, as well as in different clinical subgroups. The signature was found to be closely related to immune-specific biological processes and pathways. Additionally, high-risk group samples demonstrated high infiltration of Tregs and fibroblasts and distinctive immune checkpoint panels. Collectively, we built the first, practical B7-CD28 signature for ESCC that could independently identify high-risk patients. Such information may help inform immunotherapy-based treatment decisions for patients with ESCC.

Neoadjuvant chemoradiotherapy versus neoadjuvant chemotherapy for the treatment of esophageal squamous cell carcinoma: a propensity score-matched study from the National Cancer Center in China.

PURPOSE: The optimal mode of neoadjuvant treatment for esophageal squamous cell carcinoma (ESCC) has not been well characterized. Our study compared neoadjuvant chemotherapy (NCT) with neoadjuvant chemoradiotherapy (NCRT) for patients with ESCC. METHODS: Data from ESCC patients receiving NCRT or NCT combined with esophagectomy between 2010 and 2018 from the National Cancer Center in China were retrospectively collected. Long-term survival, pathological response, and perioperative mortality and morbidity were compared between the NCRT and NCT groups. A Cox proportional hazards model and propensity score matching (PSM) were used to minimize bias due to potential confounding. RESULTS: Out of 327 eligible patients with ESCC in our study, 90 patients were identified in each group by PSM. The complete pathologic response (pCR) rate in the NCRT group was markedly higher than that in the NCT group (before PSM: 35.1% vs. 6.0%; after PSM: 38.9% vs. 5.6%; both P < 0.001). The rates of 30-day or 90-day mortality were comparable between the two groups, but the NCRT group had a longer postoperative hospital stay (P < 0.001 before PSM and P = 0.012 after PSM) and more postoperative complications (P < 0.001 before PSM and P = 0.014 after PSM), especially, anastomotic leaks (P = 0.001 before PSM and P = 0.013 after PSM). No significant differences in 5-year overall survival (OS) (P = 0.439) or 5-year relapse-free survival (RFS) (P = 0.611) were noted between unmatched groups, but the trend favored NCRT in the propensity score-matched group (77.3% vs. 61.3%; hazard ratio [HR] 1.57; 95% confidence interval [CI] 0.86-2.87; P = 0.141 for OS, and 77.8% vs. 60.5%; HR 1.72; 95% CI 0.95-3.11; P = 0.073 for RFS). Multivariate analysis showed that only ypT and ypN stages were independent predictors of OS before and after PSM (both P < 0.05). CONCLUSION: There was no difference in survival between the NCT and NCRT groups, although a trend favored NCRT related to the significantly higher pCR rates. Prospective head-to-head clinical trials to compare these two types of neoadjuvant therapies in ESCC are warranted.

An immune-related lncRNA signature predicts prognosis and adjuvant chemotherapeutic response in patients with small-cell lung cancer.

BACKGROUND: Patients with small-cell lung cancer (SCLC) are burdened by limited treatment options and the disease's dismal prognosis. Long non-coding RNAs (lncRNAs) are essential regulators of genetic alteration and are actively involved in tumor immunity. However, few studies have examined interactions between immune genes and lncRNAs in SCLC. METHODS: Immune-related lncRNA (irlncRNA) expression profiles and their clinical significance were explored. We enrolled 227 patients with SCLC, including 79 cases from GSE65002 and 148 cases from a validation cohort with corresponding qPCR data. The least absolute shrinkage and selection operator (LASSO) model was applied to identify prognostic irlncRNAs for an irlncRNA-based SCLC signature. We additionally investigated the potential mechanisms and immune landscape of the signature using bioinformatics methods. RESULTS: An irlncRNA signature including 8 irlncRNAs (ENOX1-AS1, AC005162, LINC00092, RPL34-AS1, AC104135, AC015971, AC126544, AP001189) was established for patients with SCLC in the training cohort. Low-risk patients were more likely to benefit from chemotherapy and achieve a favorable prognosis. The signature was also well-validated in the validation cohort and various clinical subgroups. Compared to other clinical parameters, the irlncRNA signature exhibited superior predictive performance for chemotherapy response and prognosis. The signature was as an independent prognostic factor in the training and validation cohorts. Interestingly, low-risk patients showed an activated immune phenotype. CONCLUSION: We constructed the first irlncRNA-based signature for chemotherapy efficacy and outcome prediction. The irlncRNA signature is a reliable and robust prognostic classifier that could be useful for clinical management and determination of potential chemotherapy benefit for patients with SCLC.

Tumor Necrosis Factor Family Member Profile Predicts Prognosis and Adjuvant Chemotherapy Benefit for Patients With Small-Cell Lung Cancer.

Tumor necrosis factor (TNF) family members participate in the body's antitumor immunity response and influence tumor prognosis and treatment response. However, little is known about the roles of TNF family members in small cell lung cancer (SCLC). Therefore, we conducted the first comprehensive investigation of TNF family members in patients with SCLC, with the goal of using them to predict prognosis and chemotherapy benefit. Abnormal genetic alterations and expression of TNF family members were found to be widespread in SCLC patients. Using LASSO Cox regression analysis, we constructed a TNF family-based signature that separated SCLC patients in the training set (n=77) into high- and low-risk groups with distinct survival and chemotherapy benefit, and the signature was well-validated in the validation set (n=137) by RT-qPCR. Importantly, the signature exhibited superior predictive performance and was identified as a novel independent prognostic factor. Additionally, different immune phenotypes were found between the low-risk and high-risk groups, and high-risk patients had higher CMTM6 expression, suggesting that these patients could benefit from therapeutic methods targeting CMTM6. We constructed the first clinically applicable TNF family-based signature for predicting prognosis and chemotherapy benefit for patients with SCLC. The findings reported here provide a new method for predicting the prognosis of SCLC patients and optimizing clinical management.

m6A regulator expression profile predicts the prognosis, benefit of adjuvant chemotherapy, and response to anti-PD-1 immunotherapy in patients with small-cell lung cancer.

BACKGROUND: Small cell lung cancer (SCLC) is lethal and possesses limited therapeutic options. Platinum-based chemotherapy-with or without immune checkpoint inhibitors (anti-PDs)-is the current first-line therapy for SCLCs; however, its associated outcomes are heterogeneous. N6-methyladenosine (m6A) is a novel and decisive factor in tumour progression, chemotherapy resistance, and immunotherapy response. However, m6A modification in SCLC remains poorly understood. METHODS: We systematically explored the molecular features and clinical significance of m6A regulators in SCLC. We then constructed an m6A regulator-based prognostic signature (m6A score) based on our examination of 256 cases with limited-stage SCLC (LS-SCLC) from three different cohorts-including an independent cohort that contained 150 cases with qPCR data. We additionally evaluated the relationships between the m6A score and adjuvant chemotherapy (ACT) benefits and the patients' responses to anti-PD-1 treatment. Immunohistochemical (IHC) staining and the HALO digital pathological platform were used to calculate CD8+ T cell density. RESULTS: We observed abnormal somatic mutations and expressions of m6A regulators. Using the LASSO Cox model, a five-regulator-based (G3BP1, METTL5, ALKBH5, IGF2BP3, and RBM15B) m6A score was generated from the significant regulators to classify patients into high- and low-score groups. In the training cohort, patients with high scores had shorter overall survival (HR, 5.19; 2.75-9.77; P < 0.001). The prognostic accuracy of the m6A score was well validated in two independent cohorts (HR 4.6, P = 0.006 and HR 3.07, P < 0.001). Time-dependent ROC and C-index analyses found the m6A score to possess superior predictive power than other clinicopathological parameters. A multicentre multivariate analysis revealed the m6A score to be an independent prognostic indicator. Additionally, patients with low scores received a greater survival benefit from ACT, exhibited more CD8+ T cell infiltration, and were more responsive to cancer immunotherapy. CONCLUSIONS: Our results, for the first time, affirm the significance of m6A regulators in LS-SCLC. Our multicentre analysis found that the m6A score was a reliable prognostic tool for guiding chemotherapy and immunotherapy selections for patients with SCLC.

m6A regulators as predictive biomarkers for chemotherapy benefit and potential therapeutic targets for overcoming chemotherapy resistance in small-cell lung cancer.

Small-cell lung cancer (SCLC) is a devastating subtype of lung cancer with few therapeutic options. Despite the advent of immunotherapy, platinum-based chemotherapy is still the irreplaceable first-line therapy for SCLCs. However, drug resistance will invariably occur in most patients and the outcomes are heterogeneous. Therefore, clinically feasible classification strategies and potential therapeutic targets for overcoming chemotherapy resistance are urgently needed. N6-methyladenosine (m6A) is a novel epigenetic decisive factor that is involved in tumor progression and drug resistance. However, almost nothing is known about m6A modification in SCLC. Here, we assessed 200 SCLC samples from patients who underwent chemotherapy from three different cohorts, including a validation cohort containing 71 cases with qPCR data and an independent cohort containing 79 cases with immunohistochemistry data (quantified as H-score). We systematically characterized the predictive landscape of m6A regulators in SCLC patients following with chemotherapy. Using the LASSO Cox model, we built a seven-regulator-based (ZCCHC4, IGF2BP3, ALKBH5, YTHDF3, METTL5, G3BP1, and RBMX) chemotherapy benefit predictive classifier (m6A score) and subsequently validated the classifier in two other cohorts. Time-dependent ROC and C-index analyses showed that the m6A score to possessed superior predictive power for chemotherapy benefit in comparison with other clinicopathological parameters. A multicohort multivariate analysis revealed that the m6A score is an independent factor that affects survival benefit across multiple cohorts. Our in vitro experimental results revealed that three regulators-ZCCHC4, G3BP1, and RBMX-may serve as promising novel therapeutic targets for overcoming chemoresistance in SCLCs. Our results, for the first time, demonstrate the predictive significance of m6A regulators for chemotherapy benefit, as well as their potential as therapeutic targets for overcoming chemotherapy resistance in SCLC patients. The m6A score was found to be a reliable prognostic tool that may help guide chemotherapy decisions for patients with SCLC.

RNA N6 -methyladenosine modification in the lethal teamwork of cancer stem cells and the tumor immune microenvironment: Current landscape and therapeutic potential.

N6 -methyladenosine (m6 A), the newest and most prevalent layer of internal epigenetic modification in eukaryotic mRNA, has been demonstrated to play a critical role in cancer biology. Increasing evidence has highlighted that the interaction between cancer stem cells (CSCs) and the tumor immune microenvironment (TIME) is the root cause of tumorigenesis, metastasis, therapy resistance, and recurrence. In recent studies, the m6 A modification has been tightly linked to this CSC-TIME interplay, participating in the regulation of CSCs and TIME remolding. Interestingly, the m6 A modification has also been identified as a novel decisive factor in the efficacy of immunotherapies-particularly anti-PD-1/PD-L1 monotherapies-by changing the plasticity of the TIME. Given the functional importance of the m6 A modification in the crosstalk between CSCs and the TIME, targeting m6 A regulators will open new avenues to overcome therapeutic resistance, especially for immune checkpoint-based immunotherapy. In the present review, we summarize the current landscape of m6 A modifications in CSCs and the TIME, and also prospect the underling role of m6 A modifications at the crossroads of CSCs and the TIME for the first time. Additionally, to provide the possibility of modulating m6 A modifications as an emerging therapeutic strategy, we also explore the burgeoning inhibitors and technologies targeting m6 A regulators. Lastly, considering recent advances in m6 A-seq technologies and cancer drug development, we propose the future directions of m6 A modification in clinical applications, which may not only help to improve individualized monitoring and therapy but also provide enhanced and durable responses in patients with insensitive tumors.

The impact of emission trading schemes on firm competitiveness: Evidence of the mediating effects of firm behaviors from the guangdong ETS.

The pilot carbon emission trading scheme in Guangdong Province (GD ETS) of China has fulfilled seven compliance periods, and its potential impact on regulated firms has drawn increasing attention. This article empirically investigated the impact of the ETS on firm behaviors and competitiveness (i.e., cost competitiveness and green competitiveness) by surveying all power firms in the GD ETS. Low-carbon management, carbon asset transactions, and energy saving and emission reduction technology were identified as firm behaviors. The relationships among the ETS, firm behaviors, and firm competitiveness were tested by using bootstrap multiple mediation analyses. The results showed that the GD ETS has a positive impact on firm behaviors. The three examined firm behaviors actually reflect the depth of firm participation in the ETS. The more the firm participates, the greater the mediating effects that the firm behaviors exert on firm competitiveness are. Both carbon asset transactions and energy saving and emission reduction technology have a mediating effect on the relationship between the GD ETS and cost competitiveness, while only the latter mediates the relationship between the GD ETS and green competitiveness. Implications for policy makers and firm operators were discussed.

An individualized immune signature of pretreatment biopsies predicts pathological complete response to neoadjuvant chemoradiotherapy and outcomes in patients with esophageal squamous cell carcinoma.

No clinically available biomarkers can predict pathological complete response (pCR) for esophageal squamous cell carcinomas (ESCCs) with neoadjuvant chemoradiotherapy (nCRT). Considering that antitumor immunity status is an important determinant for nCRT, we performed an integrative analysis of immune-related gene profiles from pretreatment biopsies and constructed the first individualized immune signature for pCR and outcome prediction of ESCCs through a multicenter analysis. During the discovery phase, 14 differentially expressed immune-related genes (DEIGs) with greater than a twofold change between pCRs and less than pCRs (