Cancer remains a leading cause of mortality globally, highlighting the need for novel biomarkers to enhance prognosis and therapeutic strategies. Pleckstrin-2 (PLEK2), a member of the pleckstrin family, has been implicated in processes critical to tumor progression, but its role across cancers remains underexplored. This study systematically examined the expression patterns, prognostic relevance, and functional impact of PLEK2 across multiple cancer types. Using data from The Cancer Genome Atlas (TCGA), Genotype Tissue Expression Project (GTEx), and the Human Protein Atlas, we analyzed PLEK2 expression in both cancerous and normal tissues, revealing significant overexpression of PLEK2 in various cancers at the mRNA and protein levels. Single-cell RNA sequencing further indicated predominant expression of PLEK2 in tumor cells and macrophages within the tumor microenvironment. Survival analysis demonstrated that elevated PLEK2 expression correlated with poor prognosis in specific cancers, though its impact varied across cancer types. Functional assays showed that PLEK2 knockdown inhibited proliferation and migration in human cancer cell lines. In vivo studies using a Lewis lung carcinoma (LLC) model confirmed that PLEK2 knockdown suppressed tumor growth and enhanced the efficacy of PD-1 immunotherapy. Mechanistically, PLEK2 knockdown was associated with reduced AKT pathway activation, diminished tumor-associated macrophage infiltration, and increased CD8 T cell presence. Compounds like Navitoclax were also identified as potential PLEK2 inhibitors. In conclusion, PLEK2 played a multifaceted role in cancer progression and immune response modulation. Targeting PLEK2 might suppress tumor growth and overcome immunotherapy resistance, offering a promising biomarker and therapeutic target to improve cancer treatment outcomes.

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.

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.

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.

Recently, a novel oral, irreversible pan-HER tyrosine kinase inhibitor, pyrotinib, has shown anticancer effects on HER2-mutant non-small cell lung cancer (NSCLC) patients, but the explicit responses of lung cancer cells towards pyrotinib treatment are barely investigated. In our current study, we employed single-cell RNA sequencing to profile the longitudinal transcriptomic dynamics of lung cancer cells during the pyrotinib treatment, unraveling the potential resistance mechanisms. We treated a lung adenocarcinoma cell line, H358, with pyrotinib at doses of 100nM, 200nM, 500nM, and 1000nM every four days, respectively. Then, the untreated cells (P0) as well as longitudinal samples after each administration (P4, P8, P12, P16) were harvested for further analysis. After quality control, a total of 41,804 cells were sequenced and included for further analysis. The differentially expressed genes were determined using MAST and the differentially enriched cancer hallmark signatures based on single-sample Gene Set Variation Analysis (ssGSVA) were identified. The single-cell data revealed that the untreated cells (Sample P0) and persistent cells (Sample P16) had stable and distinct gene expression patterns, while cells during the course of treatment shared similar expression features at a transitional state. Several cancer driver genes were found to be aberrantly regulated during the administration, like EPHA2, CDKN2A, CDK4, PTEN, and MYC. Also, some pathways related to immune response were suppressed after pyrotinib treatment, including interferon alpha response, interferon gamma response, TNFA signaling via NF-κB, and inflammatory response. Intriguingly, CD274 (the gene encoding PD-L1) and LGALS9 were found to significantly decrease after pyrotinib treatment, suggesting that pyrotinib may be associated with outcomes of immunotherapy. With the large cell numbers analyzed, we distinguished an isolated, small subpopulation of cells characterized by the enriched expression of MGP, COL1A1, COL1A2, SPARC, and COL3A1 along with the elevated EMT and angiogenesis scores, suggesting its critical role in pyrotinib resistance. Collectively, our study for the first time reveals the transcriptomic evolution of NSCLC cells in response to pyrotinib administration at the single-cell resolution, providing new insights into potential mechanisms of resistance to this novel regimen in NSCLC. Citation Format: Xinfeng Wang, Yuan Li, Runsen Jin, Nan Sun, Jie He. Single-cell analysis sheds light on the resistance mechanisms of a novel pan-HER inhibitor, pyrotinib, in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5349.

N-7-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.

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.

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.

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.

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.

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. 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. 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). 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.

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.

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. N-6-methyladenosine (m(6)A) is a novel and decisive factor in tumour progression, chemotherapy resistance, and immunotherapy response. However, m(6)A modification in SCLC remains poorly understood. Methods We systematically explored the molecular features and clinical significance of m(6)A regulators in SCLC. We then constructed an m(6)A regulator-based prognostic signature (m(6)A 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 m(6)A 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 m(6)A regulators. Using the LASSO Cox model, a five-regulator-based (G3BP1, METTL5, ALKBH5, IGF2BP3, and RBM15B) m(6)A 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 m(6)A 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 m(6)A score to possess superior predictive power than other clinicopathological parameters. A multicentre multivariate analysis revealed the m(6)A 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 m(6)A regulators in LS-SCLC. Our multicentre analysis found that the m(6)A score was a reliable prognostic tool for guiding chemotherapy and immunotherapy selections for patients with SCLC.

The current study conducted the first exploration of biomarkers for prediction of adjuvant chemotherapy (aCT) benefit in patients with small cell esophageal carcinoma (SCEC). SCEC is a rather rare and aggressive malig-nant neuroendocrine gastrointestinal tumor. Unlike other two major pathological subtypes of esophageal carcinoma (EC)—esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC)—SCEC only accounts for ∼ 1.5% of the different subtypes of ECs. 1 Southeast Asian countries have the highest incidence rates of SCEC world-wide, especially in China. 2 Its prognosis is dismal, with a median survival of 8–21 months owing to its high recur-rence, rapid progression, and widespread metastases. 1 Additionally, due to its extreme rarity, there is no standard therapy. The current combination of surgery and aCT— adopted from well-established therapeutic strategies for small cell lung cancer (SCLC)—is the most common treat-ments for patients with limited-stage SCECs. This treatment was designed considering the histological and clinical similarity of SCECs and SCLCs. 2 Despite initially high response rates, patients’ outcomes have been heteroge-neous and many patients fail to benefit from this therapy while enduring its unnecessary side effects. 2 Therefore, more precise and clinically feasible classification strategies are urgently needed to identify aCT responders. To date, no studies have explored biomarkers for predicting the prognostic benefit after aCT in patients with SCECs. Antitumor immunity status is a critical deter-miner of chemotherapy and/or radiotherapy by our group and others.

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.

Abstract N6‐methyladenosine (m6A), 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 m6A modification has been tightly linked to this CSC‐TIME interplay, participating in the regulation of CSCs and TIME remolding. Interestingly, the m6A 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 m6A modification in the crosstalk between CSCs and the TIME, targeting m6A 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 m6A modifications in CSCs and the TIME, and also prospect the underling role of m6A modifications at the crossroads of CSCs and the TIME for the first time. Additionally, to provide the possibility of modulating m6A modifications as an emerging therapeutic strategy, we also explore the burgeoning inhibitors and technologies targeting m6A regulators. Lastly, considering recent advances in m6A‐seq technologies and cancer drug development, we propose the future directions of m6A 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.

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.

Immunotherapy has achieved success in the treatment of esophageal squamous cell carcinoma (ESCC). However, studies concerning immune phenotypes within the ESCC microenvironment and their relationship with prognostic outcomes are limited. We constructed and validated an individual immune-related risk signature for patients with ESCC. We collected 196 ESCC cases, including 119 samples from our previous public data (GSE53624) to use as a training set and an independent cohort with 77 quantitative real-time polymerase chain reaction (qRT-PCR) data, which we used for validation. Head and neck squamous cell carcinoma (HNSCC) and lung squamous cell carcinoma (LUSC) cohorts were also collected for validation. A least absolute shrinkage and selection operator (LASSO) model and a stepwise Cox proportional hazards regression model were used to construct the immune-specific signature. The potential mechanism and inflammatory landscapes of the signature were explored using bioinformatics and immunofluorescence assay methods. This signature predicted different prognoses in clinical subgroups and the independent cohort, as well as in patients with HNSCC and LUSC. Further exploration revealed that the signature was associated with specific inflammatory activities (activation of macrophages and T-cell signaling transduction). Additionally, high-risk patients exhibited distinctive immune checkpoints panel and higher regulatory T cell and fibroblast infiltration. This signature served as an independent prognostic factor in ESCC. This was the first applicable immune-related risk signature for ESCC. Our results furnished new hints of immune profiling of ESCC, which may provide some clues to further optimize associated cancer immunotherapies.