Biomarkers of response to checkpoint inhibitors beyond PD-L1 in lung cancer

Assessment of PD-L1 expression and tumour infiltrating lymphocytes in early-stage non-small cell lung carcinoma with artificial intelligence algorithms

AIMS

To study programmed death ligand 1 (PD-L1) expression and tumour infiltrating lymphocytes (TILs) in patients with early-stage non-small cell lung carcinoma (NSCLC) with artificial intelligence (AI) algorithms.

METHODS

The study included samples from 50 early-stage NSCLCs. PD-L1 immunohistochemistry (IHC) stained slides (clone SP263) were scored manually and with two different AI tools (PathAI and Navify Digital Pathology) by three pathologists. TILs were digitally assessed on H&E and CD8 IHC stained sections with two different algorithms (PathAI and Navify Digital Pathology, respectively). The agreement between observers and methods for each biomarker was analysed. For PD-L1, the turn-around time (TAT) for manual versus AI-assisted scoring was recorded.

RESULTS

Agreement was higher in tumours with low PD-L1 expression regardless of the approach. Both AI-powered tools identified a significantly higher number of cases equal or above 1% PD-L1 tumour proportion score as compared with manual scoring (p=0.00015), a finding with potential therapeutic implications. Regarding TAT, there were significant differences between manual scoring and AI use (p value <0.0001 for all comparisons). The total TILs density with the PathAI algorithm and the total density of CD8+ cells with the Navify Digital Pathology software were significantly correlated (τ=0.49 (95% CI 0.37, 0.61), p value<0.0001).

CONCLUSIONS

This preliminary study supports the use of AI algorithms for the scoring of PD-L1 and TILs in patients with NSCLC.

A tumor cornification and immune-infiltration-based scheme for anti-PD-1 plus chemotherapy response in advanced squamous cell lung carcinoma

BACKGROUND

Anti-PD-1 immunotherapy plus chemotherapy (combo) exhibits significantly prolonged survival for squamous cell lung cancer (LUSC). An exploration of predictive biomarkers is still needed.

METHODS

High-throughput RNA sequencing (RNA-seq) of 349 LUSC samples from the randomized, multi-center, phase 3 trial ORIENT-12 (ClinicalTrials.gov: NCT03629925) was conducted for biomarker discovery, followed by flow cytometry and multiplex immunohistochemistry (mIHC) in additional clinical cohorts, and in vitro experiments were performed for verification.

RESULTS

A high abundance of activated CD8+ T and CD56bright natural killer (NK) cells benefited patients' outcomes (progression-free survival [PFS]; overall survival [OS]) with combo treatment. Tumor cornification level remarkably affected the infiltration of the two crucial immune cells. Thus, a novel scheme of LUSC immune infiltration and cornification characterization-based classification (LICC) was established for combo efficacy prediction. Patients who received combo treatment achieved significant PFS improvements in LICC1 (hazard ratio [HR] = 0.43, 95% confidence interval [CI]: 0.25-0.75, p = 0.0029) and LICC2 (HR = 0.32, 95% CI: 0.17-0.58, p = 0.0002) subtypes but not in the LICC3 subtype (HR = 0.86, 95% CI: 0.60-1.23, p = 0.4053). Via single-cell RNA-seq analysis, the tumor cornification signal was mainly mapped to SPRR3+ tumor cells, whose relationships with activated CD8+ T or CD56bright NK cells were verified using flow cytometry and mIHC. Our data suggest that SPRR3+ tumor cells might evade immune surveillance via the CD24-SIGLEC10 (M2 macrophage) axis to maintain a suppressive tumor microenvironment.

CONCLUSIONS

Tumor cornification greatly impacts immune infiltration, and the LICC scheme may guide clinical medication of anti-PD-1+chemo treatment in patients with LUSC.

FUNDING

The study was funded by the National Key R&D Program of China, the National Natural Science Foundation of China, Shanghia Multidisplinary Cooperation Building Project for Diagnosis and Treatment of Major Disease, and Innovent Biologics, Inc.

Durvalumab With or Without Tremelimumab in Combination With Chemotherapy in First-Line Metastatic NSCLC: Five-Year Overall Survival Outcomes From the Phase 3 POSEIDON Trial

INTRODUCTION

The primary analysis (median follow-up 34.9 mo across all arms) of the phase 3 POSEIDON study revealed a statistically significant overall survival (OS) improvement with first-line tremelimumab plus durvalumab and chemotherapy (T+D+CT) versus CT in patients with EGFR and ALK wild-type metastatic NSCLC (mNSCLC). D+CT had a trend for OS improvement versus CT that did not reach statistical significance. This article reports prespecified OS analyses after long-term follow-up (median >5 y).

METHODS

A total of 1013 patients were randomized (1:1:1) to T+D+CT, D+CT, or CT, stratified by tumor cell programmed cell death ligand-1 (PD-L1) expression (≥50% versus <50%), disease stage (IVA versus IVB), and tumor histologic type (squamous versus nonsquamous). Serious adverse events were collected during follow-up.

RESULTS

After a median follow-up of 63.4 months across all arms, T+D+CT had sustained OS benefit versus CT (hazard ratio [HR] = 0.76, 95% confidence interval [CI]: 0.64-0.89; 5-y OS: 15.7% versus 6.8%). OS improvement with D+CT versus CT (HR = 0.84, 95% CI: 0.72-1.00; 5-y OS: 13.0%) was consistent with the primary analysis. OS benefit with T+D+CT versus CT remained more pronounced in nonsquamous (HR = 0.69, 95% CI: 0.56-0.85) versus squamous (HR = 0.85, 95% CI: 0.65-1.10) mNSCLC. OS benefit with T+D+CT versus CT was still evident regardless of PD-L1 expression, including patients with PD-L1 tumor cell less than 1%, and remained evident in STK11-mutant (nonsquamous), KEAP1-mutant, and KRAS-mutant (nonsquamous) mNSCLC. No new safety signals were identified.

CONCLUSIONS

After a median follow-up of more than 5 years, T+D+CT had durable long-term OS benefit versus CT, supporting its use as first-line treatment in mNSCLC, including in patient subgroups with harder-to-treat disease.

Genomic correlates of the response to first-line PD-1 blockade plus chemotherapy in patients with advanced non-small-cell lung cancer

BACKGROUND

Programmed death 1 (PD-1) blockade plus chemotherapy has become the new first-line standard of care for patients with advanced non-small-cell lung cancer (NSCLC). Yet not all NSCLC patients benefit from this regimen. This study aimed to investigate the predictors of PD-1 blockade plus chemotherapy in untreated advanced NSCLC.

METHODS

We integrated clinical, genomic, and survival data from 287 patients with untreated advanced NSCLC who were enrolled in one of five registered phase 3 trials and received PD-1 blockade plus chemotherapy or chemotherapy alone. We randomly assigned these patients into a discovery cohort (n = 125), a validation cohort (n = 82), and a control cohort (n = 80). The candidate genes that could predict the response to PD-1 blockade plus chemotherapy were identified using data from the discovery cohort and their predictive values were then evaluated in the three cohorts. Immune deconvolution was conducted using transcriptome data of 1014 NSCLC patients from The Cancer Genome Atlas dataset.

RESULTS

A genomic variation signature, in which one or more of the 15 candidate genes were altered, was correlated with significantly inferior response rates and survival outcomes in patients treated with first-line PD-1 blockade plus chemotherapy in both discovery and validation cohorts. Its predictive value held in multivariate analyses when adjusted for baseline parameters, programmed cell death ligand 1 (PD-L1) expression level, and tumor mutation burden. Moreover, applying both the 15-gene panel and PD-L1 expression level produced better performance than either alone in predicting benefit from this treatment combination. Immune landscape analyses revealed that tumors with one or more variation in the 15-gene panel were associated with few immune infiltrates, indicating an immune-desert tumor microenvironment.

CONCLUSION

These findings indicate that a 15-gene panel can serve as a negative prediction biomarker for first-line PD-1 blockade plus chemotherapy in patients with advanced NSCLC.

Novel therapeutic agents in clinical trials: emerging approaches in cancer therapy

Novel therapeutic agents in clinical trials offer a paradigm shift in the approach to battling this prevalent and destructive disease, and the area of cancer therapy is on the precipice of a trans formative revolution. Despite the importance of tried-and-true cancer treatments like surgery, radiation, and chemotherapy, the disease continues to evolve and adapt, making new, more potent methods necessary. The field of cancer therapy is currently witnessing the emergence of a wide range of innovative approaches. Immunotherapy, including checkpoint inhibitors, CAR-T cell treatment, and cancer vaccines, utilizes the host's immune system to selectively target and eradicate malignant cells while minimizing harm to normal tissue. The development of targeted medicines like kinase inhibitors and monoclonal antibodies has allowed for more targeted and less harmful approaches to treating cancer. With the help of genomics and molecular profiling, "precision medicine" customizes therapies to each patient's unique genetic makeup to maximize therapeutic efficacy while minimizing unwanted side effects. Epigenetic therapies, metabolic interventions, radio-pharmaceuticals, and an increasing emphasis on combination therapy with synergistic effects further broaden the therapeutic landscape. Multiple-stage clinical trials are essential for determining the safety and efficacy of these novel drugs, allowing patients to gain access to novel treatments while also furthering scientific understanding. The future of cancer therapy is rife with promise, as the integration of artificial intelligence and big data has the potential to revolutionize early detection and prevention. Collaboration among researchers, and healthcare providers, and the active involvement of patients remain the bedrock of the ongoing battle against cancer. In conclusion, the dynamic and evolving landscape of cancer therapy provides hope for improved treatment outcomes, emphasizing a patient-centered, data-driven, and ethically grounded approach as we collectively strive towards a cancer-free world.

Loss of STK11 Suppresses Lipid Metabolism and Attenuates KRAS-Induced Immunogenicity in Patients with Non-Small Cell Lung Cancer

As many as 30% of the patients with non-small cell lung cancer harbor oncogenic KRAS mutations, which leads to extensive remodeling of the tumor immune microenvironment. Although co-mutations in several genes have prognostic relevance in KRAS-mutated patients, their effect on tumor immunogenicity are poorly understood. In the present study, a total of 189 patients with non-small cell lung cancer underwent a standardized analysis including IHC, whole-exome DNA sequencing, and whole-transcriptome RNA sequencing. Patients with activating KRAS mutations demonstrated a significant increase in PDL1 expression and CD8+ T-cell infiltration. Both were increased in the presence of a co-occurring TP53 mutation and lost with STK11 co-mutation. Subsequent genomic analysis demonstrated that KRAS/TP53 co-mutated tumors had a significant decrease in the expression of glycolysis-associated genes and an increase in several genes involved in lipid metabolism, notably lipoprotein lipase, low-density lipoprotein receptor, and LDLRAD4. Conversely, in the immune-excluded KRAS/STK11 co-mutated group, we observed diminished lipid metabolism and no change in anaerobic glycolysis. Interestingly, in patients with low expression of lipoprotein lipase, low-density lipoprotein receptor, or LDLRAD4, KRAS mutations had no effect on tumor immunogenicity. However, in patients with robust expression of these genes, KRAS mutations were associated with increased immunogenicity and associated with improved overall survival. Our data further suggest that the loss of STK11 may function as a metabolic switch, suppressing lipid metabolism in favor of glycolysis, thereby negating KRAS-induced immunogenicity. Hence, this concept warrants continued exploration, both as a predictive biomarker and potential target for therapy in patients receiving ICI-based immunotherapy.

SIGNIFICANCE

In patients with lung cancer, we demonstrate that KRAS mutations increase tumor immunogenicity; however, KRAS/STK11 co-mutated patients display an immune-excluded phenotype. KRAS/STK11 co-mutated patients also demonstrated significant downregulation of several key lipid metabolism genes, many of which were associated with increased immunogenicity and improved overall survival in KRAS-mutated patients. Hence, alteration to lipid metabolism warrants further study as a potential biomarker and target for therapy in patients with KRAS-mutated lung cancer.

The role of immunotherapy in patients with lung cancer and brain metastases: a narrative review of the literature

Worldwide, approximately half of the patients diagnosed with lung cancer (LC) will develop, simultaneously or asynchronously, brain metastases (BMs). The existence of BMs negatively affects the quality of life and constitutes a poor prognostic factor, linked with high mortality. Locoregional therapy with surgery or radiation is, until now, the treatment of choice, especially for symptomatic patients; however, both options are linked to a high complication rate. The question arising here is whether, in asymptomatic patients, the benefit outweighs the risk and whether an alternative method can be used to treat this special category of patients. Over the last decade, immune checkpoint inhibitors (ICIs) have represented a major breakthrough in the field of oncology, and several molecules have been approved as a treatment option for LC. This review tried to analyze the tumor microenvironment of both the primary lung tumor and the BMs in order to evaluate the intracranial activity of ICIs, outline the main challenges of including these agents in the treatment of LC with BMs, highlight the available information from the main clinical trials, and mark the potential positive effect of choosing a combination therapy. In conclusion, it appears that immunotherapy has a positive effect, inhibiting the progression of BMs, but more data should be published specifically for this category of patients.

The multifaceted functions of DNA-PKcs: implications for the therapy of human diseases

The DNA-dependent protein kinase (DNA-PK), catalytic subunit, also known as DNA-PKcs, is complexed with the heterodimer Ku70/Ku80 to form DNA-PK holoenzyme, which is well recognized as initiator in the nonhomologous end joining (NHEJ) repair after double strand break (DSB). During NHEJ, DNA-PKcs is essential for both DNA end processing and end joining. Besides its classical function in DSB repair, DNA-PKcs also shows multifaceted functions in various biological activities such as class switch recombination (CSR) and variable (V) diversity (D) joining (J) recombination in B/T lymphocytes development, innate immunity through cGAS-STING pathway, transcription, alternative splicing, and so on, which are dependent on its function in NHEJ or not. Moreover, DNA-PKcs deficiency has been proven to be related with human diseases such as neurological pathogenesis, cancer, immunological disorder, and so on through different mechanisms. Therefore, it is imperative to summarize the latest findings about DNA-PKcs and diseases for better targeting DNA-PKcs, which have shown efficacy in cancer treatment in preclinical models. Here, we discuss the multifaceted roles of DNA-PKcs in human diseases, meanwhile, we discuss the progresses of DNA-PKcs inhibitors and their potential in clinical trials. The most updated review about DNA-PKcs will hopefully provide insights and ideas to understand DNA-PKcs associated diseases.

The opportunities and challenges of using PD-1/PD-L1 inhibitors for leukemia treatment

Leukemia poses a significant clinical challenge due to its swift onset, rapid progression, and treatment-related complications. Tumor immune evasion, facilitated by immune checkpoints like programmed death receptor 1/programmed death receptor ligand 1 (PD-1/PD-L1), plays a critical role in leukemia pathogenesis and progression. In this review, we summarized the research progress and therapeutic potential of PD-L1 in leukemia, focusing on targeted therapy and immunotherapy. Recent clinical trials have demonstrated promising outcomes with PD-L1 inhibitors, highlighting their role in enhancing treatment efficacy. This review discusses the implications of PD-L1 expression levels on treatment response and long-term survival rates in leukemia patients. Furthermore, we address the challenges and opportunities in immunotherapy, emphasizing the need for personalized approaches and combination therapies to optimize PD-L1 inhibition in leukemia management. Future research prospects include exploring novel treatment strategies and addressing immune-related adverse events to improve clinical outcomes in leukemia. Overall, this review provides valuable insights into the role of PD-L1 in leukemia and its potential as a therapeutic target in the evolving landscape of leukemia treatment.

Glyco-signatures in patients with advanced lung cancer during anti-PD-1/PD-L1 immunotherapy

Immune checkpoint inhibitors (ICIs) targeting programmed cell death 1/programmed cell death ligand-1 (PD-1/PD-L1) have significantly prolonged the survival of advanced/metastatic patients with lung cancer. However, only a small proportion of patients can benefit from ICIs, and clinical management of the treatment process remains challenging. Glycosylation has added a new dimension to advance our understanding of tumor immunity and immunotherapy. To systematically characterize anti-PD-1/PD-L1 immunotherapy-related changes in serum glycoproteins, a series of serum samples from 12 patients with metastatic lung squamous cell carcinoma (SCC) and lung adenocarcinoma (ADC), collected before and during ICIs treatment, are firstly analyzed with mass-spectrometry-based label-free quantification method. Second, a stratification analysis is performed among anti-PD-1/PD-L1 responders and non-responders, with serum levels of glycopeptides correlated with treatment response. In addition, in an independent validation cohort, a large-scale site-specific profiling strategy based on chemical labeling is employed to confirm the unusual characteristics of IgG N-glycosylation associated with anti-PD-1/PD-L1 treatment. Unbiased label-free quantitative glycoproteomics reveals serum levels' alterations related to anti-PD-1/PD-L1 treatment in 27 out of 337 quantified glycopeptides. The intact glycopeptide EEQFN 177STYR (H3N4) corresponding to IgG4 is significantly increased during anti-PD-1/PD-L1 treatment (FC=2.65, P=0.0083) and has the highest increase in anti-PD-1/PD-L1 responders (FC=5.84, P=0.0190). Quantitative glycoproteomics based on protein purification and chemical labeling confirms this observation. Furthermore, obvious associations between the two intact glycopeptides (EEQFN 177STYR (H3N4) of IgG4, EEQYN 227STFR (H3N4F1) of IgG3) and response to treatment are observed, which may play a guiding role in cancer immunotherapy. Our findings could benefit future clinical disease management.

Circulating receptor activator of nuclear factor kappa-B ligand (RANKL) levels predict response to immune checkpoint inhibitors in advanced non-small cell lung cancer (NSCLC)

BACKGROUND

Receptor activator of nuclear factor kappa-B ligand (RANKL) can directly promote tumor growth and indirectly support tumor immune evasion by altering the tumor microenvironment and immune cell responses. This study aimed to assess the prognostic significance of soluble RANKL in patients with advanced non-small cell lung cancer (NSCLC) receiving programmed cell death 1 (PD1)/programmed death-ligand 1 (PDL1) checkpoint inhibitor therapy.

METHODS

Plasma RANKL levels were measured in 100 patients with advanced NSCLC without bone metastases undergoing monotherapy with PD1/PDL1 checkpoint inhibitors. To establish the optimal cut-off value, we used the Cutoff Finder package in R. Survival curves for four distinct patient groups, according to their RANKL and PDL1 levels (high or low), were generated using the Kaplan-Meier method and compared with the log-rank test. The Cox regression model calculated HRs and 95% CIs for overall survival (OS) and progression-free survival (PFS).

RESULTS

The optimal RANKL cut-off was established at 280.4 pg/mL, categorizing patients into groups with high or low RANKL levels. A significant association was observed between increased RANKL concentrations and decreased survival rates at 24 months, only within the subgroup expressing high levels of PDL1 (p=0.002). Additionally, low RANKL levels in conjunction with elevated PDL1 expression correlated with improved PFS (median 22 months, 95% CI 6.70 to 50 vs median 4 months, 95% CI 3.0 to 7.30, p=0.009) and OS (median 26 months, 95% CI 20 to not reached vs median 7 months, 95% CI 6 to 13, p=0.003), indicating RANKL's potential as an indicator of adverse prognosis in these patients. Multivariate analysis identified RANKL as an independent negative prognostic factor for both PFS and OS, regardless of other clinicopathological features.

CONCLUSION

These results highlight the prognostic and predictive value of RANKL specifically in patients with high PDL1 expression.

Microsatellite Instability, Mismatch Repair, and Tumor Mutation Burden in Lung Cancer

Since US Food and Drug Administration approval of programmed death ligand 1 (PD-L1) as the first companion diagnostic for immune checkpoint inhibitors (ICIs) in non-small cell lung cancer, many patients have experienced increased overall survival. To improve selection of ICI responders versus nonresponders, microsatellite instability/mismatch repair deficiency (MSI/MMR) and tumor mutation burden (TMB) came into play. Clinical data show PD-L1, MSI/MMR, and TMB are independent predictive immunotherapy biomarkers. Harmonization of testing methodologies, optimization of assay design, and results analysis are ongoing. Future algorithms to determine immunotherapy eligibility might involve complementary use of current and novel biomarkers. Artificial intelligence could facilitate algorithm implementation to convert complex genetic data into recommendations for specific ICIs.

Multi-index comprehensive evaluation of the efficacy and response mechanism of immunotherapy in non-small cell lung cancer

OBJECTIVE

This research conducted multi-index comprehensive evaluations of the immunotherapeutic efficacy and response in non-small cell lung cancer (NSCLC).

METHODS

Forty-five patients with epidermal growth factor receptor (EGFR)/anaplastic lymphoma kinase (ALK) wild-type advanced NSCLC who received immunotherapy were included. Immunohistochemistry was adopted to detect the expression levels of programmed death ligand 1 (PD-L1) with X-ray cross-complementing protein 1 (XRCC1) and excision repair cross-complementing group 1 (ERCC1) proteins in tumor tissues. Flow cytometry was utilized to measure the levels of T-cell subsets in peripheral blood before and after treatment. PCR-RELP method was employed to evaluate XRCC1 and ERCC1 gene polymorphisms in peripheral blood. According to the treatment effect, patients evaluated as complete response (CR), partial response (PR), and stable disease (SD) were categorized into the immune response group, and patients evaluated as progressive disease (PD) were categorized into the immune unresponsive group. The correlation between PD-L1 protein expression, XRCC1 and ERCC1 protein expression, gene polymorphisms, T-cell subpopulation levels, and treatment efficacy was analyzed.

RESULTS

The therapeutic efficacy of patients with positive PD-L1 expression was better than that of patients with negative PD-L1 expression (P < 0.05). After treatment, peripheral blood CD3+ and CD4+ cell levels and Thl/Th2 cell levels were higher and CD8+ T cells were lower in the immune response group than in the immune unresponsive group (P < 0.05). Among the patients in the immune response group, peripheral blood CD3+ and CD4+ cell levels were higher and CD8+ T cells were lower in patients with positive PD-L1 expression than in patients with negative PD-L1 expression (P < 0.05). In the XRCC1 gene, the proportion of patients in the immune response group carrying the Arg/Trp + Trp/Trp genotype was higher than that of patients in the immune unresponsive group (P < 0.05). In the ERCC1 gene, the proportion of patients in the immune response group carrying the C/T + T/T genotype was higher than that of patients in the immune unresponsive group (P < 0.05). The positive expression rates of XRCC1 and ERCC1 in patients in the immune unresponsive group were higher than those in the immune response group (P < 0.05).

CONCLUSION

PD-L1 protein expression, XRCC1 and ERCC1 protein expression, and gene polymorphisms are associated with immunotherapy outcome in EGFR/ALK wild-type advanced NSCLC patients, and may be biological indicators for predicting immunotherapy outcome in EGFR/ALK wild-type advanced NSCLC patients.

Global research trends in immunotherapy for non-small cell lung cancer patients with KRAS mutations: a bibliometric analysis

Background

Immunotherapy, frequently combined with conventional chemotherapy, is crucial for treating NSCLC. Kirsten rat sarcoma virus (KRAS) is a poor prognostic factor in patients with NSCLC, particularly lung adenocarcinoma, where binding of conventional inhibitors to mutated KRAS proteins is challenging. Field profiles, research hotspots, and prospects for immunotherapy for patients with NSCLC-carrying KRAS mutations were uncovered in this study.

Methods

Microsoft Excel 2019, Bibliometrix, VOSviewer software, and Citespace were utilized to conduct a comprehensive scientometric analysis and understand a specific research field's knowledge base and frontiers aided by bibliometrics.

Results

Between 2014 and 2023, 398 eligible documents in the English language were acquired using the WoSCC database, of which 113 and 285 were reviews and articles, respectively. The growth rate per year was 34.25 %. The most cited articles were from the United States, and China published the highest number of articles. Cancers was the journal, with increased publications in recent years. The keywords with the strongest citation bursts were analyzed using Citespace. "Immune checkpoint inhibitors," "co-occurring genomic alterations," and "KRAS" are among the research hotspots in this field.

Conclusion

Using bibliometric and visual analyses, we examined immunotherapy for patients with KRAS-mutant NSCLC over the previous decade. The whole analysis showed a steady, quick increase in yearly publications in this area. Our findings will provide a roadmap for future research on the mechanisms of immunotherapy and immune checkpoint inhibitor action in treating KRAS-mutant NSCLC.

Unraveling the tumor immune microenvironment of lung adenocarcinoma using single-cell RNA sequencing

Tumor immune microenvironment (TIME) and its indications for lung cancer patient prognosis and therapeutic response have become new hotspots in cancer research in recent years. Tumor cells, immune cells, various regulatory factors, and their interactions in the TIME have been suggested to commonly influence lung cancer development and therapeutic outcome. The heterogeneity of TIME is composed of dynamic immune-related components, including various cancer cells, immune cells, cytokine/chemokine environments, cytotoxic activity, or immunosuppressive factors. The specific composition of cell subtypes may facilitate or hamper the response to immunotherapy and influence patient prognosis. Various markers have been found to stratify the patient prognosis or predict the therapeutic outcome. In this article, we systematically reviewed the recent advancement of TIME studies in lung adenocarcinoma (LUAD) using single-cell RNA sequencing (scRNA-seq) techniques, with specific focuses on the roles of TIME in LUAD development, TIME heterogeneity, indications of TIME in patient prognosis and therapeutic response during immunotherapy and drug resistance. The main findings in TIME heterogeneity and relevant markers or models for prognosis stratification and response prediction have been summarized. We hope that this review provides an overview of TIME status in LUAD and an inspiration for future development of strategies and biomarkers in LUAD treatment.

rs822336 binding to C/EBPβ and NFIC modulates induction of PD-L1 expression and predicts anti-PD-1/PD-L1 therapy in advanced NSCLC

Efficient predictive biomarkers are needed for immune checkpoint inhibitor (ICI)-based immunotherapy in non-small cell lung cancer (NSCLC). Testing the predictive value of single nucleotide polymorphisms (SNPs) in programmed cell death 1 (PD-1) or its ligand 1 (PD-L1) has shown contrasting results. Here, we aim to validate the predictive value of PD-L1 SNPs in advanced NSCLC patients treated with ICIs as well as to define the molecular mechanisms underlying the role of the identified SNP candidate. rs822336 efficiently predicted response to anti-PD-1/PD-L1 immunotherapy in advanced non-oncogene addicted NSCLC patients as compared to rs2282055 and rs4143815. rs822336 mapped to the promoter/enhancer region of PD-L1, differentially affecting the induction of PD-L1 expression in human NSCLC cell lines as well as their susceptibility to HLA class I antigen matched PBMCs incubated with anti-PD-1 monoclonal antibody nivolumab. The induction of PD-L1 expression by rs822336 was mediated by a competitive allele-specificity binding of two identified transcription factors: C/EBPβ and NFIC. As a result, silencing of C/EBPβ and NFIC differentially regulated the induction of PD-L1 expression in human NSCLC cell lines carrying different rs822336 genotypes. Analysis by binding microarray further validated the competitive allele-specificity binding of C/EBPβ and NFIC to PD-L1 promoter/enhancer region based on rs822336 genotype in human NSCLC cell lines. These findings have high clinical relevance since identify rs822336 and induction of PD-L1 expression as novel biomarkers for predicting anti-PD-1/PD-L1-based immunotherapy in advanced NSCLC patients.

Ferroptosis-related genes prognostic signature for pancreatic cancer and immune infiltration: potential biomarkers for predicting overall survival

BACKGROUND

Pancreatic adenocarcinoma (PAAD) constitutes a lethal malignancy, notorious for its elevated mortality rates due to the difficulties in early diagnosis and rapid metastasis. The emerging paradigm of ferroptosis-an iron-catalyzed, regulated cell death distinguished by the accrual of lipid peroxides-has recently garnered scholarly focus. However, the expression landscape of ferroptosis-related genes (FRGs) in PAAD and their prognostic implications remain enigmatic.

METHODS

We undertook a rigorous quantification of FRGs in PAAD samples, sourcing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. These repositories also provided extensive metadata, encompassing mesenchymal stemness index (mRNAsi), genomic mutations, copy number variations (CNV), tumor mutational burden (TMB), and other clinical attributes. A predictive model was constructed utilizing Lasso regression analysis, and a co-expression study was executed to elucidate the complex interconnections between FRGs and other gene sets.

RESULTS

Intriguingly, FRGs were substantially upregulated in the high-risk cohort, even in the absence of clinically manifest symptoms, emphasizing their utility as prognostic biomarkers. Gene set enrichment analysis (GSEA) revealed significant enrichment of immune and tumor-related pathways in this high-risk demographic. Striking heterogeneities in immune function and N6-methyladenosine (m6A) RNA modification were observed between the low- and high-risk groups. Our analysis further implicated a cohort of genes-including LINC01559, C11orf86, SERPINB5, DSG3, MSLN, EREG, FAM83A, CXCL5, LY6D, and PSCA-as cardinal mediators in PAAD pathogenesis. A convergence of our predictive model with an analysis of CNVs, single nucleotide polymorphisms (SNPs), and drug sensitivities, revealed an intricate relationship with the FRGs.

CONCLUSIONS

Our findings accentuate the salient role of FRGs as critical modulators in the pathogenesis and progression of PAAD. Importantly, our composite prognostic framework offers invaluable insights into PAAD clinical trajectory. Moreover, the complex crosstalk between FRGs and immune cell landscapes in the tumor microenvironment (TME) may elucidate prospective therapeutic strategies. The clinical translational utility of these insights, however, requires further in-depth empirical exploration. Accordingly, the FRG signature introduces a compelling new avenue for risk stratification and targeted therapeutic interventions in this devastating malignancy.

Efficacy of immune checkpoint inhibitors in non-small cell lung cancer with NTRK family mutations

BACKGROUND

The efficacy of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) patients harboring neurotrophin receptor kinase (NTRK) family mutations remains obscure.

METHODS

The Zehir cohort from cBioPortal was used to analyze the mutations (MT) frequency of NTRK family in patients with NSCLC, and their correlation with clinical characteristics and patient survival. The influence of NTRK MT on ICIs efficacy was evaluated in ICIs-treated patients from Samstein cohort and further validated by use of data from OAK/POPLAR cohort.

RESULTS

In the Zehir cohort, a significant difference was observed in median overall survival (mOS) between patients with NTRK MT and wild-type (WT) (mOS: 18.97 vs. 21.27 months, HR = 1.34, 95%CI 1.00-1.78; log-rank P = 0.047). In Samstein cohort, the mOS of NTRK mutant patients receiving ICIs has improved compared to WT patients (mOS: 21.00 vs. 11.00 months, log-rank P = 0.103). Notably, in subgroup analysis, ICIs significantly prolonged mOS in patients with NTRK3 MT than in WT patients (mOS: not available vs. 11.00 months, HR = 0.36, 95%CI 0.16-0.81; log-rank P = 0.009). Identical mOS between NTRK MT and WT patients receiving ICIs treatment (mOS: 13.24 vs. 13.50 months, log-rank P = 0.775) was observed in OAK/POPLAR cohort. Moreover, a similar programmed death ligand 1 (PD-L1) expression, but higher tumor mutational burden (TMB), blood TMB (bTMB) and enriched anti-tumor immunity were observed in NTRK MT compared to WT (P < 0.05).

CONCLUSION

Taking high TMB or bTMB into consideration, patients with NTRK mutant NSCLC could benefit from ICIs treatment.

Identifying Predictive Biomarkers for Head and Neck Squamous Cell Carcinoma Response

The 5-year survival rate for head and neck squamous cell carcinoma (HNSCC) is approximately 65%. In addition to radio-chemotherapy, immunotherapy is an approach in the treatment of advanced HNSCC. A better understanding of the immune context would allow personalized treatment by identifying patients who are best suited for different treatment options. In our discovery cohort, we evaluated the expression profiles of CMTM6, PD-L1, CTLA-4, and FOXP3 in 177 HNSCCs from Caucasian patients of all tumor stages and different treatment regimens, correlating marker expression in tumor and immune cells with outcomes. Patients with CMTM6high-expressing tumors had a longer overall survival regardless of treatment. This prognostic benefit of CMTM6 in HNSCC was validated in an independent cohort. Focusing on the in the discovery cohort (n = 177), a good predictive effect of CMTM6high expression was seen in patients receiving radiotherapy (p = 0.07; log rank), but not in others. CMTM6 correlated with PD-L1, CTLA-4 and FOXP3 positivity, with patients possessing CMTM6high/FOXP3high tumors showing the longest survival regardless of treatment. In chemotherapy-treated patients, PD-L1 positivity was associated with longer progression-free survival (p < 0.05). In the 27 patients who received immunotherapy, gene expression analysis revealed lower levels of CTLA-4 and FOXP3 with either partial or complete response to this treatment, while no effect was observed for CMTM6 or PD-L1. The combination of these immunomodulatory markers seems to be an interesting prognostic and predictive signature for HNSCC patients with the ability to optimize individualized treatments.

Predictive value of tumor mutational burden for PD-1/PD-L1 inhibitors in NSCLC: A meta-analysis

BACKGROUND

To investigate the association between tumor mutational burden (TMB) and the therapeutic effect of Programmed Death 1/Programmed Death Ligand 1 inhibitors in non-small cell lung cancer.

METHODS

Four electronic databases, PubMed, Embase, Web of Science, and Cochrane Library, were searched on May 10, 2023, and no time limitation was applied. Analyses were performed using STATA17.0. We assessed the methodological quality of each randomized controlled trial using the Newcastle-Ottawa scale.

RESULTS

After exhaustive database search and rigorous screening, 10 studies were included in the meta-analysis. Our findings indicate that high TMB significantly improves progression-free survival but reduces overall response rate. The overall survival was not significantly different between the high and low TMB groups. No significant publication bias was observed.

CONCLUSION

High TMB serves as a potential predictive biomarker for improved progression-free survival and reduced overall response rate in patients with non-small cell lung cancer treated with programmed death 1/programmed death ligand 1 inhibitors. However, its predictive value in overall survival requires further investigation.

Quantitative multiplexed imaging technologies for single-cell analysis to assess predictive markers for immunotherapy in thoracic immuno-oncology: promises and challenges

The past decade has witnessed a revolution in cancer treatment by the shift from conventional drugs (chemotherapies) towards targeted molecular therapies and immune-based therapies, in particular the immune-checkpoint inhibitors (ICIs). These immunotherapies selectively release the host immune system against the tumour and have shown unprecedented durable remission for patients with cancers that were thought incurable such as advanced non-small cell lung cancer (aNSCLC). The prediction of therapy response is based since the first anti-PD-1/PD-L1 molecules FDA and EMA approvals on the level of PD-L1 tumour cells expression evaluated by immunohistochemistry, and recently more or less on tumour mutation burden in the USA. However, not all aNSCLC patients benefit from immunotherapy equally, since only around 30% of them received ICIs and among them 30% have an initial response to these treatments. Conversely, a few aNSCLC patients could have an efficacy ICIs response despite low PD-L1 tumour cells expression. In this context, there is an urgent need to look for additional robust predictive markers for ICIs efficacy in thoracic oncology. Understanding of the mechanisms that enable cancer cells to adapt to and eventually overcome therapy and identifying such mechanisms can help circumvent resistance and improve treatment. However, more than a unique universal marker, the evaluation of several molecules in the tumour at the same time, particularly by using multiplex immunostaining is a promising open room to optimise the selection of patients who benefit from ICIs. Therefore, urgent further efforts are needed to optimise to individualise immunotherapy based on both patient-specific and tumour-specific characteristics. This review aims to rethink the role of multiplex immunostaining in immuno-thoracic oncology, with the current advantages and limitations in the near-daily practice use.

PD-L1 Expression by RNA-Sequencing in Non-Small Cell Lung Cancer: Concordance with Immunohistochemistry and Associations with Pembrolizumab Treatment Outcomes

Programmed cell death ligand (PD-L1) expression by immunohistochemistry (IHC) lacks sensitivity for pembrolizumab immunotherapy selection in non-small cell lung cancer (NSCLC), particularly for tumors with low expression. We retrospectively evaluated transcriptomic PD-L1 by mRNA next-generation sequencing (RNA-seq). In an unselected NSCLC patient cohort (n = 3168) tested during standard care (2017-2021), PD-L1 IHC and RNA-seq demonstrated moderate concordance, with 80% agreement overall. Most discordant cases were either low or negative for PD-L1 expression by IHC but high by RNA-seq. RNA-seq accurately discriminated PD-L1 IHC high from low tumors by receiver operator curve (ROC) analysis but could not distinguish PD-L1 IHC low from negative tumors. In a separate pembrolizumab monotherapy cohort (n = 102), NSCLC tumors classified as PD-L1 high versus not high by RNA-seq had significantly improved response, progression-free survival, and overall survival as an individual measure and in combination with IHC high or low status. PD-L1 IHC status (high or low) trended toward but had no significant associations with improved outcomes. Conventional PD-L1 IHC testing has inherent limitations, making it an imperfect reference standard for evaluating novel testing technologies. RNA-seq offers an objective PD-L1 measure that could represent a complementary method to IHC to improve NSCLC patient selection for immunotherapy.

Update in Immunotherapy for Advanced Non-Small Cell Lung Cancer: Optimizing Treatment Sequencing and Identifying the Best Choices

The introduction of immunotherapy has brought about a paradigm shift in the management of advanced non-small cell lung cancer (NSCLC). It has not only significantly improved the prognosis of patients but has also become a cornerstone of treatment, particularly in those without oncogenic driver mutations. Immune checkpoint inhibitors (ICIs) play a crucial role in the treatment of lung cancer and can be classified into two main groups: Anti-cytotoxic T lymphocyte antigen-4 (Anti-CTLA-4) and anti-T-cell receptor programmed cell death-1 or its ligand (Anti-PD-1 and Anti-PD-L1). Certainly, the landscape of approved first line immunotherapeutic approaches has expanded to encompass monotherapy, immunotherapy-exclusive protocols, and combinations with chemotherapy. The complexity of decision-making in this realm arises due to the absence of direct prospective comparisons. However, a thorough analysis of the long-term efficacy and safety data derived from pivotal clinical trials can offer valuable insights into optimizing treatment for different patient subsets. Moreover, ongoing research is investigating emerging biomarkers and innovative therapeutic strategies that could potentially refine the current treatment approach even further. In this comprehensive review, our aim is to highlight the latest advances in immunotherapy for advanced NSCLC, including the mechanisms of action, efficacy, safety profiles, and clinical significance of ICI.

Cured or Not? Long-term Outcomes of Immunotherapy Responders. Focus on Melanoma

PURPOSE OF REVIEW

Immune checkpoint inhibitors (ICIs) demonstrated robust antitumor activity and tolerable safety in advanced melanoma. Data on long-term outcome of patients who benefited from this therapy and who are still free of progression despite ICI discontinuation is now available. We review here the characteristics of long-term ICI responders and address the critical question of cure.

RECENT FINDINGS

Long-term outcome of patients with metastatic melanoma enrolled in large phase 2 and phase 3 clinical trials evaluating ICI in metastatic melanoma is now available. Durable responses, with more than 6 years of median follow-up, may persist after discontinuation. They occur more frequently in patients who achieved a complete response rather than in patients who had partial response or stable disease. Although long-term clinical benefit is more frequent in patients with high PDL-1 expression and smaller tumor burden, durable response may also be observed regardless of baseline characteristics. In patients with asymptomatic brain metastasis, combined immunotherapy (ipilimumab plus nivolumab) may also lead to long-term remission. Clinical trials confirm the durable antitumor activity of ICI. Although the hope for cure seems reasonable for many patients in this situation, late relapses may occur and no relapse-predictive biomarkers have been identified yet. Long-term responders who relapse can respond to a rechallenge of ICI although data are limited concerning the rate and the duration of this new response.

Outcome-Supervised Deep Learning on Pathologic Whole Slide Images for Survival Prediction of Immunotherapy in Patients with Non-Small Cell Lung Cancer

Although programmed death-(ligand) 1 (PD-(L)1) inhibitors are marked by durable efficacy in patients with non-small cell lung cancer (NSCLC), approximately 60% of the patients still suffer from recurrence and metastasis after PD-(L)1 inhibitor treatment. To accurately predict the response to PD-(L)1 inhibitors, we presented a deep learning model using a Vision Transformer (ViT) network based on hematoxylin and eosin (H&E)-stained specimens of patients with NSCLC. Two independent cohorts of patients with NSCLC receiving PD-(L)1 inhibitors from Shandong Cancer Hospital and Institute and Shandong Provincial Hospital were enrolled for model training and external validation, respectively. Whole slide images (WSIs) of H&E-stained histologic specimens were obtained from these patients and patched into 1024 × 1024 pixels. The patch-level model was trained based on ViT to identify the predictive patches, and patch-level probability distribution was performed. Then, we trained a patient-level survival model based on the ViT-Recursive Neural Network framework and externally validated it in the Shandong Provincial Hospital cohort. A total of 291 WSIs of H&E-stained histologic specimens from 198 patients with NSCLC in Shandong Cancer Hospital and 62 WSIs from 30 patients with NSCLC in Shandong Provincial Hospital were included in the model training and validation. The model achieved an accuracy of 88.6% in the internal validation cohort and 81% in the external validation cohort. The survival model also remained a statistically independent predictor of survival from PD-(L)1 inhibitors. In conclusion, the outcome-supervised ViT-Recursive Neural Network survival model based on pathologic WSIs could be used to predict immunotherapy efficacy in patients with NSCLC.

Reliability of panel-based mutational signatures for immune-checkpoint-inhibition efficacy prediction in non-small cell lung cancer

OBJECTIVES

Mutational signatures (MS) are gaining traction for deriving therapeutic insights for immune checkpoint inhibition (ICI). We asked if MS attributions from comprehensive targeted sequencing assays are reliable enough for predicting ICI efficacy in non-small cell lung cancer (NSCLC).

METHODS

Somatic mutations of m = 126 patients were assayed using panel-based sequencing of 523 cancer-related genes. In silico simulations of MS attributions for various panels were performed on a separate dataset of m = 101 whole genome sequenced patients. Non-synonymous mutations were deconvoluted using COSMIC v3.3 signatures and used to test a previously published machine learning classifier.

RESULTS

The ICI efficacy predictor performed poorly with an accuracy of 0.51-0.09+0.09, average precision of 0.52-0.11+0.11, and an area under the receiver operating characteristic curve of 0.50-0.09+0.10. Theoretical arguments, experimental data, and in silico simulations pointed to false negative rates (FNR) related to panel size. A secondary effect was observed, where deconvolution of small ensembles of point mutations lead to reconstruction errors and misattributions.

CONCLUSION

MS attributions from current targeted panel sequencing are not reliable enough to predict ICI efficacy. We suggest that, for downstream classification tasks in NSCLC, signature attributions be based on whole exome or genome sequencing instead.

The Long Run towards Personalized Therapy in Non-Small-Cell Lung Cancer: Current State and Future Directions

Non-small-cell lung cancer (NSCLC) is the major cause of cancer-related deaths worldwide, due to its high incidence and mortality [...].

Atezolizumab Plus Bevacizumab as First-line Treatment for Patients With Metastatic Nonsquamous Non-Small Cell Lung Cancer With High Tumor Mutation Burden: A Nonrandomized Controlled Trial

Importance

Antiangiogenic drug combinations with anti-programmed cell death 1 protein and anti-programmed cell death 1 ligand 1 (PD-L1) agents are a novel treatment option for lung cancer. However, survival remains limited, and the activity of these combinations for tumors with high tumor mutation burden (TMB) is unknown.

Objective

To assess the clinical benefits and safety of atezolizumab plus bevacizumab for patients with high-TMB advanced nonsquamous non-small cell lung cancer (NSCLC).

Design, Setting, and Participants

This multicenter, single-arm, open-label, phase 2 nonrandomized controlled trial (Atezolizumab Plus Bevacizumab in First-Line NSCLC Patients [TELMA]) included treatment-naive patients aged 18 years or older with confirmed stage IIIB-IV nonsquamous NSCLC with TMB of 10 or more mutations/megabase and no EGFR, ALK, STK11, MDM2, or ROS1 alterations. From May 2019 through January 2021, patients were assessed at 13 sites in Spain, with follow-up until February 28, 2022.

Interventions

Participants were given atezolizumab, 1200 mg, plus bevacizumab, 15 mg/kg, on day 1 of each 21-day cycle. Treatment was continued until documented disease progression, unacceptable toxic effects, patient withdrawal, investigator decision, or death.

Main Outcomes and Measures

The primary end point was 12-month progression-free survival (PFS) rate (according to Response Evaluation Criteria in Solid Tumours, version 1.1 criteria); PFS was defined as the time from enrollment to disease progression or death. Adverse events were monitored according to the National Cancer Institute Common Terminology Criteria for Adverse Events, version 4.0.

Results

A total of 307 patients were assessed for trial eligibility, of whom 266 were ineligible for enrollment. Of the 41 patients enrolled, 3 did not fulfill all inclusion criteria and were excluded. The remaining 38 patients (28 [73.7%] male; mean [SD] age, 63.7 [8.3] years) constituted the per-protocol population. The 12-month PFS rate was 51.3% (95% CI, 34.2%-66.0%), which met the primary end point. The 12-month overall survival (OS) rate was 72.0% (95% CI, 54.1%-83.9%). The median PFS was 13.0 months (95% CI, 7.9-18.0 months), and the median OS was not reached. Of the 38 patients, 16 (42.1%) achieved an objective response and 30 (78.9%) achieved disease control. The median time to response was 2.8 months (IQR, 2.8-3.58 months), with a median duration of response of 11.7 months (range, 3.57-22.4 months; the response was ongoing at cutoff). Of 16 responses, 8 (50.0%) were ongoing. Most adverse events were grade 1 or 2. For atezolizumab, the most common adverse events were fatigue (6 [15.8%]) and pruritus (6 [15.8%]). For bevacizumab, they were hypertension (10 [26.3%]) and proteinuria (4 [10.5%]). Drug discontinuation occurred in 2 patients receiving atezolizumab (5.3%) and 3 patients receiving bevacizumab (7.9%). PD-L1 levels were not associated with response, PFS, or OS.

Conclusions and Relevance

These findings suggest that atezolizumab with bevacizumab is a potential treatment for high-TMB nonsquamous NSCLC.

Trial Registration

ClinicalTrials.gov Identifier: NCT03836066.

LC-MS/MS Based Volatile Organic Compound Biomarkers Analysis for Early Detection of Lung Cancer

(1) Background: lung cancer is the world's deadliest cancer, but early diagnosis helps to improve the cure rate and thus reduce the mortality rate. Annual low-dose computed tomography (LD-CT) screening is an efficient lung cancer-screening program for a high-risk population. However, LD-CT has often been characterized by a higher degree of false-positive results. To meet these challenges, a volatolomic approach, in particular, the breath volatile organic compounds (VOCs) fingerprint analysis, has recently received increased attention for its application in early lung cancer screening thanks to its convenience, non-invasiveness, and being well tolerated by patients. (2) Methods: a LC-MS/MS-based volatolomics analysis was carried out according to P/N 5046800 standard based breath analysis of VOC as novel cancer biomarkers for distinguishing early-stage lung cancer from the healthy control group. The discriminatory accuracy of identified VOCs was assessed using subject work characterization and a random forest risk prediction model. (3) Results: the proposed technique has good performance compared with existing approaches, the differences between the exhaled VOCs of the early lung cancer patients before operation, three to seven days after the operation, as well as four to six weeks after operation under fasting and 1 h after the meal were compared with the healthy controls. The results showed that only 1 h after a meal, the concentration of seven VOCs, including 3-hydroxy-2-butanone (TG-4), glycolaldehyde (TG-7), 2-pentanone (TG-8), acrolein (TG-11), nonaldehyde (TG-19), decanal (TG-20), and crotonaldehyde (TG-22), differ significantly between lung cancer patients and control, with the invasive adenocarcinoma of the lung (IAC) having the most significant difference. (4) Conclusions: this novel, non-invasive approach can improve the detection rate of early lung cancer, and LC-MS/MS-based breath analysis could be a promising method for clinical application.

Development and validation of an integrative pan-solid tumor predictor of PD-1/PD-L1 blockade benefit

BACKGROUND

Anti-PD-1 and PD-L1 (collectively PD-[L]1) therapies are approved for many advanced solid tumors. Biomarkers beyond PD-L1 immunohistochemistry, microsatellite instability, and tumor mutation burden (TMB) may improve benefit prediction.

METHODS

Using treatment data and genomic and transcriptomic tumor tissue profiling from an observational trial (NCT03061305), we developed Immunotherapy Response Score (IRS), a pan-tumor predictive model of PD-(L)1 benefit. IRS real-world progression free survival (rwPFS) and overall survival (OS) prediction was validated in an independent cohort of trial patients.

RESULTS

Here, by Cox modeling, we develop IRS-which combines TMB with CD274, PDCD1, ADAM12 and TOP2A quantitative expression-to predict pembrolizumab rwPFS (648 patients; 26 tumor types; IRS-High or -Low groups). In the 248 patient validation cohort (248 patients; 24 tumor types; non-pembrolizumab PD-[L]1 monotherapy treatment), median rwPFS and OS are significantly longer in IRS-High vs. IRS-Low patients (rwPFS adjusted hazard ratio [aHR] 0.52, p = 0.003; OS aHR 0.49, p = 0.005); TMB alone does not significantly predict PD-(L)1 rwPFS nor OS. In 146 patients treated with systemic therapy prior to pembrolizumab monotherapy, pembrolizumab rwPFS is only significantly longer than immediately preceding therapy rwPFS in IRS-High patients (interaction test p = 0.001). In propensity matched lung cancer patients treated with first-line pembrolizumab monotherapy or pembrolizumab+chemotherapy, monotherapy rwPFS is significantly shorter in IRS-Low patients, but is not significantly different in IRS-High patients. Across 24,463 molecularly-evaluable trial patients, 7.6% of patients outside of monotherapy PD-(L)1 approved tumor types are IRS-High/TMB-Low.

CONCLUSIONS

The validated, predictive, pan-tumor IRS model can expand PD-(L)1 monotherapy benefit outside currently approved indications.

KRAS Mutations in Solid Tumors: Characteristics, Current Therapeutic Strategy, and Potential Treatment Exploration

Kristen rat sarcoma (KRAS) gene is one of the most common mutated oncogenes in solid tumors. Yet, KRAS inhibitors did not follow suit with the development of targeted therapy, for the structure of KRAS has been considered as being implausible to target for decades. Chemotherapy was the initial recommended therapy for KRAS-mutant cancer patients, which was then replaced by or combined with immunotherapy. KRAS G12C inhibitors became the most recent breakthrough in targeted therapy, with Sotorasib being approved by the Food and Drug Administration (FDA) based on its significant efficacy in multiple clinical studies. However, the subtypes of the KRAS mutations are complex, and the development of inhibitors targeting non-G12C subtypes is still at a relatively early stage. In addition, the monotherapy of KRAS inhibitors has accumulated possible resistance, acquiring the exploration of combination therapies or next-generation KRAS inhibitors. Thus, other non-target, conventional therapies have also been considered as being promising. Here in this review, we went through the characteristics of KRAS mutations in cancer patients, and the prognostic effect that it poses on different therapies and advanced therapeutic strategy, as well as cutting-edge research on the mechanisms of drug resistance, tumor development, and the immune microenvironment.

Panobinostat Induced Spatial In Situ Biomarkers Predictive of Anti-PD-1 Efficacy in Mouse Mammary Carcinoma

Immunotherapies, including anti-PD-1 immune checkpoint blocking (ICB) antibodies, have revolutionized the treatment of many solid malignancies. However, their efficacy in breast cancer has been limited to a subset of patients with triple-negative breast cancer, where ICBs are routinely combined with a range of cytotoxic and targeted agents. Reliable biomarkers predictive of the therapeutic response to ICB in breast cancer are critically missing, though a combination response has been associated with immunogenic cell death (ICD). Here, we utilized a recently developed integrated analytical platform, the multiplex implantable microdevice assay (MIMA), to evaluate the presence and spatial cell relations of literature-based candidate markers predictive of ICB efficacy in luminal mouse mammary carcinoma. MIMA integrates (i) an implantable microdevice for the localized delivery of small amounts of drugs inside the tumor bed with (ii) sequential multiplex immunohistochemistry (mIHC) and spatial cell analysis pipelines to rapidly (within days) describe drug mechanisms of action and find predictive biomarkers in complex tumor tissue. We show that the expression of cleaved caspase-3, ICAM-1, neuropilin-1, myeloperoxidase, calreticulin, galectin-3, and PD-L1 were spatially associated with the efficacy of panobinostat, a pan-HDAC inhibitor that was previously shown to induce immunogenic cell death and synergize with anti-PD-1 in breast cancer. PD-L1 by itself, however, was not a reliable predictor. Instead, ICB efficacy was robustly identified through the in situ hotspot detection of galectin-3-positive non-proliferating tumor zones enriched in cell death and infiltrated by anti-tumor cytotoxic neutrophils positive for ICAM-1 and neuropilin-1. Such hotspots can be specifically detected using distance-based cluster analyses. Single-cell measurements of the functional states in the tumor microenvironment suggest that both qualitative and quantitative effects might drive effective therapy responses. Overall, the presented study provides (i) complementary biological knowledge about the earliest cell events of induced anti-tumor immunity in breast cancer, including the emergence of resistant cancer stem cells, and (ii) newly identified biomarkers in form of specific spatial cell associations. The approach used standard cell-type-, IHC-, and FFPE-based techniques, and therefore the identified spatial clustering of in situ biomarkers can be readily integrated into existing clinical or research workflows, including in luminal breast cancer. Since early drug responses were detected, the biomarkers could be especially applicable to window-of-opportunity clinical trials to rapidly discriminate between responding and resistant patients, thus limiting unnecessary treatment-associated toxicities.

Plasma GDF15 levels associated with circulating immune cells predict the efficacy of PD-1/PD-L1 inhibitor treatment and prognosis in patients with advanced non-small cell lung cancer

PURPOSE

Although increased plasma growth differentiation factor-15 (GDF15) levels have been reported in patients with various cancers, the predictive role of PD-1/PD-L1 inhibitors in advanced cancers remains unknown. This study aimed to investigate GDF15 levels as a predictive marker in advanced non-small cell lung cancer (NSCLC) treated with PD-1/PD-L1 inhibitors and analyze their association with immune cell populations.

METHODS

This study included 87 patients with advanced NSCLC receiving anti-PD-1/PD-L1 inhibitors between March 2018 and May 2020. Blood samples were obtained immediately before and months after PD-1/PD-L1 inhibitor administration.

RESULTS

The objective response rate (ORR) was significantly higher in the low GDF15 than in the high GDF15 group (39.2% vs. 15.3%, P = 0.013). The median progression-free survival (PFS) was significantly longer in the low GDF15 than in the high GDF15 group (13.2 [95% CI 7.6-18.9] vs. 7.2 [95% CI 4.8-9.6] months, P = 0.048). Moreover, plasma GDF15 levels negatively correlated with PD-1⁺/CD8⁺ T cells (r = - 0.399, P = 0.003) and positively with PD-1⁺/Treg cells (r = 0.507, P < 0.001) and PD-1⁺Treg/CD4⁺ T cells (r = 0.439, P < 0.001). The ORR was significantly higher in the group with decreased GDF15 from baseline than in the increased GDF15 group (37.2% vs. 10.0%, P = 0.026). The median PFS was significantly longer in the decreased GDF15 group (14.8 [95% CI 10.4-19.2] vs. 5.9 [95% CI 2.8-9.0] months, P = 0.002). Plasma GDF15 levels were associated with PD-1⁺CD8⁺ T cells and PD-1⁺ Treg cells.

CONCLUSION

Plasma GDF15 could be a potential biomarker for predicting the efficacy and survival benefit of immunotherapy in advanced NSCLC.

Association of Machine Learning-Based Assessment of Tumor-Infiltrating Lymphocytes on Standard Histologic Images With Outcomes of Immunotherapy in Patients With NSCLC

Importance

Currently, predictive biomarkers for response to immune checkpoint inhibitor (ICI) therapy in lung cancer are limited. Identifying such biomarkers would be useful to refine patient selection and guide precision therapy.

Objective

To develop a machine-learning (ML)-based tumor-infiltrating lymphocytes (TILs) scoring approach, and to evaluate TIL association with clinical outcomes in patients with advanced non-small cell lung cancer (NSCLC).

Design, Setting, and Participants

This multicenter retrospective discovery-validation cohort study included 685 ICI-treated patients with NSCLC with median follow-up of 38.1 and 43.3 months for the discovery (n = 446) and validation (n = 239) cohorts, respectively. Patients were treated between February 2014 and September 2021. We developed an ML automated method to count tumor, stroma, and TIL cells in whole-slide hematoxylin-eosin-stained images of NSCLC tumors. Tumor mutational burden (TMB) and programmed death ligand-1 (PD-L1) expression were assessed separately, and clinical response to ICI therapy was determined by medical record review. Data analysis was performed from June 2021 to April 2022.

Exposures

All patients received anti-PD-(L)1 monotherapy.

Main Outcomes and Measures

Objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) were determined by blinded medical record review. The area under curve (AUC) of TIL levels, TMB, and PD-L1 in predicting ICI response were calculated using ORR.

Results

Overall, there were 248 (56%) women in the discovery cohort and 97 (41%) in the validation cohort. In a multivariable analysis, high TIL level (≥250 cells/mm2) was independently associated with ICI response in both the discovery (PFS: HR, 0.71; P = .006; OS: HR, 0.74; P = .03) and validation (PFS: HR = 0.80; P = .01; OS: HR = 0.75; P = .001) cohorts. Survival benefit was seen in both first- and subsequent-line ICI treatments in patients with NSCLC. In the discovery cohort, the combined models of TILs/PD-L1 or TMB/PD-L1 had additional specificity in differentiating ICI responders compared with PD-L1 alone. In the PD-L1 negative (<1%) subgroup, TIL levels had superior classification accuracy for ICI response (AUC = 0.77) compared with TMB (AUC = 0.65).

Conclusions and Relevance

In these cohorts, TIL levels were robustly and independently associated with response to ICI treatment. Patient TIL assessment is relatively easily incorporated into the workflow of pathology laboratories at minimal additional cost, and may enhance precision therapy.

Predictive Biomarkers for Immunotherapy in Lung Cancer: Perspective From the International Association for the Study of Lung Cancer Pathology Committee

Immunotherapy including immune checkpoint inhibitors (ICIs) has become the backbone of treatment for most lung cancers with advanced or metastatic disease. In addition, they have increasingly been used for early stage tumors in neoadjuvant and adjuvant settings. Unfortunately, however, only a subset of patients experiences meaningful response to ICIs. Although programmed death-ligand 1 (PD-L1) protein expression by immunohistochemistry (IHC) has played a role as the principal predictive biomarker for immunotherapy, its performance may not be optimal, and it suffers multiple practical issues with different companion diagnostic assays approved. Similarly, tumor mutational burden (TMB) has multiple technical issues as a predictive biomarker for ICIs. Now, ongoing research on tumor- and host immune-specific factors has identified immunotherapy biomarkers that may provide better response and prognosis prediction, in particular in a multimodal approach. This review by the International Association for the Study of Lung Cancer Pathology Committee provides an overview of various immunotherapy biomarkers, including updated data on PD-L1 IHC and TMB, and assessments of neoantigens, genetic and epigenetic signatures, immune microenvironment by IHC and transcriptomics, and microbiome and pathologic response to neoadjuvant immunotherapies. The aim of this review is to underline the efficacy of new individual or combined predictive biomarkers beyond PD-L1 IHC and TMB.

Delineation of a SMARCA4-specific competing endogenous RNA network and its function in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignancy worldwide, and the mortality rate continues to rise each year. SMARCA4 expression has been associated with poor prognosis in various types of cancer; however, the specific mechanism of action of SMARCA4 in HCC needs to be fully elucidated.

AIM

To explore the specific mechanism of action of SMARCA4 in HCC.

METHODS

Herein, the expression level of SMARCA4 as well as its association with HCC prognosis were evaluated using transcriptome profiling and clinical data of 18 different types of cancer collected from The Cancer Genome Atlas database. Furthermore, SMARCA4-high and -low groups were identified. Thereafter, gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to identify the function of SMARCA4, followed by construction of a SMARCA4-specific competing endogenous RNA (ceRNA) network using starBase database. The role of SMARCA4 in immunotherapy and its association with immune cells were assessed using correlation analysis.

RESULTS

It was observed that SMARCA4 was overexpressed and negatively correlated with prognosis in HCC. Further, SMARCA4 expression was positively associated with tumor mutational burden, microsatellite stability, and immunotherapy efficacy. The SNHG3/THUMP3-AS1-miR-139-5p-SMARCA4 ceRNA network was established and could be assumed to serve as a stimulatory mechanism in HCC.

CONCLUSION

The findings of this study demonstrated that SMARCA4 plays a significant role in progression and immune infiltration in HCC. Moreover, a ceRNA network was detected, which was found to be correlated with poor prognosis in HCC. The findings of this study could contribute towards the identification of predictive markers for immunotherapy and a novel mechanism of action for HCC treatment.

Construction of Prognostic Risk Model for Small Cell Lung Cancer Based on Immune-Related Genes

Small cell lung cancer (SCLC) is a highly invasive and fatal malignancy. Research at the present stage implied that the expression of immune-related genes is associated with the prognosis in SCLC. Accordingly, it is essential to explore effective immune-related molecular markers to judge prognosis and treat SCLC. Our research obtained SCLC dataset from Gene Expression Omnibus (GEO) and subjected mRNAs in it to differential expression analysis. Differentially expressed mRNAs (DEmRNAs) were intersected with immune-related genes to yield immune-related differentially expressed genes (DEGs). The functions of these DEGs were revealed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Thereafter, we categorized 3 subtypes of immune-related DEGs via K-means clustering. Kaplan-Meier curves analyzed the effects of 3 subtypes on SCLC patients' survival. Single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE validated that the activation of different immune gene subtypes differed significantly. Finally, an immune-related-7-gene assessment model was constructed by univariate-Lasso-multiple Cox regression analyses. Riskscores, Kaplan-Meier curves, receiver operating characteristic (ROC) curves, and independent prognostic analyses validated the prognostic value of the immune-related-7-gene assessment model. As suggested by GSEA, there was a prominent difference in cytokine-related pathways between high- and low-risk groups. As the analysis went further, we discovered a statistically significant difference in the expression of human leukocyte antigen (HLA) proteins and costimulatory molecules expressed on the surface of CD274, CD152, and T lymphocytes in different groups. In a word, we started with immune-related genes to construct the prognostic model for SCLC, which could effectively evaluate the clinical outcomes and offer guidance for the treatment and prognosis of SCLC patients.

Transcriptomic Correlates of Tumor Cell PD-L1 Expression and Response to Nivolumab Monotherapy in Metastatic Clear Cell Renal Cell Carcinoma

PURPOSE

PD-L1 expression on tumor cells (TC) is associated with response to anti-PD-1-based therapies in some tumor types, but its significance in clear cell renal cell carcinoma (ccRCC) is uncertain. We leveraged tumor heterogeneity to identify molecular correlates of TC PD-L1 expression in ccRCC and assessed their role in predicting response to anti-PD-1 monotherapy.

EXPERIMENTAL DESIGN

RNA sequencing was performed on paired TC PD-L1 positive and negative areas isolated from eight ccRCC tumors and transcriptomic features associated with PD-L1 status were identified. A cohort of 232 patients with metastatic ccRCC from the randomized CheckMate-025 (CM-025) trial was used to confirm the findings and correlate transcriptomic profiles with clinical outcomes.

RESULTS

In both the paired samples and the CM-025 cohort, TC PD-L1 expression was associated with combined overexpression of immune- and cell proliferation-related pathways, upregulation of T-cell activation signatures, and increased tumor-infiltrating immune cells. In the CM-025 cohort, TC PD-L1 expression was not associated with clinical outcomes. A molecular RCC subtype characterized by combined overexpression of immune- and cell proliferation-related pathways (previously defined by unsupervised clustering of transcriptomic data) was enriched in TC PD-L1 positive tumors and displayed longer progression-free survival (HR, 0.32; 95% confidence interval, 0.13-0.83) and higher objective response rate (30% vs. 0%, P = 0.04) on nivolumab compared with everolimus.

CONCLUSIONS

Both TC-extrinsic (immune-related) and TC-intrinsic (cell proliferation-related) mechanisms are likely intertwined in the regulation of TC PD-L1 expression in ccRCC. The quantitation of these transcriptional programs may better predict benefit from anti-PD-1-based therapy compared with TC PD-L1 expression alone in ccRCC.

Sintilimab plus docetaxel as second-line therapy of advanced non-small cell lung cancer without targetable mutations: a phase II efficacy and biomarker study

BACKGROUND

Single-agent immunotherapy is currently the recommended second-line therapy for patients with advanced non-small cell lung cancer (NSCLC) without targetable mutations; however, the objective response rate (ORR) remains low. This phase II study evaluated the efficacy of the combination therapy of sintilimab plus docetaxel and explored potential biomarkers for efficacy prediction.

METHODS

Thirty patients with NSCLC without targetable mutations whose disease progressed from first-line platinum-based chemotherapy from October 2019 to December 2020 were enrolled in this single-arm, single-center, phase II trial. Sintilimab (200 mg) and docetaxel (75 mg/m2) were administered every 3 weeks until progression. The primary endpoint was ORR. Secondary endpoints included progression-free survival (PFS), overall survival (OS), and safety. Biomarker analyses of blood and tissue samples were also performed.

RESULTS

Among 30 patients, 11 patients had partial response, resulting in an ORR of 36.7%. The median PFS was 5.0 months (95%CI: 3.9-6.1) and OS was 13.4 months (95%CI: 5.6-21.2). The most common immune-related adverse event of any grade was hepatitis, observed in 23.3% (7/30) of patients. Treatment-emergent adverse events were manageable. Patients detected with high PD-L1 expression in circulating tumor cells (cutoff value ≥32.5% based on the median CTC-PD-L1 expression) achieved significantly higher ORR (60% versus 13.3%, p = 0.021) and significantly longer median PFS (6.0 versus 3.5 months, p = 0.011) and median OS (15.8 versus 9.0 months, p = 0.038) than those with low CTC-PD-L1 level. Patients detected with PD-L1 < 1% and CD8 ≥ 1% expression from their baseline tissue samples had significantly higher ORR (83.3% versus 12.5%, p = 0.026) but similar PFS (p = 0.62) and OS (p = 0.15).

CONCLUSION

This study demonstrated the effectiveness and safety of sintilimab plus docetaxel as a second-line treatment of NSCLC without targetable mutations after progression from first-line platinum-based chemotherapy.

TRIAL REGISTRATION

This study was registered in the Clinical trials registry with ClinicalTrials.gov Identifier NCT03798743 (SUCCESS).

Impact of pharmacodynamic biomarkers in immuno-oncology phase 1 clinical trials

BACKGROUND

Phase 1 immuno-oncology (IO) trials frequently involve pharmacodynamic (PD) biomarker assessments involving tumour biopsies and/or blood collection, with increasing use of molecular imaging. PD biomarkers are set to play a fundamental role in early drug development of immuno-oncology (IO) agents. In the IO era, the impact of PD biomarkers for confirmation of biologic activity and their role in subsequent drug development have not been investigated.

METHODS

Phase 1 studies published between January 2014 and December 2020 were reviewed. Studies that reported on-treatment PD biomarkers [tissue-derived (tissue-PD), blood-based (blood-PD) and imaging-based (imaging-PD)] were analysed. PD biomarker results and their correlation with clinical activity endpoints were evaluated. Authors' statements on the influence of PD biomarkers on further drug development decisions, and subsequent citations of PD biomarker study results were recorded.

RESULTS

Among 386 trials, the most frequent IO agent classes evaluated were vaccines (32%) and PD-(L)1 inhibitors (25%). No PD biomarker assessments were reported in 100 trials (26%). Of the remaining 286, blood-PD, tissue-PD, and imaging-PD data were reported in 270 (94%), 94 (33%), and 12 (4%) trials, respectively. Assessments of more than one PD biomarker type were reported in 82 studies (29%). Similar proportions of blood-PD (9%), tissue-PD (7%), and imaging-PD studies (8%) had positive results that correlated with clinical activity. Results of 22 PD biomarker studies (8%) were referenced in subsequent clinical trials.

CONCLUSIONS

Most phase 1 IO studies performed PD biomarker assessments. Overall, positive PD biomarker results were infrequently correlated with clinical activity or cited in subsequent trials, suggesting a limited impact on subsequent drug development. With emerging health regulatory emphasis on optimal dose selection based on PD activity, more informative and integrative multiplexed assays that capture the complexity of tumour-host immunity interactions are warranted to improve phase 1 IO trial methodology.

PD-L1 Expression in Non-Small Cell Lung Cancer Specimens: Association with Clinicopathological Factors and Molecular Alterations

Immune checkpoint inhibitors (ICI) targeting programmed cell death-1 or its ligand (PD-L1) have improved outcomes in non-small cell lung cancer (NSCLC). High tumor PD-L1 expression, detected by immunohistochemistry (IHC) typically on formalin-fixed paraffin-embedded (FFPE) histological specimens, is linked to better response. Following our previous investigation on PD-L1 in cytological samples, the aim of this study was to further explore the potential impacts of various clinicopathological and molecular factors on PD-L1 expression. Two retrospective NSCLC cohorts of 1131 and 651 specimens, respectively, were investigated for PD-L1 expression (<1%/1−49%/≥50%), sample type, sample site, histological type, and oncogenic driver status. In both cohorts, PD-L1 was positive (≥1%) in 55% of the cases. Adenocarcinomas exhibited lower PD-L1 expression than squamous cell carcinomas (p < 0.0001), while there was no difference between sample types, tumor locations, or between the two cohorts in multivariate analysis (all p ≥ 0.28). Mutational status correlated significantly with PD-L1 expression (p < 0.0001), with the highest expression for KRAS-mutated cases, the lowest for EGFR-mutated, and the KRAS/EGFR wild-type cases in between. There was no difference in PD-L1 levels between different prevalent KRAS mutations (all p ≥ 0.44), while mucinous KRAS-mutated adenocarcinomas exhibited much lower PD-L1 expression than non-mucinous (p < 0.0001). Our data indicate that cytological and histological specimens are comparable for PD-L1 evaluation. Given the impact of KRAS mutations and the mucinous growth pattern on PD-L1 expression, these factors should be further investigated in studies on ICI response.

Ferroptosis Patterns and Tumor Microenvironment Infiltration Characterization in Bladder Cancer

Background: Ferroptosis is a unique iron-dependent form of cell death and bladder cancer (BCa) is one of the top ten most common cancer types in the world. However, the role of ferroptosis in shaping the tumor microenvironment and influencing tumor clinicopathological features remains unknown.

Methods: Using the data downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we comprehensively evaluated the ferroptosis patterns of 570 BCa samples based on 234 validated ferroptosis genes reported in the FerrDb database and systematically correlated these ferroptosis patterns with tumor microenvironment (TME) cell-infiltrating characteristics. The ferroptosis score was constructed to quantify ferroptosis patterns of individuals using principal component analysis (PCA) algorithms.

Results: Four distinct ferroptosis patterns and two gene clusters were finally determined. Significant differences in clinical characteristics and the prognosis of patients were found among different ferroptosis patterns and gene clusters, so were in the mRNA transcriptome and the landscape of TME immune cell infiltration. We also established a set of scoring system to quantify the ferroptosis pattern of individual patients with BCa named the ferroptosis score, which was discovered to tightly interact with clinical signatures such as the TNM category and tumor grade and could predict the prognosis of patients with BCa. Moreover, tumor mutation burden (TMB) was positively correlated to the ferroptosis score, and the low ferroptosis score was related to a better response to immunotherapy using PD-1 blockade. Finally, we also found there existed a positive correlation between the sensitivity to cisplatin chemotherapy and ferroptosis score.

Conclusions: Our work demonstrated and interpreted the complicated regulation mechanisms of ferroptosis on the tumor microenvironment and that better understanding and evaluating ferroptosis patterns could be helpful in guiding the clinical therapeutic strategy and improving the prognosis of patients with BCa.

SMARCA4-deficient rectal carcinoma with a sarcomatoid component: a case report

A new classification of SMARCA4-deficient tumors was proposed recently for thoracic malignancies, and the tumors have some histopathological characteristics similar to those of carcinosarcoma. We encountered a case of SMARCA4-deficient rectal carcinoma with a sarcomatoid component. A 46-year-old man presented to our hospital with a prolapsing anal mass. Colonoscopy revealed an irregular, nodular, and elevated lesion in the rectum, and the biopsy revealed a moderately differentiated adenocarcinoma. Abdominoperineal resection of the rectum was performed. A macroscopic image of the resected specimen showed a complex tumor 3.5 cm × 3 cm in size with a papillary protrusion and an irregular ulcerative lesion. Histopathological examination revealed that the tumor was composed of moderately/poorly differentiated adenocarcinoma and atypical spindle cells. The adenocarcinoma component was positive for epithelial markers (AE1/AE3 and carcinoembryonic antigen) and showed deletion of SMARCA2 and SMARCA4, while the spindle cells expressed mesenchymal markers (α-smooth muscle actin and vimentin). The pathological diagnosis was poorly differentiated adenocarcinoma with a sarcomatoid component, pT3N2bM0, stage IIIc. Although our case had histological characteristics of carcinosarcoma, immunostaining revealed a deficiency of SMARCA4. This case presented a SMARCA4-deficient colorectal carcinoma with a sarcomatoid component, which was histopathologically similar to carcinosarcoma.