Nivolumab plus Ipilimumab in Lung Cancer with a High Tumor Mutational Burden

Exploring the tumor genomic landscape of aggressive prostate cancer by whole-genome sequencing of tissue or liquid biopsies

Treatment resistance remains a major issue in aggressive prostate cancer (PC), and novel genomic biomarkers may guide better treatment selection. Circulating tumor DNA (ctDNA) can provide minimally invasive information about tumor genomes, but the genomic landscape of aggressive PC based on whole-genome sequencing (WGS) of ctDNA remains incompletely characterized. Thus, we here performed WGS of tumor tissue (n = 31) or plasma ctDNA (n = 10) from a total of 41 aggressive PC patients, including 11 hormone-naïve, 15 hormone-sensitive, and 15 castration-resistant patients. Across all variant types, we found progressively more altered tumor genomic profiles in later stages of aggressive PC. The potential driver genes most frequently affected by single-nucleotide variants or insertions/deletions included the known PC-related genes TP53, CDK12, and PTEN and the novel genes COL13A1, KCNH3, and SENP3. Etiologically, aggressive PC was associated with age-related and DNA repair-related mutational signatures. Copy number variants most frequently affected 14q11.2 and 8p21.2, where no well-recognized PC-related genes are located, and also frequently affected regions near the known PC-related genes MYC, AR, TP53, PTEN, and BRCA1. Structural variants most frequently involved not only the known PC-related genes TMPRSS2 and ERG but also the less extensively studied gene in this context, PTPRD. Finally, clinically actionable variants were detected throughout all stages of aggressive PC and in both plasma and tissue samples, emphasizing the potential clinical applicability of WGS of minimally invasive plasma samples. Overall, our study highlights the feasibility of using liquid biopsies for comprehensive genomic characterization as an alternative to tissue biopsies in advanced/aggressive PC.

The single cell immunogenomic landscape after neoadjuvant immunotherapy combined chemotherapy in esophageal squamous cell carcinoma

Neoadjuvant immunotherapy represents promising strategy in the treatment of esophageal squamous cell carcinoma (ESCC). However, the mechanisms underlying its impact on treatment sensitivity or resistance remain a subject of controversy. In this study, we conducted single-cell RNA and T/B cell receptor (scTCR/scBCR) sequencing of CD45+ immune cells on samples from 10 patients who received neoadjuvant immunotherapy and chemotherapy. We also validated our findings using multiplexed immunofluorescence and analyzed bulk RNA-seq from other cohorts in public database. By integrating analysis of 87357 CD45+ cells, we found GZMK + effector memory T cells (Tem) were relatively enriched and CXCL13+ exhausted T cells (Tex) and regulator T cells (Treg) decreased among responders, indicating a persistent anti-tumor memory process. Additionally, the enhanced presence of BCR expansion and somatic hypermutation process within TNFRSF13B + memory B cells (Bmem) suggested their roles in antigen presentation. This was further corroborated by the evidence of the T-B co-stimulation pattern and CXCL13-CXCR5 axis. The complexity of myeloid cell heterogeneity was also particularly pronounced. The elevated expression of S100A7 in ESCC, as detected by bulk RNA-seq, was associated with an exhausted and immunosuppressive tumor microenvironment. In summary, this study has unveiled a potential regulatory network among immune cells and the clonal dynamics of their functions, and the mechanisms of exhaustion and memory conversion between GZMK + Tem and TNFRSF13B + Bmem from antigen presentation and co-stimulation perspectives during neoadjuvant PD-1 blockade treatment in ESCC.

Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours

Although more than a decade has passed since the approval of immune checkpoint inhibitors (ICIs) for the treatment of melanoma and non-small-cell lung, breast and gastrointestinal cancers, many patients still show limited response. US Food and Drug Administration (FDA)-approved biomarkers include programmed cell death 1 ligand 1 (PDL1) expression, microsatellite status (that is, microsatellite instability-high (MSI-H)) and tumour mutational burden (TMB), but these have limited utility and/or lack standardized testing approaches for pan-cancer applications. Tissue-based analytes (such as tumour gene signatures, tumour antigen presentation or tumour microenvironment profiles) show a correlation with immune response, but equally, these demonstrate limited efficacy, as they represent a single time point and a single spatial assessment. Patient heterogeneity as well as inter- and intra-tumoural differences across different tissue sites and time points represent substantial challenges for static biomarkers. However, dynamic biomarkers such as longitudinal biopsies or novel, less-invasive markers such as blood-based biomarkers, radiomics and the gut microbiome show increasing potential for the dynamic identification of ICI response, and patient-tailored predictors identified through neoadjuvant trials or novel ex vivo tumour models can help to personalize treatment. In this Perspective, we critically assess the multiple new static, dynamic and patient-specific biomarkers, highlight the newest consortia and trial efforts, and provide recommendations for future clinical trials to make meaningful steps forwards in the field.

A paradigm shift in understanding vulvovaginal melanoma as a distinct tumor type compared with cutaneous melanoma

OBJECTIVE

Our goal was to compare molecular and immune profiles of vulvovaginal melanoma (VVM) with cutaneous melanoma (CM) and explore the significance of immune checkpoint inhibitor (ICI) agents on survival.

METHODS

Samples from VVM and CM tumors underwent comprehensive molecular and immune profiling. Treatment and survival data were extracted from insurance claims data and OS was calculated from time of ICI treatment to last contact. Statistical significance was determined using chi-square and Wilcoxon rank sum test and adjusted for multiple comparisons.

RESULTS

Molecular analysis was performed on 142 VVM and 3823 CM tumors. VVM demonstrated significantly (q < 0·01) less frequent BRAF and more frequent KIT, ATRX, and SF3B1 mutations. Alterations in pathways involving DNA damage and mRNA splicing were more common in VVM, while alterations in cell cycle and chromatin remodeling were less common. Immunogenicity of VVM was lower than CM, with an absence of high TMB (0% vs 46.9%) and lower PD-L1 positivity (18·0% vs 29·5%). Median immune checkpoint gene expression was lower in VVM, as were cell fractions for type I macrophages and CD8+ T-cells(q < 0·01). Myeloid dendritic cells were increased in VVM(q < 0·01). Median OS was shorter for VVM than for CM patients treated with ICIs (17·6 versus 37·9 months, HR:1·65 (95% CI 1·02-2·67) p = 0·04).

CONCLUSIONS

VVM has a distinct molecular and immune profile compared to CM, which may contribute to the worse survival in VVM compared to CM patients treated with ICI therapy. Though ICIs have been a mainstay of treatment in recent years, our findings suggest that new therapeutic strategies are needed.

Spatial genomic, biochemical and cellular mechanisms underlying meningioma heterogeneity and evolution

Intratumor heterogeneity underlies cancer evolution and treatment resistance, but targetable mechanisms driving intratumor heterogeneity are poorly understood. Meningiomas are the most common primary intracranial tumors and are resistant to all medical therapies, and high-grade meningiomas have significant intratumor heterogeneity. Here we use spatial approaches to identify genomic, biochemical and cellular mechanisms linking intratumor heterogeneity to the molecular, temporal and spatial evolution of high-grade meningiomas. We show that divergent intratumor gene and protein expression programs distinguish high-grade meningiomas that are otherwise grouped together by current classification systems. Analyses of matched pairs of primary and recurrent meningiomas reveal spatial expansion of subclonal copy number variants associated with treatment resistance. Multiplexed sequential immunofluorescence and deconvolution of meningioma spatial transcriptomes using cell types from single-cell RNA sequencing show decreased immune infiltration, decreased MAPK signaling, increased PI3K-AKT signaling and increased cell proliferation, which are associated with meningioma recurrence. To translate these findings to preclinical models, we use CRISPR interference and lineage tracing approaches to identify combination therapies that target intratumor heterogeneity in meningioma cell co-cultures.

Immunotherapy combination approaches: mechanisms, biomarkers and clinical observations

The approval of the first immune checkpoint inhibitors provided a paradigm shift for the treatment of malignancies across a broad range of indications. Whereas initially, single-agent immune checkpoint inhibition was used, increasing numbers of patients are now treated with combination immune checkpoint blockade, where non-redundant mechanisms of action of the individual agents generally lead to higher response rates. Furthermore, immune checkpoint therapy has been combined with various other therapeutic modalities, including chemotherapy, radiotherapy and other immunotherapeutics such as vaccines, adoptive cellular therapies, cytokines and others, in an effort to maximize clinical efficacy. Currently, a large number of clinical trials test combination therapies with an immune checkpoint inhibitor as a backbone. However, proceeding without inclusion of broad, if initially exploratory, biomarker investigations may ultimately slow progress, as so far, few combinations have yielded clinical successes based on clinical data alone. Here, we present the rationale for combination therapies and discuss clinical data from clinical trials across the immuno-oncology spectrum. Moreover, we discuss the evolution of biomarker approaches and highlight the potential new directions that comprehensive biomarker studies can yield.

A real-world analysis of second-line treatment option, gemcitabine plus anlotinib and anti-PD1, in advanced pancreatic cancer

BACKGROUND

In the second-line treatment of advanced pancreatic cancer (APC), there is only one approved regimen based on the phase III NAPOLI-1 trial. However, for patients progressing after Nab-paclitaxel and Gemcitabine (Nab-P/Gem) or Nab-P combinations, second-line treatment were very limited.

METHODS

This is a retrospective single-center analysis of patients. Our aim was to determine the effectiveness and tolerability of a novel regimen, gemcitabine plus Anlotinib and anti-PD1, in APC patients and to compare it with oxaliplatin, irinotecan, leucovorin, and fluorouracil (FOLFIRINOX) in the second-line setting who have failed on the first-line Nab-P combinations.

RESULTS

In total, twenty-three patients received Gemcitabine plus Anlotinib and anti-PD1 in the second-line, 28 patients were treated with FOLFORINOX. There was no significant difference in overall survival (OS) or progression free survival (PFS) for either of the two sequences (p > 0.05). Patients who received Gemcitabine plus Anlotinib and anti-PD1 had a median PFS of 4.0 months (95% CI: 1.1-6.9) versus 3.5 months (95% CI 1.8-5.2) in FOLFORINOX group (p = 0.953). The median OS of Gemcitabine plus Anlotinib and anti-PD1 was 9.0 months (95% CI: 4.0-13.7) and 8.0 months (95% CI: 5.5-10.5) in FOLFORINOX group (p = 0.373). Grade ≥3 treatment-emergent adverse events (AEs) occurred for 13% of patients with Gemcitabine plus Anlotinib and anti-PD1 and 40% for FOLFORINOX.

CONCLUSION

Our data confirms the effectiveness of Gemcitabine plus Anlotinib and anti-PD1 as a well-tolerated regimen in the second-line treatment of APC and extends available data on its use as a second-line treatment option when compared with FOLFIRINOX.

The significance of inflammatory markers in prognosticating the effectiveness and safety of immunotherapy in conjunction with chemotherapy during the primary intervention of advanced non-small cell lung carcinoma

OBJECTIVE

The aim of this study is to scrutinize the prognostic significance of inflammatory biomarkers concerning the effectiveness and safety of combining PD-1 inhibition with chemotherapy in the management of advanced NSCLC.

METHODS

We conducted a retrospective analysis involving 206 NSCLC patients who received treatment at Qingdao Municipal Hospital. The study encompassed the acquisition of baseline clinical attributes and hematological parameters of these patients. The optimal threshold values for PLT and NLR were ascertained based on pre-treatment evaluations, with a particular focus on their association with PFS. Variables linked to PFS were subject to scrutiny through Kaplan-Meier analysis and logistic regression. The Receiver Operating Characteristic (ROC) curve served as the means to determine the ideal cut-off values for categorizing levels of inflammatory markers into high and low classifications. We employed Chi-square tests to evaluate the relationship between elevated and reduced baseline levels of inflammatory markers and irAE.

RESULTS

Kaplan-Meier analysis disclosed that patients in the low baseline PLT group and the low NLR group exhibited a substantially more favorable prognosis in contrast to their counterparts in the high baseline PLT and high NLR groups. Multivariate analysis indicated that diminished baseline PLT and NLR levels before treatment independently foretell extended PFS. Chi-square analysis underscored a substantial correlation between baseline WBC, NEUT, LYMPH, MONO, and NLR levels and irAE.

CONCLUSION

Subdued baseline PLT and NLR levels may serve as indicators of a more auspicious prognosis in patients contending with advanced NSCLC undergoing the combination of PD-1 inhibition and chemotherapy. Elevated baseline levels of inflammatory markers antedating PD-1 therapy in advanced NSCLC may be intimately interrelated with the occurrence of irAE.

Tackling Non-Small Cell Lung Cancer in Young Adults: From Risk Factors and Genetic Susceptibility to Lung Cancer Profile and Outcomes

Lung cancer has traditionally been associated with advanced age; however, its increasing incidence among young adults raises concerning questions regarding its etiology and unique considerations for this population. In contrast to the older population, the onset of lung cancer at younger age may be attributed to a complex interplay of incompletely understood individual susceptibility and prevalent environmental risk factors beyond tobacco smoke exposure, such as radon gas and air pollution, which are widespread globally. Consequently, this leads to distinct clinical and molecular profiles, requiring a tailored approach. Furthermore, a diagnosis of cancer represents a threatening event during the prime years of a young person's life, prompting concern about career development, social aspects, fertility aspirations, and physical independence. This poses significant additional challenges for health care professionals in a field that remains underexplored. This comprehensive review recognizes lung cancer in young adults as a distinct entity, exploring its clinical and molecular characteristics, diverse predisposing factors, and priorities in terms of quality of life, with the aim of providing practical support to oncologists and enhancing our understanding of this under-researched population.

Multifactoral immune modulation potentiates durable remission in multiple models of aggressive malignancy

Tumors typically lack canonical danger signals required to activate adaptive immunity and also frequently employ substantial immunomodulatory mechanisms that downregulate adaptive responses and contribute to escape from immune surveillance. Given the variety of mechanisms involved in shielding tumors from immune recognition, it is not surprising that single-agent immunomodulatory approaches have been largely unsuccessful in generating durable antitumor responses. Here we report a unique combination of immunomodulatory and cytostatic agents that recondition the tumor microenvironment and eliminate complex and/or poor-prognosis tumor types including the non-immunogenic 4T-1 model of TNBC, the aggressive MOC-2 model of HNSCC, and the high-risk MYCN-amplified model of neuroblastoma. A course of therapy optimized for TNBC cured a majority of tumors in both ectopic and orthotopic settings and eliminated metastatic spread in all animals tested at the highest doses. Immune responses were transferable between therapeutic donor and naïve recipient through adoptive transfer, and a sizeable abscopal effect on distant, untreated lesions could be demonstrated experimentally. Similar results were observed in HNSCC and neuroblastoma models, with characteristic remodeling of the tumor microenvironment documented in all model systems. scRNA-seq analysis implicated upregulation of innate immune responses and antigen presentation in tumor cells and the myeloid cell compartment as critical early events. This analysis also highlighted the potential importance of the autonomic nervous system in the governance of inflammatory processes. The data indicate that the targeting of multiple pathways and mechanisms of action can result in substantial synergistic antitumor effects and suggest follow-up in the neoadjuvant setting may be warranted.

Targeted proteomics-determined multi-biomarker profiles developed classifier for prognosis and immunotherapy responses of advanced cervical cancer

Background

Cervical cancer (CC) poses a global health challenge, with a particularly poor prognosis in cases of recurrence, metastasis, or advanced stages. A single biomarker is inadequate to predict CC prognosis or identify CC patients likely to benefit from immunotherapy, presumably owing to tumor complexity and heterogeneity.

Methods

Using advanced Olink proteomics, we analyzed 92 oncology-related proteins in plasma from CC patients receiving immunotherapy, based upon the comparison of protein expression levels of pre-therapy with those of therapy-Cycle 6 in the partial response (PR) group and progressive disease (PD) group, respectively.

Results

55 proteins were identified to exhibit differential expression trends across pre-therapy and post-therapy in both PR and PD groups. Enriched GO terms and KEGG pathways were associated with vital oncological and immunological processes. A logistic regression model, using 5 proteins (ITGB5, TGF-α, TLR3, WIF-1, and ERBB3) with highest AUC values, demonstrated good predictive performance for prognosis of CC patients undergoing immunotherapy and showed potential across different cancer types. The effectiveness of these proteins in prognosis prediction was further validated using TCGA-CESC datasets. A negative correlation and previously unidentified roles of WIF-1 in CC immunotherapy was also first determined.

Conclusion

Our findings reveal multi-biomarker profiles effectively predicting CC prognosis and identifying patients benefitting most from immunotherapy, especially for those with limited treatment options and traditionally poor prognosis, paving the way for personalized immunotherapeutic treatments and improved clinical strategies.

IFN-α/β/IFN-γ/IL-15 pathways identify GBP1-expressing tumors with an immune-responsive phenotype

Immunotherapy is widely used in cancer treatment; however, only a subset of patients responds well to it. Significant efforts have been made to identify patients who will benefit from immunotherapy. Successful anti-tumor immunity depends on an intact cancer-immunity cycle, especially long-lasting CD8+ T-cell responses. Interferon (IFN)-α/β/IFN-γ/interleukin (IL)-15 pathways have been reported to be involved in the development of CD8+ T cells. And these pathways may predict responses to immunotherapy. Herein, we aimed to analyze multiple public databases to investigate whether IFN-α/β/IFN-γ/IL-15 pathways could be used to predict the response to immunotherapy. Results showed that IFN-α/β/IFN-γ/IL-15 pathways could efficiently predict immunotherapy response, and guanylate-binding protein 1 (GBP1) could represent the IFN-α/β/IFN-γ/IL-15 pathways. In public and private cohorts, we further demonstrated that GBP1 could efficiently predict the response to immunotherapy. Functionally, GBP1 was mainly expressed in macrophages and strongly correlated with chemokines involved in T-cell migration. Therefore, our study comprehensively investigated the potential role of GBP1 in immunotherapy, which could serve as a novel biomarker for immunotherapy and a target for drug development.

One-carbon unit supplementation fuels purine synthesis in tumor-infiltrating T cells and augments checkpoint blockade

Nucleotides perform important metabolic functions, carrying energy and feeding nucleic acid synthesis. Here, we use isotope tracing-mass spectrometry to quantitate contributions to purine nucleotides from salvage versus de novo synthesis. We further explore the impact of augmenting a key precursor for purine synthesis, one-carbon (1C) units. We show that tumors and tumor-infiltrating T cells (relative to splenic or lymph node T cells) synthesize purines de novo. Shortage of 1C units for T cell purine synthesis is accordingly a potential bottleneck for anti-tumor immunity. Supplementing 1C units by infusing formate drives formate assimilation into purines in tumor-infiltrating T cells. Orally administered methanol functions as a formate pro-drug, with deuteration enabling kinetic control of formate production. Safe doses of methanol raise formate levels and augment anti-PD-1 checkpoint blockade in MC38 tumors, tripling durable regressions. Thus, 1C deficiency can gate antitumor immunity and this metabolic checkpoint can be overcome with pharmacological 1C supplementation.

Identification of a fatty acid metabolism-related gene signature to predict prognosis in stomach adenocarcinoma

BACKGROUND

Fatty acid metabolism (FAM) contributes to tumorigenesis and tumor development, but the role of FAM in the progression of stomach adenocarcinoma (STAD) has not been comprehensively clarified.

METHODS

The expression data and clinical follow-up information were obtained from The Cancer Genome Atlas (TCGA). FAM pathway was analyzed by gene set enrichment analysis (GSEA) and single-sample GSEA (ssGSEA) methods. Univariate Cox regression analysis was conducted to select prognosis genes. Molecular subtypes were classified by consensus clustering analysis. Furthermore, least absolute shrinkage and selection operator (Lasso) analysis was employed to develop a risk model. ESTIMATE and tumour immune dysfunction and exclusion (TIDE) algorithm were used to assess immunity. pRRophetic package was conducted to predict drug sensitivity.

RESULTS

Based on 14 FAM related prognosis genes (FAMRG), 2 clusters were determined. Patients in C2 showed a worse overall survival (OS). Furthermore, a 7-FAMRG risk model was established as an independent predictor for STAD, with a higher riskscore indicating an unfavorable OS. High riskscore patients had higher TIDE score and these patients were more sensitive to anticancer drugs such as Bortezomib, Dasatinib and Pazopanib. A nomogram based on riskscore was an effective prediction tool applicable to clinical settings. The results from pan-cancer analysis supported a prominent application value of riskscore model in other cancer types.

CONCLUSION

The FAMRGs model established in this study could help predict STAD prognosis and offer new directions for future studies on dysfunctional FAM-induced damage and anti-tumor drugs in STAD disease.

PCDH11X mutation as a potential biomarker for immune checkpoint therapies in lung adenocarcinoma

Immune checkpoint inhibitors (ICIs) have achieved impressive success in lung adenocarcinoma (LUAD). However, the response to ICIs varies among patients, and predictive biomarkers are urgently needed. PCDH11X is frequently mutated in LUAD, while its role in ICI treatment is unclear. In this study, we curated genomic and clinical data of 151 LUAD patients receiving ICIs from three independent cohorts. Relations between PCDH11X and treatment outcomes of ICIs were examined. A melanoma cohort collected from five published studies, a pan-cancer cohort, and non-ICI-treated TCGA-LUAD cohort were also examined to investigate whether PCDH11X mutation is a specific predictive biomarker for LUAD ICI treatment. Among the three ICI-treated LUAD cohorts, PCDH11X mutation (PCDH11X-MUT) was associated with better clinical response compared to wild-type PCDH11X (PCDH11X-WT). While in ICI-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and the non-ICI-treated TCGA-LUAD cohort, no significant differences in overall survival (OS) were observed between the PCDH11X-MUT and PCDH11X-WT groups. PCDH11X mutation was associated with increased PD-L1 expression, tumor mutation burden (TMB), neoantigen load, DNA damage repair (DDR) mutations, and hot tumor microenvironment in TCGA-LUAD cohort. Our findings suggested that the PCDH11X mutation might serve as a specific biomarker to predict the efficacy of ICIs for LUAD patients. Considering the relatively small sample size of ICI-treated cohorts, future research with larger cohorts and prospective clinical trials will be essential for validating and further exploring the role of PCDH11X mutation in the context of immunotherapy outcomes in LUAD. KEY MESSAGES: PCDH11X mutation is associated with better clinical response compared to wild type PCDH11X in three ICIs-treated LUAD cohorts. In ICIs-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and non-ICIs-treated TCGA-LUAD cohorts PCDH11X mutation is not associated with better clinical response, suggesting PCDH11X mutation might be a specific biomarker to predict the efficacy of ICIs treatment for LUAD patients. PCDH11X mutation is associated with increased PD-L1 expression, tumor mutation burden, and neoantigen load in TCGA-LUAD cohort. PCDH11X mutation is associated with hot tumor microenvironment in TCGA-LUAD cohort.

Camrelizumab plus famitinib in previously chemo-immunotherapy treated patients with advanced NSCLC: results from an open-label multicenter phase 2 basket study

BACKGROUND

The combination of immune checkpoint inhibitors and antiangiogenic agents has been effective in treating multiple cancers. This was further explored in an open-label, multicenter phase 2 basket study (NCT04346381), which evaluated the antitumor activity and safety of camrelizumab (an anti-PD-1 antibody) plus famitinib (a receptor tyrosine kinase inhibitor) in patients with advanced solid tumors. We herein report the findings from the cohort of advanced NSCLC patients who progressed after treatment with platinum-doublet chemotherapy and immunotherapy.

METHODS

Eligible patients were enrolled and treated with camrelizumab (200 mg once every 3 weeks via intravenous infusion) and oral famitinib (20 mg once daily). The primary endpoint was the objective response rate (ORR). Secondary endpoints included the disease control rate (DCR), duration of response (DoR), progression-free survival (PFS), overall survival (OS), and safety.

RESULTS

Forty patients were enrolled in this cohort, with a median follow-up duration of 11.5 months. Three patients (7.5%) achieved a partial response, and 29 patients (72.5%) achieved stable disease. The ORR and DCR with this combination regimen were 7.5% (95% CI, 1.6-20.4) and 80.0% (95% CI, 64.4-90.9), respectively. The median DoR was 12.1 months (95% CI, 10.3-not reached). The median PFS was 5.4 months (95% CI, 4.1-7.5), and the median OS was 12.1 months (95% CI, 9.1-16.7). The estimated 12-month OS rate was 51.5% (95% CI, 34.9-65.9). The most frequent grade 3 or higher treatment-related adverse events occurring in more than 5% of patients included hypertension (27.5%), palmar-plantar erythrodysesthesia syndrome (10%), decreased neutrophil count (10%), and proteinuria (7.5%).

CONCLUSION

Camrelizumab plus famitinib demonstrated favorable benefits in PFS and OS, along with manageable safety profiles, in patients with advanced NSCLC who progressed after platinum-doublet chemotherapy and immunotherapy. This finding warrants further exploration.

Association of pretreatment neutrophil-to-lymphocyte ratio with clinical outcomes in cancer immunotherapy: An evidence synthesis from 30 meta-analyses

BACKGROUND

The Neutrophil-to-lymphocyte ratio (NLR) holds relevance in cancer immunotherapy outcomes, yet its validation remains limited. Thus, we conducted an umbrella review to comprehensively assess the association between pretreatment NLR and immunotherapy outcomes, along with evaluating their credibility and strength.

METHODS

Electronic databases, including PubMed, Web of Science, Embase, Scopus, and Cochrane, were systematically searched for eligible systematic reviews and meta-analyses. Quality assessment and evidence grading utilized AMSTAR, GRADE, and additional classification criteria, following PRISMA and PRIOR guidelines.

RESULTS

Thirty unique meta-analyses were included, with 24 associations (80%) exhibiting statistical significance. Notably, associations between pretreatment NLR and the prognosis of renal cell carcinoma, hepatocellular carcinoma, melanoma, and non-small cell lung cancer garnered highly suggestive or convincing evidence grading.

CONCLUSIONS

Elevated pretreatment NLR correlates with poor outcomes in cancer immunotherapy, suggesting its potential as a biomarker for identifying appropriate treatment populations and predicting clinical outcomes. Nevertheless, further validation through prospective cohort studies is warranted.

Integrative analysis of the cuproptosis-related gene ATP7B in the prognosis and immune infiltration of IDH1 wild-type glioma

Glioma is the most common malignant tumor in the brain and the central nervous system with a poor prognosis, and wild-type isocitrate dehydrogenase (IDH) glioma indicates a worse prognosis. Cuproptosis is a recently discovered form of cell death regulated by copper-dependent mitochondrial respiration. However, the effect of cuproptosis on tumor prognosis and immune infiltration is not clear. In this research, we analyzed of public databases to show the correlation between cuproptosis-related genes and the prognosis of IDH1 wild-type glioma. Nine out of 12 genes were upregulated in IDH1 wild-type glioma patients, and 6 genes were significantly associated with overall survival (OS), while 5 genes were associated with progression-free survival (PFS). Then, we constructed a prognostic cuproptosis-related gene signature for IDH1 wild-type glioma patients. ATP7B was considered an independent prognostic indicator, and a low expression level of ATP7B was related to a shorter period of OS and PFS. Moreover, downregulation of ATP7B was correlated not only with the infiltration of activated NK cells, CD8 + T cells and M2 macrophages; but also with high expression of immune checkpoint genes and tumor mutation burden (TMB). In the IDH1 wild-type glioma tissues we collected, our data also confirmed that high tumor grade was accompanied by low expression of ATP7B and high expression of PD-L1, which was associated with increasing infiltration of CD8 + immune cells. In conclusion, our research constructed a prognostic cuproptosis-related gene signature model to predict the prognosis of IDH1 wild-type glioma. ATP7B is deemed to be a potential prognostic indicator and novel immunotherapy biomarker for IDH1 wild-type glioma patients.

Neoantigen Identification and Dendritic Cell-Based Vaccines for Lung Cancer Immunotherapy

Immunotherapies can treat many cancers, including difficult-to-treat cases such as lung cancer. Due to its tolerability, long-lasting therapeutic responses, and efficacy in a wide spectrum of patients, immunotherapy can also help to treat lung cancer, which has few treatment choices. Tumor-specific antigens (TSAs) for cancer vaccinations and T-cell therapies are difficult to discover. Neoantigens (NeoAgs) from genetic mutations, irregular RNA splicing, protein changes, or viral genetic sequences in tumor cells provide a solution. NeoAgs, unlike TSAs, are non-self and can cause an immunological response. Next-generation sequencing (NGS) and bioinformatics can swiftly detect and forecast tumor-specific NeoAgs. Highly immunogenic NeoAgs provide personalized or generalized cancer immunotherapies. Dendritic cells (DCs), which originate and regulate T-cell responses, are widely studied potential immunotherapeutic therapies for lung cancer and other cancers. DC vaccines are stable, reliable, and safe in clinical trials. The purpose of this article is to evaluate the current status, limitations, and prospective clinical applications of DC vaccines, as well as the identification and selection of major histocompatibility complex (MHC) class I and II genes for NeoAgs. Our goal is to explain DC biology and activate DC manipulation to help researchers create extremely potent cancer vaccines for patients.

The risk of endocrine immune-related adverse events induced by PD-1 inhibitors in cancer patients: a systematic review and meta-analysis

Objective

Endocrinopathies are the most common immune-related adverse events (irAEs) observed during therapy with PD-1 inhibitors. In this study, we conducted a comprehensive systematic review and meta-analysis to evaluate the risk of immune-related endocrinopathies in patients treated with PD-1 inhibitors.

Methods

We performed a systematic search in the PubMed, Embase, and Cochrane Library databases to retrieve all randomized controlled trials (RCTs) involving PD-1 inhibitors, spanning from their inception to November 24, 2023. The comparative analysis encompassed patients undergoing chemotherapy, targeted therapy, or receiving placebo as control treatments. This study protocol has been registered with PROSPERO (CRD42023488303).

Results

A total of 48 clinical trials comprising 24,514 patients were included. Compared with control groups, patients treated with PD-1 inhibitors showed an increased risk of immune-related adverse events, including hypothyroidism, hyperthyroidism, hypophysitis, thyroiditis, diabetes mellitus, and adrenal insufficiency. Pembrolizumab was associated with an increased risk of all aforementioned endocrinopathies (hypothyroidism: RR=4.76, 95%CI: 3.55-6.39; hyperthyroidism: RR=9.69, 95%CI: 6.95-13.52; hypophysitis: RR=5.47, 95%CI: 2.73-10.97; thyroiditis: RR=5.95, 95%CI: 3.02-11.72; diabetes mellitus: RR=3.60, 95%CI: 1.65-7.88; adrenal insufficiency: RR=4.80, 95%CI: 2.60-8.88). Nivolumab was associated with an increased risk of hypothyroidism (RR=7.67, 95%CI: 5.00-11.75) and hyperthyroidism (RR=9.22, 95%CI: 4.71-18.04). Tislelizumab and sintilimab were associated with an increased risk of hypothyroidism (RR=19.07, 95%CI: 5.46-66.69 for tislelizumab and RR=18.36, 95%CI: 3.58-94.21 for sintilimab). For different tumor types, both hypothyroidism and hyperthyroidism were at high risks. Besides, patients with non-small cell lung cancer were at a higher risk of thyroiditis and adrenal insufficiency. Patients with melanoma were at a higher risk of hypophysitis and diabetes mellitus. Both low- and high-dose group increased risks of hypothyroidism and hyperthyroidism.

Conclusion

Risk of endocrine irAEs may vary in different PD-1 inhibitors and different tumor types. Increased awareness and understanding of the risk features of endocrine irAEs associated with PD-1 inhibitors is critical for clinicians.

Systematic review registration

crd.york.ac.uk/prospero, identifier PROSPERO (CRD42023488303).

Predictive value of PD-L1 and TMB for short-term efficacy prognosis in non-small cell lung cancer and construction of prediction models

Objective

To investigate the correlation between programmed death ligand 1(PD-L1), tumor mutation burden (TMB) and the short-term efficacy and clinical characteristics of anti-PD-1 immune checkpoint inhibitor combination chemotherapy in NSCLC patients. The efficacy of the prediction model was evaluated.

Methods

A total of 220 NSCLC patients receiving first-line treatment with anti-PD-1 immune checkpoint inhibitor combined with chemotherapy were retrospectively collected. The primary endpoint was short-term efficacy ORR. The correlation between short-term efficacy, PD-L1, TMB, and clinical characteristics using χ2 test or t-test was evaluated. Screen the independent prognostic factors using univariate and multivariate logistic regression analyses, and construct a nomogram prediction model using the "rms" package in R software. Using receiver operating characteristic (ROC) curve analysis to evaluate the independent Prognostic factors and the prediction model. Using decision curve analysis (DCA) to verify the superiority of the prediction model.

Results

The mean values of PD-L1, TMB, neutrophils, lymphocytes, neutrophil-to-lymphocyte ratio, and albumin were the highest in the ORR group, PD-L1 expression and TMB correlated with epidermal growth factor receptor expression. Multivariate analyses showed that PD-L1, TMB, and neutrophil were independent prognostic factors for ORR. The area under the ROC curve (AUC) values of the ROC constructed based on these three indicators were 0.7104, 0.7139, and 0.7131, respectively. The AUC value under the ROC of the nomogram model was 0.813. The DCA of the model showed that all three indicators used together to build the prediction model of the net return were higher than those of the single indicator prediction model.

Conclusion

PD-L1, TMB, and neutrophils are independent prognostic factors for short-term efficacy. The nomogram prediction model constructed using these three indicators can further improve predictive efficacy of ICIs in patients with NSCLC.

WhARIO: whole-slide-image-based survival analysis for patients treated with immunotherapy

Purpose

Immune checkpoint inhibitors (ICIs) are now one of the standards of care for patients with lung cancer and have greatly improved both progression-free and overall survival, although < 20 % of the patients respond to the treatment, and some face acute adverse events. Although a few predictive biomarkers have integrated the clinical workflow, they require additional modalities on top of whole-slide images and lack efficiency or robustness. In this work, we propose a biomarker of immunotherapy outcome derived solely from the analysis of histology slides.

Approach

We develop a three-step framework, combining contrastive learning and nonparametric clustering to distinguish tissue patterns within the slides, before exploiting the adjacencies of previously defined regions to derive features and train a proportional hazards model for survival analysis. We test our approach on an in-house dataset of 193 patients from 5 medical centers and compare it with the gold standard tumor proportion score (TPS) biomarker.

Results

On a fivefold cross-validation (CV) of the entire dataset, the whole-slide image-based survival analysis for patients treated with immunotherapy (WhARIO) features are able to separate a low- and a high-risk group of patients with a hazard ratio (HR) of 2.29 (CI 95 = 1.48 to 3.56), whereas the TPS 1% reference threshold only reaches a HR of 1.81 (CI 95 = 1.21 to 2.69). Combining the two yields a higher HR of 2.60 (CI 95 = 1.72 to 3.94). Additional experiments on the same dataset, where one out of five centers is excluded from the CV and used as a test set, confirm these trends.

Conclusions

Our uniquely designed WhARIO features are an efficient predictor of survival for lung cancer patients who received ICI treatment. We achieve similar performance to the current gold standard biomarker, without the need to access other imaging modalities, and show that both can be used together to reach even better results.

Circulating biomarkers as predictors of response to immune checkpoint inhibitors in NSCLC: Are we on the right path?

Immune checkpoints inhibitors (ICIs) have markedly improved the therapeutic management of advanced NSCLC and, more recently, they have demonstrated efficacy also in the early-stage disease. Despite better survival outcomes with ICIs compared to standard chemotherapy, a large proportion of patients can derive limited clinical benefit from these agents. So far, few predictive biomarkers, including the programmed death-ligand 1 (PD-L1), have been introduced in clinical practice. Therefore, there is an urgent need to identify novel biomarkers to select patients for immunotherapy, to improve efficacy and avoid unnecessary toxicity. A deeper understanding of the mechanisms involved in antitumor immunity and advances in the field of liquid biopsy have led to the identification of a wide range of circulating biomarkers that could potentially predict response to immunotherapy. Herein, we provide an updated overview of these circulating biomarkers, focusing on emerging data from clinical studies and describing modern technologies used for their detection.

Prediction performance comparison of biomarkers for response to immune checkpoint inhibitors in advanced non-small cell lung cancer

BACKGROUND

The aim of the present study was to compare the predictive accuracy of PD-L1 immunohistochemistry (IHC), tissue or blood tumor mutation burden (tTMB, bTMB), gene expression profile (GEP), driver gene mutation, and combined biomarkers for immunotherapy response of advanced non-small cell lung cancer (NSCLC).

METHODS

In part 1, clinical trials involved with predictive biomarker exploration for immunotherapy in advanced NSCLC were included. The area under the curve (AUC) of the summary receiver operating characteristic (SROC), sensitivity, specificity, likelihood ratio and predictive value of the biomarkers were evaluated. In part 2, public datasets of immune checkpoint inhibitor (ICI)-treated NSCLC involved with biomarkers were curated (N = 871). Odds ratio (OR) of the positive versus negative biomarker group for objective response rate (ORR) was measured.

RESULTS

In part 1, the AUC of combined biomarkers (0.75) was higher than PD-L1 (0.64), tTMB (0.64), bTMB (0.68), GEP (0.67), and driver gene mutation (0.51). Combined biomarkers also had higher specificity, positive likelihood ratio and positive predictive value than single biomarkers. In part 2, the OR of combined biomarkers of PD-L1 plus TMB (PD-L1 cutoff 1%, 0.14; cutoff 50% 0.13) was lower than that of PD-L1 (cutoff 1%, 0.33; cutoff 50% 0.24), tTMB (0.28), bTMB (0.48), EGFR mutation (0.17) and KRAS mutation (0.47), for distinguishing ORR of patients after immunotherapy. Furthermore, positive PD-L1, tTMB-high, wild-type EGFR, and positive PD-L1 plus TMB were associated with prolonged progression-free survival (PFS).

CONCLUSION

Combined biomarkers have superior predictive accuracy than single biomarkers for immunotherapy response of NSCLC. Further investigation is warranted to select optimal biomarkers for various clinical settings.

Immunologic tumor microenvironment modulators for turning cold tumors hot

Tumors can be classified into distinct immunophenotypes based on the presence and arrangement of cytotoxic immune cells within the tumor microenvironment (TME). Hot tumors, characterized by heightened immune activity and responsiveness to immune checkpoint inhibitors (ICIs), stand in stark contrast to cold tumors, which lack immune infiltration and remain resistant to therapy. To overcome immune evasion mechanisms employed by tumor cells, novel immunologic modulators have emerged, particularly ICIs targeting cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed cell death protein 1/programmed death-ligand 1(PD-1/PD-L1). These agents disrupt inhibitory signals and reactivate the immune system, transforming cold tumors into hot ones and promoting effective antitumor responses. However, challenges persist, including primary resistance to immunotherapy, autoimmune side effects, and tumor response heterogeneity. Addressing these challenges requires innovative strategies, deeper mechanistic insights, and a combination of immune interventions to enhance the effectiveness of immunotherapies. In the landscape of cancer medicine, where immune cold tumors represent a formidable hurdle, understanding the TME and harnessing its potential to reprogram the immune response is paramount. This review sheds light on current advancements and future directions in the quest for more effective and safer cancer treatment strategies, offering hope for patients with immune-resistant tumors.

[Molecular pathological analysis through the ages]

BACKGROUND

Molecular pathological examinations of tumor samples encompass a wide range of diagnostic analyses. Especially in recent years, numerous new biomarkers have come to the forefront-the analysis of which is crucial for therapy decisions.

OBJECTIVES

Within the field of molecular pathology, the demands of next generation sequencing (NGS)-based requirements have experienced massive growth in recent years. To meet this demand, methods are constantly being adapted and further developed. The following sections aim to illuminate how this trend arises and which analyses are gaining importance.

METHODS

The article provides an overview of the essential nucleic acid-based analysis techniques in the field of massive parallel sequencing. Terms such as DNA- and RNA-based techniques, as well as the associated analysis methods, are described, particularly with regard to their use in routine molecular pathological diagnostics.

RESULTS

The breadth of genomic sequencing has been steadily growing in recent years, particularly due to the increasing relevance of personalized medicine, along with the rising approvals of targeted therapeutics. This necessitates, among other things, the analysis of new biomarkers. The diagnostics as part of interdisciplinary molecular tumor boards (MTB) are now based on large gene panels (> 1 megabase). Furthermore, through the "Modellvorhaben Genomsequenzierung" § 64e, whole exome or whole genome sequencing has been made available for oncological patients. Given these developments, it is evident that future analyses will require the integration of additional omics fields, such as whole transcriptome analysis, epigenomics, and proteomics.

CONCLUSION

The challenges of personalized medicine along with the necessity of simultaneously assessing numerous new biomarkers require the implementation and execution of new techniques in molecular pathology whose complexity is steadily increasing.

Adverse events associated with immune checkpoint inhibitors in non-small cell lung cancer: a safety analysis of clinical trials and FDA pharmacovigilance system

Objectives

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of non-small cell lung cancer (NSCLC). However, the application of ICIs can also cause treatment-related adverse events (trAEs) and immune-related adverse events (irAEs). This study was to evaluate both the irAEs and trAEs of different ICI strategies for NSCLC based on randomized clinical trials (RCTs). The study also examined real-world pharmacovigilance data from the Food and Drug Administration Adverse Event Reporting System (FAERS) regarding claimed ICI-associated AEs in clinical practice.

Methods

Based on Pubmed, Embase, Medline, and the Cochrane CENTRAL, we retrieved RCTs comparing ICIs with chemotherapy drugs or with different ICI regimens for the treatment of NSCLC up to October 20, 2023. Bayesian network meta-analysis (NMA) was performed using odds ratios (ORs) with 95% credible intervals (95%CrI). Separately, a retrospective pharmacovigilance study was performed based on FAERS database, extracting ICI-associated AEs in NSCLC patients between the first quarter (Q1) of 2004 and Q4 of 2023. The proportional reports reporting odds ratio was calculated to analyze the disproportionality.

Results

The NMA included 51 RCTs that involved a total of 26,958 patients with NSCLC. Based on the lowest risk of any trAEs, cemiplimab, tislelizumab, and durvalumab were ranked as the best. Among the agents associated with the lowest risk of grades 3-5 trAEs, tislelizumab, avelumab, and nivolumab were most likely to rank highest. As far as any or grades 3-5 irAEs are concerned, atezolizumab plus bevacizumab plus chemotherapy is considered the most safety option. However, it is associated with a high risk of grades 3-5 trAEs. As a result of FAERS pharmacovigilance data analysis, 9,420 AEs cases have been identified in 7,339 NSCLC patients treated with ICIs, and ICIs were related to statistically significant positive signal with 311 preferred terms (PTs), and comprehensively investigated and identified those AEs highly associated with ICIs. In total, 152 significant signals were associated with Nivolumab, with malignant neoplasm progression, death, and hypothyroidism being the most frequent PTs.

Conclusion

These findings revealed that ICIs differed in their safety profile. ICI treatment strategies can be improved and preventive methods can be developed for NSCLC patients based on our results.

Genetic analysis of cervical cancer with lymph node metastasis

OBJECTIVE

To find out the differences in gene characteristics between cervical cancer patients with and without lymph node metastasis, and to provide reference for therapy.

METHODS

From January 2018 to June 2022, recurrent cervical cancer patients 39 cases with lymph node metastasis and 73 cases without lymph node metastasis underwent testing of 1,021 cancer-related genes by next-generation sequencing. Maftools software was used to analyze somatic single nucleotide/insertion-deletion variation mutation, co-occurring mutation, cosmic mutation characteristics, oncogenic signaling pathways.

RESULTS

EP300 and FBXW7 were significantly enriched in lymph node-positive patients. Lymph node-positive patients with EP300 or FBXW7 mutations had lower overall survival (OS) after recurrence. Both lymph node-positive and -negative patients had plenty of co-occurring mutations but few mutually exclusive mutations. Lymph node-positive co-occurring mutation number ≥6 had lower OS, while lymph node-negative co-occurring mutation number ≥3 had lower OS after recurrence. The etiology of SBS3 was defects in DNA double strand break repair by homologous recombination, which exclusively exist in lymph node-positive patients. There was no difference in median tumor mutation burden (TMB) between positive and negative lymph nodes, but TMB was significantly associated with PIK3CA mutation.

CONCLUSION

The somatic SNV/Indels of EP300 and FBXW7, SBS3 homologous recombination-mediated DNA repair defect were enriched in lymph node-positive patients. For lymph node-positive patients, EP300 or FBXW7 mutations predicted poor prognosis. No matter lymph node-positive or negative, more co-occurring mutation number predicted poor prognosis. PIK3CA mutation may account for the higher TMB and help identify patients who benefit from immunotherapy.

The relative risk of immune checkpoint inhibitor pneumonitis in advanced non-small- cell lung cancer: Meta-analyses of controlled clinical trials

OBJECTIVE

Immune checkpoint inhibitor pneumonitis (CIP) is a prevalent form of immunotherapy-induced pulmonary toxicity, ranking among the leading causes of mortality associated with immune checkpoint inhibitors (ICIs). Despite its significance, the risk stratification of CIP in advanced non-small cell lung cancer (NSCLC) remains uncertain. In this study, we conducted a comprehensive analysis, comparing various factors such as histological types, treatment regimens, PD-L1 expression levels, and EGFR/ALK negativity in advanced NSCLC. Our investigation extends to evaluating the relative risk of developing CIP based on previous treatment history. This analysis aims to provide valuable insights for the identification of specific patient subgroups at higher risk, facilitating more effective risk management and precision therapy approaches.

METHODS

PubMed, Embase, and Cochrane databases were systematically searched up to February 16, 2023. We conducted a screening of randomized controlled trials (RCTs) that compared ICI monotherapy or its combination with chemotherapy in advanced NSCLC. The trials were categorized based on histological type, treatment regimen, PD-L1 expression level, EGFR/ALK-negative status, and prior treatment history. Subsequently, the data were stratified into five subgroups, and the occurrences of all-grades (1-5) and high-grades (3-5) pneumonia events were extracted. Odds ratios (OR) and corresponding 95% confidence intervals (CI) were then calculated for further analysis.

RESULTS

Twenty-two RCTs, encompassing 13,725 patients with advanced NSCLC, were included in this analysis. Regardless of histology (OR = 2.47, 95% CI 1.41-4.33, P = 0.002; OR = 1.84, 95% CI 1.10-3.09, P = 0.02), treatment regimen (OR = 3.27, 95% CI 2.00-5.35, P < 0.00001; OR = 2.91, 95% CI 1.98-4.27, P < 0.00001), PD-L1 expression level (OR = 5.11, 95% CI 2.58-10.12, P < 0.00001; OR = 5.15, 95% CI 2.48-10.70, P < 0.0001), negative EGFR/ALK expression (OR = 4.32, 95% CI 2.22-8.41, P < 0.0001; OR = 3.6, 95% CI 1.56-8.28, P = 0.003), whether there is a history of treatment (OR = 3.27, 95% CI 2.00-5.35, P < 0.00001; OR = 2.74, 95% CI 1.75-4.29, P < 0.0001), ICI use was associated with a higher risk of all-grade (1-5) and high-grade (3-5) pneumonia compared to chemotherapy. Subgroup analysis revealed that the squamous group, the ICI vs. combination chemotherapy (CT) group, the PD-L1 > 50% group, and the previously untreated group had a higher risk of developing all-grade and grade 3-5 CIP (P < 0.05).

CONCLUSIONS

In advanced NSCLC, ICI treatment was linked to an elevated risk of pneumonitis across all grades (1-5) as well as high-grade occurrences (3-5) compared to chemotherapy. Notably, individuals with squamous histology and high PD-L1 expression, along with those lacking a history of prior treatment, demonstrated a heightened susceptibility to developing immune-related pneumonitis of all grades (1-5) and high grades (3-5). These observations provide valuable insights for clinicians seeking to enhance the management of pulmonary toxicity associated with immunotherapy.

First-line immunotherapy efficacy in advanced squamous non-small cell lung cancer with PD-L1 expression ≥50%: a network meta-analysis of randomized controlled trials

Objective

The optimal first-line immunotherapy regimen for patients with PD-L1 expression ≥50% in squamous non-small cell lung cancer (Sq-NSCLC) remains uncertain. This study utilized net-work meta-analysis (NMA) to indirectly compare the efficacy of various first-line immuno-therapy regimens in this patient subset.

Methods

Systematic searches were conducted across PubMed, the Cochrane Library, Web of Science, and Embase databases for randomized controlled trials reporting overall survival (OS) and progression-free survival (PFS) outcomes. The search spanned from database inception to November 3, 2023. Bayesian network meta-analysis was employed for a comprehen-sive analysis. To ensure scientific rigor and transparency, this study is registered in the Interna-tional Prospective Register of Systematic Reviews (PROSPERO) under the registration number CRD42022349712.

Results

The NMA encompassed 9 randomized controlled trials (RCTs), involving 2170 patients and investigating 9 distinct immunotherapy regimens. For OS, the combination of camrelizumab and chemotherapy demonstrated the highest probability (36.68%) of efficacy, fol-lowed by cemiplimab (33.86%) and atezolizumab plus chemotherapy (23.87%). Regarding PFS, the camrelizumab and chemotherapy combination had the highest probability (39.70%) of efficacy, followed by pembrolizumab (22.88%) and pembrolizumab plus chemotherapy (17.69%). Compared to chemotherapy, first-line treatment with immune checkpoint inhibitors (ICIs) in Sq-NSCLC pa-tients exhibited significant improvements in OS (HR 0.59, 95% CI 0.47-0.75) and PFS (HR 0.44, 95% CI 0.37-0.52).

Conclusion

This study suggests that, for Sq-NSCLC patients with PD-L1 expression ≥50%, the first-line immunotherapy regimen of camrelizumab plus chemotherapy provides superior OS and PFS outcomes. Furthermore, ICIs demonstrate enhanced efficacy compared to chemotherapy in this patient population.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier: CRD 42022349712.

Cost-effectiveness analysis of durvalumab, tremelimumab, and etoposide-platinum in first-line treatment of extensive-stage small cell lung cancer

BACKGROUND

Durvalumab plus etoposide-platinum (DEP) showed sustained overall survival improvements in patients with extensive-stage small-cell lung cancer (ES-SCLC) compared to etoposide-platinum (EP), but adding tremelimumab to DEP (DTEP) did not significantly improve outcomes. A third-party payer perspective is taken here to evaluate the cost-effectiveness of DTEP, DEP, and EP for ES-SCLC.

METHODS

The cost-effectiveness was evaluated by partitioning survival models into 3 mutually exclusive health states. In this model, clinical characteristics and outcomes were obtained from the CASPIAN. Model robustness was evaluated through 1-way deterministic and probabilistic sensitivity analyses. Outcome measurements included costs, quality-adjusted life-years (QALYs), incremental cost-effectiveness ratio, life-years, incremental net health benefit, and incremental net monetary benefit. The analysis was conducted with a 10-year lifetime horizon in a United States setting.

RESULTS

Compared with EP, DEP, and DTEP were associated with an increment of 0.480 and 0.313 life-years, and an increment of 0.247 and 0.165 QALYs, as well as a $139,788 and $170,331 increase in cost per patient. The corresponding ICERs were $565,807/QALY and $1033,456/QALY, respectively. The incremental net health benefit and incremental net monetary benefit of DEP or DTEP were -0.685 QALYs and -$102,729, or -0.971 QALYs and -$145,608 at a willingness to pay threshold of $150,000/QALY, respectively. Compared with DTEP, DEP was dominated. DTEP and DEP were 100% unlikely to be cost-effective if the willingness to pay threshold was $150,000/QALY. DEP was cost-effective compared to EP when durvalumab was priced below $0.994/mg. Compared with EP, DEP, and DTEP were unlikely to be considered cost-effective across all subgroups.

CONCLUSION

DEP and DTEP were not cost-effective options in the first-line treatment for ES-SCLC compared with EP, from the third-party payer perspective in the United States. Compared with DTEP, DEP was dominated.

Efficacy and safety of bispecific antibodies vs. immune checkpoint blockade combination therapy in cancer: a real-world comparison

Emerging tumor immunotherapy methods encompass bispecific antibodies (BSABs), immune checkpoint inhibitors (ICIs), and adoptive cell immunotherapy. BSABs belong to the antibody family that can specifically recognize two different antigens or epitopes on the same antigen. These antibodies demonstrate superior clinical efficacy than monoclonal antibodies, indicating their role as a promising tumor immunotherapy option. Immune checkpoints are also important in tumor immunotherapy. Programmed cell death protein-1 (PD-1) is a widely acknowledged immune checkpoint target with effective anti-tumor activity. PD-1 inhibitors have demonstrated notable therapeutic efficacy in treating hematological and solid tumors; however, more than 50% of patients undergoing this treatment exhibit a poor response. However, ICI-based combination therapies (ICI combination therapies) have been demonstrated to synergistically increase anti-tumor effects and immune response rates. In this review, we compare the clinical efficacy and side effects of BSABs and ICI combination therapies in real-world tumor immunotherapy, aiming to provide evidence-based approaches for clinical research and personalized tumor diagnosis and treatment.

Facts and Hopes on Biomarkers for Successful Early Clinical Immunotherapy Trials: Innovative Patient Enrichment Strategies

Despite the clinical validation and unequivocal benefit to patients, the development of cancer immunotherapies is facing some key challenges and the attrition rate in early phases of development remains high. Identifying the appropriate patient population that would benefit most from the drug is on the critical path for successful clinical development. We believe that a systematic implementation of patient enrichment strategies early in the drug development process and trial design, is the basis for an innovative, more efficient, and leaner clinical development to achieve earlier a clear proof of concept or proof of failure. In this position article, we will describe and propose key considerations for the implementation of patient enrichment strategies as an opportunity to provide decision-enabling data earlier in the drug development process. We introduce an innovative multidimensional tool for immuno-oncology drug development that focuses on facilitating the identification and prioritization of enrichment-relevant biomarkers, based on the drug mechanism of action. To illustrate its utility, we discuss patient enrichment examples and use a case in the field of cancer immunotherapy, together with technical and regulatory considerations. Overall, we propose to implement fit for purpose enrichment strategies for all investigational drugs as early as possible in the development process. We believe that this will increase the success rate of immuno-oncology clinical trials, and eventually bring new and better medicines to patients faster.

Identification of lung adenocarcinoma subtypes and a prognostic signature based on activity changes of the hallmark and immunologic gene sets

Background

Lung adenocarcinoma (LUAD) has a complex tumor heterogeneity. Our research attempts to clearness LUAD subtypes and build a reliable prognostic signature according to the activity changes of the hallmark and immunologic gene sets.

Methods

According to The Cancer Genome Atlas (TCGA) - LUAD dataset, changes in marker and immune gene activity were analyzed, followed by identification of prognosis-related differential gene sets (DGSs) and their related LUAD subtypes. Survival analysis, correlation with clinical characteristics, and immune microenvironment assessment for subtypes were performed. Moreover, the differentially expressed genes (DEGs) between different subtypes were identified, followed by the construction of a prognostic risk score (RS) model and nomogram model. The tumor mutation burden (TMB) and tumor immune dysfunction and exclusion (TIDE) of different risk groups were compared.

Results

Two LUAD subtypes were determined according to the activity changes of the hallmark and immunologic gene sets. Cluster 2 had worse prognosis, more advanced tumor and clinical stages than cluster 1. Moreover, a prognostic RS signature was established using two LUAD subtype-related DEGs, which could stratify patients at different risk levels. Nomogram model incorporated RS and clinical stage exerted good prognostic performance in LUAD patients. A shorter survival time and higher TMB were observed in the high-risk patients.

Conclusions

Our findings revealed that our constructed prognostic signature could exactly predict the survival status of LUAD cases, which was helpful in predicting the prognosis and guiding personalized therapeutic strategies for LUAD.

Nivolumab Plus Chemotherapy in Epidermal Growth Factor Receptor-Mutated Metastatic Non-Small-Cell Lung Cancer After Disease Progression on Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors: Final Results of CheckMate 722

PURPOSE

The phase III CheckMate 722 trial (ClinicalTrials.gov identifier: NCT02864251) evaluated nivolumab plus chemotherapy versus chemotherapy in patients with epidermal growth factor receptor (EGFR)-mutated metastatic non-small-cell lung cancer (NSCLC) after disease progression on EGFR tyrosine kinase inhibitors (TKIs).

METHODS

Patients with disease progression after first- or second-generation EGFR TKI therapy (without EGFR T790M mutation) or osimertinib (with/without T790M mutation) were randomly assigned 1:1 to nivolumab (360 mg once every 3 weeks) plus platinum-doublet chemotherapy (once every 3 weeks) or platinum-doublet chemotherapy alone (once every 3 weeks) for four cycles. Primary end point was progression-free survival (PFS). Secondary end points included 9- and 12-month PFS rates, overall survival (OS), objective response rate (ORR), and duration of response (DOR).

RESULTS

Overall, 294 patients were randomly assigned. At final analysis (median follow-up, 38.1 months), PFS was not significantly improved with nivolumab plus chemotherapy versus chemotherapy (median, 5.6 v 5.4 months; hazard ratio [HR], 0.75 [95% CI, 0.56 to 1.00]; P = .0528), with 9- and 12-month PFS rates of 25.9% versus 19.8%, and 21.2% versus 15.9%, respectively. Post hoc PFS subgroup analyses showed a trend favoring nivolumab plus chemotherapy in patients with tumors harboring sensitizing EGFR mutations (HR, 0.72 [95% CI, 0.54 to 0.97]), one line of previous EGFR TKI (0.72 [95% CI, 0.54 to 0.97]), or both (0.64 [95% CI, 0.47 to 0.88]). Median OS was 19.4 months with nivolumab plus chemotherapy versus 15.9 months with chemotherapy, while ORR was 31.3% versus 26.7%, and median DOR was 6.7 versus 5.6 months, respectively. Grade 3/4 treatment-related adverse events occurred in 44.7% and 29.4% of patients treated with nivolumab plus chemotherapy and chemotherapy alone, respectively.

CONCLUSION

Nivolumab plus chemotherapy did not significantly improve PFS versus chemotherapy in patients with EGFR-mutated metastatic NSCLC previously treated with EGFR TKIs. No new safety signals were identified.

Prognostic and predictive biomarkers with therapeutic targets in nonsmall-cell lung cancer: A 2023 update on current development, evidence, and recommendation

BACKGROUND

Since the publication of the original work in 2014, significant progress has been made in the characterization of genomic alterations that drive oncogenic addiction of nonsmall cell lung cancer (NSCLC) and how the immune system can leverage non-oncogenic pathways to modulate therapeutic outcomes. This update evaluates and validates the recent and emerging data for prognostic and predictive biomarkers with therapeutic targets in NSCLC.

DATA SOURCES

We performed a literature search from January 2015 to October 2023 using the keywords non-small cell lung cancer, clinical practice guidelines, gene mutations, genomic assay, immune cancer therapy, circulating tumor DNA, predictive and prognostic biomarkers, and targeted therapies.

STUDY SELECTION AND DATA EXTRACTION

We identified, reviewed, and evaluated relevant clinical trials, meta-analyses, seminal articles, and published clinical practice guidelines in the English language.

DATA SYNTHESIS

Regulatory-approved targeted therapies include those somatic gene alterations of EGFR ("classic" mutations, exon 20 insertion, and rare EGFR mutations), ALK, ROS1, BRAF V600, RET, MET, NTRK, HER2, and KRAS G12C. Data for immunotherapy and circulating tumor DNA in next-generation sequencing are considered emerging, whereas the predictive role for PIK3CA gene mutation is insufficient.

CONCLUSIONS

Advances in sequencing and other genomic technologies have led to identifying novel oncogenic drivers, novel resistance mechanisms, and co-occurring mutations that characterize NSCLC, creating further therapeutic opportunities. The benefits associated with immunotherapy in the perioperative setting hold initial promise, with their long-term results awaiting.

Immune checkpoint inhibitors for metastatic uveal melanoma: a meta-analysis

Several studies have evaluated immune checkpoint inhibitors (ICIs) for metastatic uveal melanoma; however, the efficacy of ICIs in the previous studies varied greatly. In this systematic review, we searched for prospective or retrospective studies on single or dual-ICIs for metastatic uveal melanoma treatment. A random-effect model meta-analysis with generic inverse-variance was conducted, and 36 articles representing 41 cohorts of 1414 patients with metastatic uveal melanoma were included. The pooled outcomes were as follows: objective response rate (ORR) was 5.6% (95% confidence interval [95%CI] 3.7-7.5%; I2, 36%), disease control rate (DCR) was 32.5% (95% CI 27.2-37.7%; I2, 73%), median progression-free survival was 2.8 months (95% CI 2.7-2.9 months; I2, 26%), and median overall survival (OS) was 11.2 months (95% CI 9.6-13.2 months; I2, 74%). Compared to single-agent ICI, dual ICI led to better ORR (single-agent: 3.4% [95% CI 1.8-5.1]; dual-agent: 12.4% [95% CI 8.0-16.9]; P < 0.001), DCR (single-agent: 29.3%, [95% CI 23.4-35.2]; dual-agent: 44.3% [95% CI 31.7-56.8]; P = 0.03), and OS (single-agent: 9.8 months [95% CI 8.0-12.2]; dual-agent: 16.3 months [95% CI 13.5-19.7]; P < 0.001). Our analysis provided treatment outcomes as described above. Dual-ICIs appear better than single-agent ICIs for the treatment of metastatic uveal melanoma.

Multiparameter spectral CT-based radiomics in predicting the expression of programmed death ligand 1 in non-small-cell lung cancer

AIM

To explore the value of radiomics for predicting the expression of programmed death ligand 1 (PD-L1) in non-small-cell lung cancer (NSCLC) based on multiparameter spectral computed tomography (CT) images.

MATERIALS AND METHODS

A total of 220 patients with NSCLC were enrolled retrospectively and divided into the training (n=176) and testing (n=44) cohorts. The radiomics features were extracted from the conventional CT images, mono-energy 40 keV images, iodine density (ID) maps, Z-effective maps, and electron density maps. The logistic regression (LR) and support vector machine (SVM) algorithms were employed to build models based on radiomics signatures. The prediction abilities were qualified by the area under the curve (AUC) obtained from the receiver operating characteristic (ROC) curve. Internal validation was performed on the independent testing dataset.

RESULTS

The combined model for PD-L1 ≥1%, which consisted of the radiomics score (rad-score; p<0.0001), white blood cell (WBC; p=0.027) counts, and air bronchogram (p=0.003), reached the highest performance with the AUCs of 0.873 and 0.917 in the training and testing dataset, respectively, which was better than the radiomics model with the AUCs of 0.842 and 0.886. The combined model for PD-L1 ≥50%, which consisted of rad-score (p<0.0001) and WBC counts (p=0.027), achieved the highest performance in the training and testing dataset with AUCs of 0.932 and 0.903, respectively, which was better than the radiomics model with AUCs of 0.920 and 0.892, respectively.

CONCLUSION

The radiomics model based on the multiparameter images of spectral CT can predict the expression level of PD-L1 in NSCLC. The combined model can obtain higher prediction efficiency and serves as a promising method for immunotherapy selection.

A Novel Signature Based on m6A Regulator-Mediated Genes Along Glycolytic Pathway Predicts Prognosis and Immunotherapy Responses of Gastric Cancer Patients

N6-methyladenosine (m6A) modification is involved in many aspects of gastric cancer (GC). Moreover, m6A and glycolysis-related genes (GRGs) play important roles in immunotherapeutic and prognostic implication of GC. However, GRGs involved in m6A regulation have never been analyzed comprehensively in GC. Herein, the study aims to identify and validate a novel signature based on m6A-related GRGs in GC patients. Therefore, a m6A-related GRGs signature is established, which can predict the survival of patients with GC and remain an independent prognostic factor in multivariate analyses. Clinical significance of the model is well validated in internal cohort and independent validation cohort. In addition, the expression levels of risk model-related GRGs in clinical samples are validated. Consistent with the database results, all model genes are up-regulated in expression except DCN. After regrouping the patients based on this risk model, the study can effectively distinguish between them in respect to immune-cell infiltration microenvironment and immunotherapeutic response. Additionally, candidate drugs targeting risk model-related GRGs are confirmed. Finally, a nomogram combining risk scores and clinical parameters is created, and calibration plots show that the nomogram can accurately predict survival. This risk model can serve as a reliable assessment tool for predicting prognosis and immunotherapeutic responses in GC patients.

Comprehensive Analysis of N6-Methylandenosine-Related lncRNAs in Clear Cell Renal Cell Carcinoma: A Correlation With Prognosis, Tumor Progression, and Therapeutic Response

This study aims to develop a prognostic signature based on m6A-related lncRNAs for clear cell renal cell carcinoma (ccRCC). Differential expression analysis and Pearson correlation analysis were used to identify m6A-related lncRNAs associated with patient outcomes in The Cancer Genome Atlas (TCGA) database. Our approach led to the development of an m6A-related lncRNA risk score (MRLrisk), formulated using six identified lncRNAs: NFE4, AL008729.2, AL139123.1, LINC02154, AC124854.1 and ARHGAP31-AS1. Higher MRLrisk was identified as a risk factor for patients' prognosis in ccRCC. Furthermore, an MRLrisk-based nomogram was developed and demonstrated as a reliable tool for prognosis prediction in ccRCC. Enrichment analysis and tumor mutation signature studies were conducted to investigate MRLrisk-related biological phenotypes. The tumor immune dysfunction and exclusion (TIDE) score was employed to infer patients' response to immunotherapy, indicating a negative correlation between high MRLrisk and immunotherapy response. Our focus then shifted to LINC02154 for deeper exploration. We assessed LINC02154 expression in 28 ccRCC/normal tissue pairs and 3 ccRCC cell lines through quantitative real-time polymerase chain reaction (qRT-PCR). Functional experiments, including EdU incorporation, flow cytometry and transwell assays, were performed to assess the role of LINC02154 in ccRCC cell functions, discovering that its downregulation hinders cancer cell proliferation and migration. Furthermore, the influence of LINC02154 on ccRCC cells' sensitivity to Sunitinib was explored using CCK-8 assays, demonstrating that decreased LINC02154 expression increases Sunitinib sensitivity. In summary, this study successfully developed an MRLrisk model with significant prognostic value for ccRCC and established LINC02154 as a critical biomarker and prospective therapeutic target in ccRCC management.

Combining Genomic Biomarkers to Guide Immunotherapy in Non-Small Cell Lung Cancer

PURPOSE

The clinical value of STK11, KEAP1, and EGFR alterations for guiding immune checkpoint blockade (ICB) therapy in non-small cell lung cancer (NSCLC) remains controversial, as some patients with these proposed resistance biomarkers show durable ICB responses. More specific combinatorial biomarker approaches are urgently needed for this disease.

EXPERIMENTAL DESIGN

To develop a combinatorial biomarker strategy with increased specificity for ICB unresponsiveness in NSCLC, we performed a comprehensive analysis of 254 patients with NSCLC treated with ligand programmed death-ligand 1 (PD-L1) blockade monotherapy, including a discovery cohort of 75 patients subjected to whole-genome sequencing (WGS), and an independent validation cohort of 169 patients subjected to tumor-normal large panel sequencing. The specificity of STK11/KEAP1/EGFR alterations for ICB unresponsiveness was assessed in the contexts of a low (<10 muts/Mb) or high (≥10 muts/Mb) tumor mutational burden (TMB).

RESULTS

In low TMB cases, STK11/KEAP1/EGFR alterations were highly specific biomarkers for ICB resistance, with 0/15 (0.0%) and 1/34 (2.9%) biomarker-positive patients showing treatment benefit in the discovery and validation cohorts, respectively. This contrasted with high TMB cases, where 11/13 (85%) and 15/34 (44%) patients with at least one STK11/KEAP1/EGFR alteration showed durable treatment benefit in the discovery and validation cohorts, respectively. These findings were supported by analyses of progression-free survival and overall survival.

CONCLUSIONS

The unexpected ICB responses in patients carrying resistance biomarkers in STK11, KEAP1, and EGFR were almost exclusively observed in patients with a high TMB. Considering these alterations in context, the TMB offered a highly specific combinatorial biomarker strategy for limiting overtreatment in NSCLC.

A TGF-β signaling-related lncRNA signature for prediction of glioma prognosis, immune microenvironment, and immunotherapy response

AIMS

The dysregulation of TGF-β signaling is a crucial pathophysiological process in tumorigenesis and progression. LncRNAs have diverse biological functions and are significant participants in the regulation of tumor signaling pathways. However, the clinical value of lncRNAs related to TGF-β signaling in glioma is currently unclear.

METHODS

Data on glioma's RNA-seq transcriptome, somatic mutation, DNA methylation data, and clinicopathological information were derived from the CGGA and TCGA databases. A prognostic lncRNA signature was constructed by Cox and LASSO regression analyses. TIMER2.0 database was utilized to deduce immune infiltration characteristics. "ELMER v.2" was used to reconstruct TF-methylation-gene regulatory network. Immunotherapy and chemotherapy response predictions were implemented by the TIDE algorithm and GDSC database, respectively. In vitro and in vivo experiments were conducted to verify the results and clarify the regulatory mechanism of lncRNA.

RESULTS

In glioma, a TGF-β signaling-related 15-lncRNA signature was constructed, including AC010173.1, HOXA-AS2, AC074286.1, AL592424.1, DRAIC, HOXC13-AS, AC007938.1, AC010729.1, AC013472.3, AC093895.1, AC131097.4, AL606970.4, HOXC-AS1, AGAP2-AS1, and AC002456.1. This signature proved to be a reliable prognostic tool, with high risk indicating an unfavorable prognosis and being linked to malignant clinicopathological and genomic mutation traits. Risk levels were associated with different immune infiltration landscapes, where high risk was indicative of high levels of macrophage infiltration. In addition, high risk also suggested better immunotherapy and chemotherapy response. cg05987823 was an important methylation site in glioma progression, and AP-1 transcription factor family participated in the regulation of signature lncRNA expression. AGAP2-AS1 knockdown in in vitro and in vivo experiments inhibited the proliferation, migration, and invasion of glioma cells, as well as the growth of glioma, by downregulating the expression levels of NF-κB and ERK 1/2 in the TGF-β signaling pathway.

CONCLUSIONS

A prognostic lncRNA signature of TGF-β signaling was established in glioma, which can be used for prognostic judgment, immune infiltration status inference, and immunotherapy response prediction. AGAP2-AS1 plays an important role in glioma progression.

Randomized phase 2 trial of tremelimumab and durvalumab in combination versus sequentially in recurrent platinum-resistant ovarian cancer

BACKGROUND

Single-agent immune checkpoint inhibitors (ICIs) have demonstrated limited responses in recurrent ovarian cancer; however, 30%-40% of patients achieve stable disease. The primary objective was to estimate progression-free survival (PFS) after sequential versus combination cytotoxic T-lymphocyte antigen 4 and programmed death ligand 1 ICIs in patients with platinum-resistant high-grade serous ovarian cancer (HGSOC).

METHODS

Patients were randomized to a sequential arm (tremelimumab followed by durvalumab on progression) or a combination arm (tremelimumab plus durvalumab, followed by durvalumab) via a Bayesian adaptive design that made it more likely for patients to be randomized to the more effective arm. The primary end point was immune-related PFS (irPFS).

RESULTS

Sixty-one subjects were randomized to sequential (n = 38) or combination therapy (n = 23). Thirteen patients (34.2%) in the sequential arm received durvalumab. There was no difference in PFS in the sequential arm (1.84 months; 95% CI, 1.77-2.17 months) compared with the combination arm (1.87 months; 95% CI, 1.77-2.43 months) (p = .402). In the sequential arm, no responses were observed, although 12 patients (31.6%) demonstrated stable disease. In the combination arm, two patients (8.7%) had partial response, whereas one patient (4.4%) had stable disease. Adverse events were consistent with those previously reported for ICIs. Patient-reported outcomes were similar in both arms.

CONCLUSIONS

There was no difference in irPFS for combination tremelimumab plus durvalumab compared to tremelimumab alone (administered as part of a sequential treatment strategy) in a heavily pretreated population of patients with platinum-resistant HGSOC. Response rates were comparable to prior reports, although the combination regimen did not add significant benefit, as has been previously described.

The prognostic biomarker TPGS2 is correlated with immune infiltrates in pan-cancer: a bioinformatics analysis

Background

Tubulin polyglutamylase complex subunit 2 (TPGS2) is an element of the neuronal polyglutamylase complex that plays a role in the post-translational addition of glutamate residues to C-terminal tubulin tails. Recent research has shown that TPGS2 is associated with some tumors, but the roles of TPGS2 in tumor immunity remain unclear.

Methods

The research data were mainly sourced from The Cancer Genome Atlas. The data were analyzed to identify potential correlations between TPGS2 expression and survival, gene alterations, the tumor mutational burden (TMB), microsatellite instability (MSI), immune infiltration, and various immune-related genes across various cancers. The Wilcoxon rank-sum test was used to identify the significance. A log-rank test and univariate Cox regression analysis were performed to assess the survival state of the patients. Spearman's correlation coefficients were used to show the correlations.

Results

TPGS2 exhibited abnormal expression patterns in most types of cancers, and has promising prognostic potential in adrenocortical carcinoma and liver hepatocellular carcinoma. Further, TPGS2 expression was significantly correlated with molecular and immune subtypes. Moreover, the single-cell analyses showed that the expression of TPGS2 was associated with the cell cycle, metastasis, invasion, inflammation, and DNA damage. In addition, the immune cell infiltration analysis and gene-set enrichment analysis demonstrated that a variety of immune cells and immune processes were associated with TPGS2 expression in various cancers. Further, immune regulators, including immunoinhibitors, immunostimulators, the major histocompatibility complex, chemokines, and chemokine receptors, were correlated with TPGS2 expression in different cancer types. Finally, the TMB and MSI, which have been identified as powerful predictors of immunotherapy, were shown to be correlated with the expression of TPGS2 across human cancers.

Conclusions

TPGS2 is aberrantly expressed in most cancer tissues and might be associated with immune cell infiltration in the tumor microenvironment. TPGS2 could serve not only as a biomarker for predicting clinical outcomes, but also as a promising biomarker for evaluating and developing new approaches to immunotherapy in many types of cancers, especially colon adenocarcinoma and stomach adenocarcinoma.

Multi-omics and artificial intelligence predict clinical outcomes of immunotherapy in non-small cell lung cancer patients

In recent years, various types of immunotherapy, particularly the use of immune checkpoint inhibitors targeting programmed cell death 1 or programmed death ligand 1 (PD-L1), have revolutionized the management and prognosis of non-small cell lung cancer. PD-L1 is frequently used as a biomarker for predicting the likely benefit of immunotherapy for patients. However, some patients receiving immunotherapy have high response rates despite having low levels of PD-L1. Therefore, the identification of this group of patients is extremely important to improve prognosis. The tumor microenvironment contains tumor, stromal, and infiltrating immune cells with its composition differing significantly within tumors, between tumors, and between individuals. The omics approach aims to provide a comprehensive assessment of each patient through high-throughput extracted features, promising a more comprehensive characterization of this complex ecosystem. However, features identified by high-throughput methods are complex and present analytical challenges to clinicians and data scientists. It is thus feasible that artificial intelligence could assist in the identification of features that are beyond human discernment as well as in the performance of repetitive tasks. In this paper, we review the prediction of immunotherapy efficacy by different biomarkers (genomic, transcriptomic, proteomic, microbiomic, and radiomic), together with the use of artificial intelligence and the challenges and future directions of these fields.

Tumor mutational burden for the prediction of PD-(L)1 blockade efficacy in cancer: challenges and opportunities

Tumor mutational burden (TMB) is a biomarker that measures the number of somatic mutations in a tumor's genome. TMB has emerged as a predictor of response to immune checkpoint inhibitors (ICIs) in various cancer types, and several studies have shown that patients with high TMB have better outcomes when treated with programmed death-ligand 1-based therapies. Recently, the Food and Drug Administration has approved TMB as a companion diagnostic for the use of pembrolizumab in solid tumors. However, despite its potential, the use of TMB as a biomarker for immunotherapy efficacy is limited by several factors. Here we review the limitations of TMB in predicting immunotherapy outcomes in patients with cancer and discuss potential strategies to optimize its use in the clinic.

Immune Cytolytic Activity and Strategies for Therapeutic Treatment

Intratumoral immune cytolytic activity (CYT), calculated as the geometric mean of granzyme-A (GZMA) and perforin-1 (PRF1) expression, has emerged as a critical factor in cancer immunotherapy, with significant implications for patient prognosis and treatment outcomes. Immune checkpoint pathways, the composition of the tumor microenvironment (TME), antigen presentation, and metabolic pathways regulate CYT. Here, we describe the various methods with which we can assess CYT. The detection and analysis of tumor-infiltrating lymphocytes (TILs) using flow cytometry or immunohistochemistry provide important information about immune cell populations within the TME. Gene expression profiling and spatial analysis techniques, such as multiplex immunofluorescence and imaging mass cytometry allow the study of CYT in the context of the TME. We discuss the significant clinical implications that CYT has, as its increased levels are associated with positive clinical outcomes and a favorable prognosis. Moreover, CYT can be used as a prognostic biomarker and aid in patient stratification. Altering CYT through the different methods targeting it, offers promising paths for improving treatment responses. Overall, understanding and modulating CYT is critical for improving cancer immunotherapy. Research into CYT and the factors that influence it has the potential to transform cancer treatment and improve patient outcomes.

Analysis of tumor mutational burden and mutational landscape comparing whole-exome sequencing and comprehensive genomic profiling in patients with resectable early-stage non-small-cell lung cancer

Background

Identifying actionable driver mutations via tissue-based comprehensive genomic profiling (CGP) is paramount in treatment decisions for metastatic non-squamous, non-small-cell lung cancer (NSCLC). However, the role of CGP remains elusive in resectable NSCLC. Here, we elucidate the feasibility of CGP in early-stage NSCLC Korean patients and compare the tumor mutational burden (TMB) and mutation landscape using three different platforms.

Methods

All surgically resected NSCLC samples (N = 96) were analyzed to assess the concordance in TMB calculation and targetable mutations using whole-exome sequencing (WES) and TruSight Oncology 500 (TSO500). In all, 26 samples were analyzed with Foundation One CDx Assay (F1CDx). Programmed death-ligand 1 (PD-L1) expression was evaluated using Vectra Polaris.

Results

Stage distribution post-surgery was 80% I (N = 77) and 20% II (N = 19). Ninety-nine percent (N = 95) were adenocarcinoma. The median TMB with WES and TSO500 was 1.6 and 4.7 mut/Mb, respectively (p < 0.05). Using all three platforms, the median TMB was 1.9, 5.5, and 4 mut/Mb for WES, TSO500, and F1CDx, respectively (p = 0.0048). Linear regression analysis of TMB values calculated between WES and TSO500 resulted in a concordance correlation coefficient of 0.83. For the PD-L1 tumor proportion score of <1% (negative, N = 18), 1-49% (low, N = 68), and ⩾50% (high, N = 10), the R2 values were 0.075, 0.79, and 0.95, respectively. The R2 values for TMB concordance were variable between the three platforms. Mutation landscape revealed EGFR mutation (51%, N = 49) as the most common actionable driver mutation, comprising L858R (N = 22), E19del (N = 20), and other non-common EGFR mutations (N = 7).

Conclusion

TSO500 and F1CDx showed robust analytical performance for TMB assessment with TSO500 showing stronger concordance of TMB with high PD-L1 expression. As the paradigm for the management of early-resected NSCLC continues to evolve, understanding TMB and the mutation landscape may help advance clinical outcomes for this subset of patients.

Blood-based biomarkers in patients with non-small cell lung cancer treated with immune checkpoint blockade

The paradigm of non-small cell lung cancer (NSCLC) treatment has been profoundly influenced by the development of immune checkpoint inhibitors (ICI), but the range of clinical responses observed among patients poses significant challenges. To date, analyses of tumor biopsies are the only parameter used to guide prognosis to ICI therapy. Tumor biopsies, however, are often difficult to obtain and tissue-based biomarkers are limited by intratumoral heterogeneity and temporal variability. In response, there has been a growing emphasis on the development of "liquid biopsy"‒ derived biomarkers, which offer a minimally invasive means to dynamically monitor the immune status of NSCLC patients either before and/or during the course of treatment. Here we review studies in which multiple blood-based biomarkers encompassing circulating soluble analytes, immune cell subsets, circulating tumor DNA, blood-based tumor mutational burden, and circulating tumor cells have shown promising associations with the clinical response of NSCLC patients to ICI therapy. These investigations have unveiled compelling correlations between the peripheral immune status of patients both before and during ICI therapy and patient outcomes, which include response rates, progression-free survival, and overall survival. There is need for rigorous validation and standardization of these blood-based assays for broader clinical application. Integration of multiple blood-based biomarkers into comprehensive panels or algorithms also has the potential to enhance predictive accuracy. Further research aimed at longitudinal monitoring of circulating biomarkers is also crucial to comprehend immune dynamics and resistance mechanisms and should be used alongside tissue-based methods that interrogate the tumor microenvironment to guide treatment decisions and may inform on the development of novel therapeutic strategies. The data reviewed here reinforce the opportunity to refine patient stratification, optimize treatments, and improve outcomes not only in NSCLC but also in the wider spectrum of solid tumors undergoing immunotherapy.

Risk and Incidence of Endocrine Immune-Related Adverse Effects Under Checkpoint Inhibitor Mono- or Combination Therapy in Solid Tumors: A Meta-Analysis of Randomized Controlled Trials

CONTEXT

Few meta-analyses on incidence of endocrine immune-related adverse effects (eirAEs) have been published and many trials have been published since.

OBJECTIVE

We performed a comprehensive meta-analysis with updated literature to assess risk and incidence of eirAEs of any grade and grade 3 to 5 by immune checkpoint inhibitor (ICI) monotherapy or combination therapy in solid tumors.

METHODS

An electronic search using PubMed/Medline, Embase, and the Cochrane Library was performed. Randomized controlled studies (RCTs) assessing eirAEs under ICI monotherapy or ICI combination therapy were selected. Stata software (v17) was used for statistical analyses and risk of bias was evaluated using Review Manager version 5.3.

RESULTS

A total of 69 RCTs with 80 independent reports, involving 42 886 patients, were included in the study. Meta-analysis revealed the following pooled estimates for risk ratio and incidence, respectively: for any grade hypothyroidism 7.81 (95% CI, 5.68-10.74, P < .0001) and 7.64% (95% CI, 6.23-9.17, P < .0001); significantly increased also for hyperthyroidism, hypophysitis/hypopituitarism, and adrenal insufficiency; and for insulin-dependent diabetes mellitus 1.52 (95% CI, 1.07-2.18, P = .02), and 0.087% (95% CI, 0.019-0.189, P = .0006), respectively. Meta-regression showed that combination of ICIs (nivolumab plus ipilimumab; durvalumab plus tremelimumab) is an independent risk factor for any grade hypophysitis/hypopituitarism, and that ICI agent is an independent factor of risk for adrenal insufficiency, but that cancer type is not an independent risk factor for eirAEs.

CONCLUSION

We showed that risk, independent from cancer type, and incidence of eirAEs are substantially increased with ICI therapy. Combination of ICIs increases risk for eirAEs, especially for hypophysitis/hypopituitarism.