Programmed Death-Ligand 1 Heterogeneity and Its Impact on Benefit From Immune Checkpoint Inhibitors in NSCLC

Impact of assessment-to-treatment interval and metastatic biopsy site on the predictive value of PD-L1 expression at the 1 % cut-off level in melanoma

BACKGROUND

Intratumoral PD-L1 expression at the 1 % cut-off predicts clinical outcomes and may guide first-line immune checkpoint inhibitor (ICI) selection for metastatic melanoma (MM). However, the impact of the interval between PD-L1 assessment and ICI initiation and the metastatic site used for PD-L1 evaluation, remains unclear.

METHODS

In this nationwide cohort study we used the Danish Metastatic Melanoma Database (DAMMED) and the Danish Pathology Registry to analyze patients with MM treated with anti-PD-1 or anti-PD-1 plus anti-CTLA-4 from January 2017 to February 2024. Progression-free survival (PFS) and overall survival (OS) were analyzed using Log-rank tests and Cox regression.

RESULTS

Data from 1137 patients were analyzed. Among patients with PD-L1 assessed within 90 days of treatment (n = 964; 55.2 % PD-L1 <1 %, 44.8 % PD-L1 ≥1 %), combination therapy improved outcomes in PD-L1 < 1 % (PFS adjusted (a)HR 0.62; 95 % CI 0.48-0.80; p < 0.001, OS aHR 0.64; 95 % CI 0.48-0.85; p = 0.002), while outcomes were comparable for PD-L1 ≥ 1 % patients (PFS aHR 0.90; 95 % CI 0.62-1.30; p = 0.57, OS aHR 0.97; 95 % CI 0.60-1.57; p = 0.89). For PD-L1 assessed > 90 days prior (n = 173), this pattern was less pronounced. Among 48 paired PD-L1 assessments from the same organ, discordance occurred in 25 %. Combination therapy improved PFS for patients with PD-L1 < 1 % skin/subcutaneous (aHR 0.51; 95 % CI 0.34-0.76; p < 0.001) and visceral metastases (aHR 0.65; 95 % CI 0.42-1.02; p = 0.060) while this association was not evident for lymph node metastases (aHR 0.79; 95 % CI 0.48-1.29; p = 0.35).

CONCLUSIONS

PD-L1 seems a reliable predictive biomarker in MM, when assessed on tissue obtained within 90 days prior to ICI initiation. Non-nodal metastatic sites appear preferable.

PD-L1 imaging with [99mTc]NM-01 SPECT/CT is associated with metabolic response to pembrolizumab with/without chemotherapy in advanced lung cancer

BACKGROUND

Programmed death-ligand 1 (PD-L1) immunohistochemistry is a predictive biomarker for anti-PD-(L)1 therapy in non-small cell lung cancer (NSCLC). It is not a reliable predictor of clinical benefit with non-invasive imaging providing a potential solution. We present the PECan study, the aim of which to assess the relationship of [99mTc]-labeled anti-PD-L1 single-domain antibody (NM-01) single-photon emission computed tomography (SPECT)/CT with metabolic response to anti-PD-(L)1.

METHODS

PD-L1 tumour proportion score (TPS) measured using SP263 assay. [99mTc]NM-01 SPECT/CT and [18F]FDG PET/CT performed before and 9-weeks following pembrolizumab with/without chemotherapy in patients with advanced NSCLC. Tumor (T) to blood pool (BP) maximum region of interest (ROImax) measurements performed in primary and metastatic lesions using SPECT/CT images.

RESULTS

Fifteen patients were included (median age 63 years, 9 male). Intertumoural heterogeneity evident in 10(67%) patients. Mean [99mTc]NM-01 T:BP demonstrated moderate correlation with PD-L1 TPS (r = 0.45, p < 0.05). Depth of [18F]FDG PET/CT metabolic response at 9-weeks (n = 13), correlated strongly with baseline [99mTc]NM-01 T:BP (r = -0.73, p < 0.05), but only moderately with PD-L1 TPS (r = -0.46, p = 0.06).

CONCLUSION

[99mTc]NM-01 SPECT/CT allows non-invasive quantification of PD-L1 in primary tumour and metastases in NSCLC. [99mTc]NM-01 uptake moderately correlates with PD-L1 immunohistochemistry, determines heterogeneity, and is associated with early metabolic response to anti-PD-1 pembrolizumab.

CLINICAL TRIALS REGISTRATION

PD-L1 Expression in Cancer (PECan) study (NCT04436406), registered 18 June 2020 https://clinicaltrials.gov/ct2/show/NCT04436406.

EGFR mutation status affects intra-tumoural heterogeneity of PD-L1 expression but not agreement between assays in resectable non-small cell lung cancer

BACKGROUND

The predictive value of PD-L1 to select patients for immunotherapy in resectable NSCLC remains imprecise, confounded by different assays used across trials and intra-tumoural heterogeneity (ITH). We sought to compare the concordance between 3 PD-L1 antibodies stratified by EGFR mutation status, evaluate ITH and implications on survival outcomes.

METHODS

Tissue microarrays were constructed from stage IA-IIIA NSCLC with 3 tumour cores per patient. Tumour proportion score (TPS) was evaluated by 3 pathologists for SP263, SP142, 22C3 and analysed in tertiles of < 1 %, 1-49 % and ≥ 50 %. ITH was defined as discordant TPS in ≥ 2/3 tumour cores. Cohen's kappa test was used to assess agreement. Survival outcomes were estimated using Kaplan-Meier.

RESULTS

A total of 561 patients were included, 59.5% (334/561) were EGFR-mutant. Stage IA comprised 45.5%(255/561), IB 24.1%(135/561), IIA 12.7%(71/561), IIB 4.5%(25/561) and IIIA 13.4%(75/561). Across 1683 tumour cores, SP263 and 22C3 had the highest concordance (Kappa = 0.689), followed by 22C3 and SP142 (Kappa = 0.354), then SP263 and SP142 (Kappa = 0.284), similar between EGFR-mutant and EGFR-wildtype. Agreement between pathologists was almost perfect. ITH by SP263 was observed in 14.1 % of EGFR-mutant versus 24.2 % in EGFR-wildtype(p = 0.002). Discordance was highest among TPS 1-49 % at 92.6 % (88/95) followed by ≥ 50 % at 37.8 % (14/37) and least among < 1 % at 0 % (0/429) (p < 0.001). For tumour cores scored 1-49 %, 63 %/70 % of adjacent cores were scored < 1 % for EGFR-wildtype/mutant respectively. Histological grade was the only independent predictor of PD-L1 ITH on multivariable analysis. PD-L1 ITH was not associated with survival on multivariable analysis.

CONCLUSION

PD-L1 scoring by SP263 and 22C3 are interchangeable but not SP142 regardless of EGFR status. PD-L1 ITH was more common in EGFR-wildtype versus EGFR-mutant tumours. Extra care should be taken to select the most representative tumour core for tumours with high histological grade or TPS 1-49% as this may influence peri-operative treatment decisions.

Intratumoral and peritumoral PET/CT-based radiomics for non-invasively and dynamically predicting immunotherapy response in NSCLC

BACKGROUND

We aimed to develop a machine learning model based on intratumoral and peritumoral 18F-FDG PET/CT radiomics to non-invasively and dynamically predict the response to immunotherapy in non-small cell lung cancer (NSCLC).

METHODS

This retrospective study included 296 NSCLC patients, including a training cohort (N = 183), a testing cohort (N = 78), and a TCIA radiogenomic cohort (N = 35). The extreme gradient boosting algorithm was employed to develop the radiomic models.

RESULTS

The COMB-Radscore, which was developed by combining radiomic features from PET, CT, and PET/CT images, had the most satisfactory predictive performance with AUC (ROC) 0.894 and 0.819 in the training and testing cohorts, respectively. Survival analysis has demonstrated that COMB-Radscore is an independent prognostic factor for progression-free survival and overall survival. Moreover, COMB-Radscore demonstrates excellent dynamic predictive performance, with an AUC (ROC) of 0.857, enabling the earlier detection of potential disease progression in patients compared to radiological evaluation solely relying on tumor size. Further radiogenomic analysis showed that the COMB-Radscore was associated with infiltration abundance and functional status of CD8 + T cells.

CONCLUSIONS

The radiomic model holds promise as a precise, personalized, and dynamic decision support tool for the treatment of NSCLC patients.

Tumor Heterogeneity and the Immune Response in Non-Small Cell Lung Cancer: Emerging Insights and Implications for Immunotherapy

Resistance to immune checkpoint inhibitors (ICIs) represents a major challenge for the effective treatment of non-small cell lung cancer (NSCLC). Tumor heterogeneity has been identified as an important mechanism of treatment resistance in cancer and has been increasingly implicated in ICI resistance. The diversity and clonality of tumor neoantigens, which represent the target epitopes for tumor-specific immune cells, have been shown to impact the efficacy of immunotherapy. Advances in genomic techniques have further enhanced our understanding of clonal landscapes within NSCLC and their evolution in response to therapy. In this review, we examine the role of tumor heterogeneity during immune surveillance in NSCLC and highlight its spatial and temporal evolution as revealed by modern technologies. We explore additional sources of heterogeneity, including epigenetic and metabolic factors, that have come under greater scrutiny as potential mediators of the immune response. We finally discuss the implications of tumor heterogeneity on the efficacy of ICIs and highlight potential strategies for overcoming therapeutic resistance.

Spatial Heterogeneity of PD-L1 Expression as a Biomarker for Third-Generation EGFR-TKI Response in Advanced EGFR-Mutant NSCLC

The association between the spatial heterogeneity of programmed cell death ligand 1 (PD-L1) expression and the efficacy of third-generation epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in EGFR-mutant non-small cell lung cancer (NSCLC) remains elusive. This retrospective study analyzed data from 4171 NSCLC patients with EGFR-sensitive mutations treated at Shanghai Chest Hospital from August 2019 to September 2023. Among them, 182 patients receiving third-generation EGFR-TKIs monotherapy as a first-line treatment were enrolled. Patients were categorized by biopsy sites into primary lung lesions (n = 112) and metastatic lymph nodes (n = 70). PD-L1 expression was stratified based on tumor cell proportion score (TPS): < 1%, 1%-49%, and ≥ 50%. The median progression-free survival (PFS) for the entire cohort was 18.33 months. In the PD-L1 TPS group, PFS was 18.87 months for TPS < 1%, 17.6 months for TPS 1%-49%, and 13.6 months for TPS ≥ 50%, with significant differences across groups (p = 0.026). Moreover, multivariate analysis identified smoking history [HR = 1.653, 95% CI (1.132-2.414), p = 0.009] and TPS ≥ 50% [HR = 2.069, 95% CI (1.183-3.618), p = 0.011] as independent risk factors. In primary lesions, the median PFS was 21.93 months for TPS < 1%, 18.57 months for TPS 1%-49%, and 10.17 months for TPS ≥ 50%, with significant differences (p < 0.001). However, PD-L1 expression in metastatic lymph nodes was not associated with PFS (p = 0.973). In advanced EGFR-mutant NSCLC, high PD-L1 expression may suggest reduced efficacy of third-generation EGFR-TKIs. The spatial heterogeneity of PD-L1 expression could influence its predictive accuracy for third-generation EGFR-TKI efficacy.

Immunotherapy for advanced-stage squamous cell lung cancer: the state of the art and outstanding questions

Immune-checkpoint inhibitors (ICIs) have transformed the treatment paradigm for advanced-stage squamous non-small-cell lung cancer (LUSC), a histological subtype associated with inferior outcomes compared with lung adenocarcinoma. However, only a subset of patients derive durable clinical benefit. In the first-line setting, multiple ICI regimens are available, including anti-PD-(L)1 antibodies as monotherapy, in combination with chemotherapy, or with an anti-CTLA4 antibody with or without chemotherapy. Several important questions persist regarding the optimal regimen for individual patients, particularly how to identify patients who might benefit from adding chemotherapy and/or anti-CTLA4 antibodies to anti-PD-(L)1 antibodies. An urgent need exists for predictive biomarkers beyond PD-L1 to better guide precision oncology approaches. Deeper knowledge of the underlying molecular biology of LUSC and its implications for response to ICIs will be important in this regard. Integration of this knowledge into multi-omics methods coupled with artificial intelligence might enable the development of more robust biomarkers. Finally, several novel therapeutic strategies, including novel ICIs, bispecific antibodies and personalized cancer vaccines, are emerging. Addressing these unresolved questions through innovative clinical trials and translational research will be crucial to further improving the outcomes of patients with LUSC. In this Review, we provide a comprehensive overview of current immunotherapeutic approaches, unresolved challenges and emerging strategies for patients with LUSC.

Prospects and Challenges of Immunotherapy for Thyroid Cancer

BACKGROUND

Thyroid cancer generally boasts a favorable prognosis; however, advanced and refractory cases exhibit aggressive characteristics and resistance to conventional therapies, necessitating the investigation of innovative treatment modalities. Immunotherapy, which harnesses the body's immune system to target cancer cells, has shown considerable promise for specific thyroid cancer subtypes.

OBJECTIVE

This review article aims to encapsulate the latest advancements in immunotherapy for thyroid cancer, examining its mechanisms, therapeutic efficacy, ongoing challenges, and the potential benefits of combination therapy approaches.

METHODS

An extensive literature review and critical analysis of clinical trial data were conducted to inform this synthesis.

RESULTS

The review reveals that immunotherapy strategies, encompassing immune checkpoint inhibitors, CAR-T cell therapy, tumor vaccines, and immunomodulators, are demonstrating efficacy in the treatment of thyroid cancer. Notably, checkpoint inhibitors have been particularly effective in anaplastic and poorly differentiated thyroid cancers, albeit with challenges such as treatment resistance and adverse effects. The application of CAR-T cell therapy, successful in hematologic cancers, provides a novel perspective for thyroid cancer treatment, although its efficacy in solid tumors requires further study. Additionally, research into tumor vaccines and immunomodulators is advancing, with preliminary evidence suggesting their therapeutic potential for thyroid cancer patients.

CONCLUSION

The recognition of the immune microenvironment's role in treatment responsiveness is pivotal for enhancing the care of thyroid cancer patients. This review underscores the significance of combination therapy as a means to optimize treatment outcomes and charts a course for future research endeavors to broaden the spectrum of effective treatment options available to thyroid cancer patients.

Development and First-in-Human evaluation of a Site-Specific [18F]-Labeled PD-L1 nanobody PET radiotracer for noninvasive imaging in NSCLC

Immunohistochemistry (IHC) for PD-L1 detection is limited by its invasiveness and heterogeneity of tumors. To address these challenges, a new PD-L1-targeted nanobody-based immune-PET radiotracer [18F]AlF-APN09 was developed using the site-specific radiolabeling method with the complexing agent (Mal-RESCA) under mild conditions. [18F]AlF-APN09 was prepared at room temperature (pH 4.6-4.8) within 20 min with satisfactory radiochemical yields (45.8 ± 4.48 %, non-decay corrected), high radiochemical purity (>98 %) and moderate apparent molar activity (15-35 GBq/μmol), and remained stable in both PBS and 5 % HSA after 4 h (>90 %). Cell uptake studies indicated variable levels of surface PD-L1 expression in the following order: A549PD-L1 > H1975 > A549. In micro-PET/CT imaging, A549PD-L1 and H1975 tumors were distinctly visualized in a 6.0:1 and 3.2:1 ratios over PD-L1-negative A549 tumors in vivo. Ex vivo biodistribution studies showed tumor uptake values of 6.47 ± 1.06 %ID/g (A549PD-L1) and 2.27 ± 0.19 %ID/g (H1975), significantly higher than 0.90 ± 0.28 %ID/g in A549 tumors. The estimated effective radiation dose in humans was 8.65E-03 mSv/MBq, lower than that of conventional [18F]FDG. First-in-human imaging was conducted on a single resectable non-small cell lung cancer (NSCLC) subject without any adverse reactions. The radiotracer exhibited renal excretion with minimal hepatobiliary clearance. Tumor uptake reached SUVmax 4.20 at 2 h post-injection, demonstrating high contrast and rapid clearance. After PD-1 inhibitor immunotherapy and chemotherapy, the subject showed a therapeutic response and postoperative pathological specimens confirmed a major pathological response (MPR). These results suggest that we have successfully developed a new PD-L1-targeted nanobody PET tracer using the site-specific labeling method with the complexing agent (Mal-RESCA) within 20 min under mild conditions and [18F]AlF-APN09 is a promising noninvasive PET radiotracer for visualizing PD-L1 expression in tumors, offering rapid tumor targeting, excellent signal-to-noise ratios, and favorable clearance properties.

A Cohort Study on Dual Predictive Markers of Immune Combination Therapy for Advanced Non-Small Cell Lung Cancer

Background

Immune checkpoint inhibitors (ICIs) hold a great promise in treatment of non-small cell lung cancer (NSCLC), while only a portion of patients benefited from the treatment, and others could not achieve optimal therapeutic effects from initial immunotherapy, even for those patients with PD-L1 (Programed cell death ligand 1) tested positive. However, the clinical markers for the selection of patients who will benefit from ICIs combination treatment beforehand are largely unknown.

Objectives

The purpose of this study was to explore the non-invasive biomarkers that can predict the efficacy of immune combination therapy in advanced/metastatic NSCLC patients.

Design

This study employed a retrospective cohort design to analyze dual predictive biomarkers in advanced non-small cell lung cancer (NSCLC) patients with immune combination therapy.

Method

An analysis was conducted on baseline information of 144 patients with advanced/metastatic NSCLC who received ICIs treatment from the November of 2018 to the January of 2023 in Beijing Chest Hospital. We established a scoring group chart to make quantitative prediction for overall survival (OS) and progression-free survival (PFS) based on 4 variables, and set up the nomogram model as well as Decision curve analysis (DCA) to assess clinical benefits of ICIs combination in treatment of patients with advanced/metastatic NSCLC.

Results

We found that serum globulin (GLB) >26.6 (g/L) (HR = 1.865, P = .002), absolute neutrophil counts (ANC) (109/L) > 5 (HR = 2.146, P < .001), and bone metastasis (HR = 2.148, P < .001) were independent factors affecting the PFS of NSCLC patients. GLB > 26.6 (g/L) (HR = 1.741, P = .018), ANC (109/L) >5 (HR = 1.807, P = .008), bone metastasis (HR = 1.651, P = .002), and PD-L1 Negative (HR = 2.432, P = .032) were independent factors affecting the OS of NSCLC patients. Same variables and cut-off value have good predictive efficacy in both PFS and OS.

Conclusion

In patients with advanced/metastatic NSCLC receiving ICIs combination treatment, the GLB, ANC, bone metastasis, and PD-L1 may serve as useful predictive markers for the prognosis of NSCLC patients with ICIs combination treatment.

Supraclavicular Lymph Node Metastases in Advanced Lung Cancer: Prevalence and Analysis of Demographic, Clinical and Molecular Characteristics

BACKGROUND

The prevalence of supraclavicular lymph nodes metastases (SNM) in advanced lung cancer has not been systematically evaluated, nor has then been a comparison of demographic, clinical, or molecular characteristics between patients with and without SNM.

METHODS

In this prospective cohort study, the presence of SNM was evaluated using imaging studies (CT, PET, neck ultrasonography) in patients with suspected advanced lung cancer referred for biopsy aimed at diagnosis and molecular profiling. Ultrasound-guided biopsy confirmed or excluded metastatic involvement when suspicious supraclavicular nodes were identified. We assessed the prevalence of SNM and compared the demographic, clinicopathologic and molecular characteristics of patients with and without SNM.

RESULTS

Among the 348 patients with advanced lung cancer, 94 (27%) had SMN. SMN was more common in small cell lung cancer (24/48, 50%) and adenocarcinoma (61/248, 24.6%) than in squamous cell carcinoma (4/35, 11.4%). Compared to patients without SMN, those with SMN were more likely to have small-cell lung cancer, N2/3 disease (97.9 vs. 83.9%, P < .0001), liver metastases (29.8% vs. 16.1% P = .006), and metastases to less common sites (33.7% vs. 14.1%, P < .0001). The prevalence of genomic alterations and PD-L1 expression did not differ between biopsy samples obtained from SNM and those from the primary tumor or other metastatic sites.

CONCLUSION

SNM is common in patients with advanced small-cell lung cancer and adenocarcinoma. Ultrasound-guided biopsy of SNM is a simple and relatively inexpensive method for obtaining adequate tissue samples for diagnosis and comprehensive molecular profiling.

A comprehensive insights of cancer immunotherapy resistance

Cancer is a major global health issue that is usually treated with multiple therapies, such as chemotherapy and targeted therapies like immunotherapy. Immunotherapy is a new and alternative approach to treating various types of cancer that are difficult to treat with other methods. Although immune checkpoint inhibitors have shown promise for long-term efficacy, they have limited effectiveness in common cancer types such as breast, prostate, and lung. Some patients do not respond to immunotherapy, while others develop resistance to the treatment over time, which is classified as primary or acquired resistance. Cancer immunotherapy, specifically immune checkpoint inhibitor-based resistance involves multiple factors such as genes, metabolism, inflammation, and angiogenesis. However, cutting-edge research has identified the mechanisms of immunotherapy resistance and possible solutions. Current research may improve biomarker identification and modify treatment strategies, which will lead to better clinical outcomes. This review provides a comprehensive discussion of the current mechanisms of immunotherapy resistance, related biomarker modulation, and strategies to overcome resistance.

IRF4: A potential prognostic biomarker for immunotherapy in NSCLC

BACKGROUND

Immunotherapy is revolutionizing the management of advanced non-small cell lung cancer (NSCLC). However, sustained responses are observed in only a minority of patients. Reliable biomarkers are required to identify potential beneficiaries. Interferon regulatory factor 4 (IRF4) plays a crucial role in immune regulation, suggesting its potential as a prognostic biomarker in NSCLC immunotherapy. This study aimed to investigate the predictive role of IRF4 expression in patients with NSCLC receiving immunotherapy.

METHODS

Data from three NSCLC cohorts treated with immune checkpoint inhibitors were collected from the Gene Expression Omnibus (GEO) database. The prognostic significance of IRF4 was assessed across these cohorts, and gene set enrichment analysis (GSEA) was performed. IRF4-based nomograms were developed to predict the outcomes of immunotherapy. Correlations among IRF4 expression, immune cell infiltration, and immunotherapy prognosis were evaluated in our cohort.

RESULTS

Elevated IRF4 expression was associated with improved prognosis in patients with NSCLC undergoing immunotherapy, consistent with both GEO dataset and our cohort. IRF4 emerged as an independent predictor for progression-free survival (PFS) and overall survival (OS) in multivariable Cox regression analysis. GSEA analysis highlighted links between IRF4 expression and immune activation pathways such as Chemokine_Signaling_Pathway, Natural_Killer_Cell_Mediated_Cytotoxicity, B_Cell_Receptor_Signaling_Pathway, and T_Cell_Receptor_Signaling_Pathway. In our cohort, immunohistochemistry demonstrated correlations between IRF4 expression and the infiltration of CD8+ T cells, CD20+ B cells, and PD-L1 expression in the tumor microenvironment.

CONCLUSION

High IRF4 expression in baseline tumor tissue could serve as a favorable predictor of NSCLC immunotherapy outcomes, aiding in personalized treatment strategies.

Discover Mutational Differences Between Lung Adenocarcinoma and Lung Squamous Cell Carcinoma and Search for More Effective Biomarkers for Immunotherapy

Purpose

Lung cancer is a severe malignant tumor. This study aims to more comprehensively characterize lung cancer patients and identify combination markers for immunotherapy.

Patients and Methods

We gathered data from 166 lung cancer patients at the Cancer Hospital Affiliated with Xinjiang Medical University. The collected samples underwent NGS sequencing using a panel of 616 genes associated with cancer. Subsequently, data analysis was conducted to identify markers that are more suitable for lung cancer immunotherapy.

Results

In this study, the most common variant genes in LUAD were TP53, EGFR, MST1, KMT2C, RBM10, LRP1B. Meanwhile, the highest mutation frequency genes in LUSC samples were TP53, KMT2D, LRP1B, FAT1, MST1, KMT2C. Mutation frequencies, tumor mutation burden (TMB), PD-L1 expression, and mutant-allele tumor heterogeneity (MATH) values differed between LUAD and LUSC, with LUSC exhibiting higher values than LUAD. Irrespective of LUAD or LUSC, patients with TMB≥10 demonstrated better immunotherapy efficacy compared to patients with TMB<10. Similarly, when PD-L1≥50%, whether in LUAD or LUSC, the immunotherapy effect was superior to that of patients with PD-L1<50%. Combining TMB≥10 and PD-L1≥50% as immunotherapy markers, in both LUAD and LUSC, resulted in a very favorable immunotherapy effect, with the overall response rate (ORR) reaching 100%.

Conclusion

We observed distinct mutation patterns and clinical factors between LUAD and LUSC, and noted that patients with TMB≥10 and PD-L1≥50% exhibited enhanced immunotherapy effects. Combining TMB≥10 and PD-L1≥50% proved to be a more effective predictor of immunotherapy efficacy.

The roles of PD-L1 in the various stages of tumor metastasis

The interaction between tumor programmed death ligand 1 (PD-L1) and T-cell programmed cell death 1 (PD-1) has long been acknowledged as a mechanism for evading immune surveillance. Recent studies, however, have unveiled a more nuanced role of tumor-intrinsic PD-L1 in reprograming tumoral phenotypes. Preclinical models emphasize the synchronized effects of both intracellular and extracellular PD-L1 in promoting metastasis, with intricate interactions with the immune system. This review aims to summarize recent findings to elucidate the spatiotemporal heterogeneity of PD-L1 expression and the pro-metastatic roles of PD-L1 in the entire process of tumor metastasis. For example, PD-L1 regulates the epithelial-to-mesenchymal transition (EMT) process, facilitates the survival of circulating tumor cells, and induces the formation of immunosuppressive environments at pre-metastatic niches and metastatic sites. And the complexed and dynamic regulation process of PD-L1 for tumor metastasis is related to the spatiotemporal heterogeneity of PD-L1 expression and functions from tumor primary sites to various metastatic sites. This review extends the current understandings for the roles of PD-L1 in mediating tumor metastasis and provides new insights into therapeutic decisions in clinical practice.

The role of PD-L1 in patients with non-small cell lung cancer receiving neoadjuvant immune checkpoint inhibitor plus chemotherapy: a meta-analysis

BACKGROUND

The use of immune checkpoint inhibitors (ICIs) as neoadjuvant therapy is a promising novel approach in resectable non-small-cell lung cancer (NSCLC). This study aimed to investigate the prognostic value of PD-L1 in patients with NSCLC receiving neoadjuvant immune checkpoint inhibitor plus chemotherapy (CT).

MATERIALS AND METHODS

Several databases (PubMed, Embase, and cochrane central register of controlled trials [CENTRAL]) were systematically searched. Randomized controlled trials (RCTs) investigating pathological and survival outcomes with neoadjuvant ICI + CT versus CT alone in NSCLC were analyzed.

RESULTS

Overall, eight RCTs (n = 3,404) were included. The analyses showed neoadjuvant ICI + CT significantly improved complete pathological response (pCR) and event-free survival (EFS) in either tumor PD-L1 < 1%, ≥ 1%, 1-49%, or ≥ 50% population (both p < 0.0001) compared with neoadjuvant CT alone. The overall survival (OS) data are not yet mature among all included RCTs, and only three RCTs presented OS data by PD-L1 status of patients. The pooled OS favored neoadjuvant ICI + CT in the PD-L1 ≥ 1% population (hazard ratio [HR], 0.45; 95% CI, 0.31-0.65; p < 0.0001), but not in the PD-L1 < 1% population (HR, 0.89; 95% CI, 0.66-1.19; p = 0.43).

CONCLUSIONS

Compared with neoadjuvant CT alone, neoadjuvant ICI + CT significantly enhanced pCR and EFS for patients with resectable NSCLC regardless of the expression of PD-L1. It seems that only patients with PD-L1 positive tumors may achieve a better OS, but it's currently inconclusive due to immature data, so future research with long-term follow-up is still needed.

Predicting survival benefits of immune checkpoint inhibitor therapy in lung cancer patients: a machine learning approach using real-world data

BACKGROUND

Due to the heterogeneity in the effectiveness of immunotherapy for lung cancer, identifying predictors is crucial.

AIM

This study aimed to develop a machine learning model to identify predictors of overall survival in lung cancer patients treated with immune checkpoint inhibitors (ICIs).

METHOD

A retrospective analysis was performed on data from 1314 lung cancer patients at the Chongqing University Cancer Hospital from September 2018 to September 2022. We used the random survival forest (RSF) model to identify survival-influencing factors, using backward elimination for variable selection. A Cox proportional hazards (CPH) model was constructed using the most significant predictors. We assessed model performance and generalizability using time-dependent receiver operating characteristics (ROC) and predictive error curves.

RESULTS

The RSF model demonstrated better predictive accuracy than the CPH (IBS 0.17 vs. 0.17; C-index 0.91 vs. 0.68), with better discrimination and prediction performance. The influential variables identified included D-dimer, Karnofsky performance status, albumin, surgery, TNM stage, platelet count, and age. The RSF model, which incorporated these variables, achieved area under the curve (AUC) scores of 0.95, 0.94, and 0.98 for 1-, 3-, and 5-year survival predictions, respectively, in the training set. The validation set showed AUCs of 0.94, 0.90, and 0.95, respectively, exceeding the performance of the CPH model.

CONCLUSION

The study successfully developed a machine learning model that accurately predicted the survival benefits of ICI therapy in lung cancer patients, supporting clinical decision-making in lung cancer treatment.

Pan-cancer evaluation of tumor-infiltrating lymphocytes and programmed cell death protein ligand-1 in metastatic biopsies and matched primary tumors

Tumor immunological characterization includes evaluation of tumor-infiltrating lymphocytes (TILs) and programmed cell death protein ligand-1 (PD-L1) expression. This study investigated TIL distribution, its prognostic value, and PD-L1 expression in metastatic and matched primary tumors (PTs). Specimens from 550 pan-cancer patients of the SHIVA01 trial (NCT01771458) with available metastatic biopsy and 111 matched PTs were evaluated for TILs and PD-L1. Combined positive score (CPS), tumor proportion score (TPS), and immune cell (IC) score were determined. TILs and PD-L1 were assessed according to PT organ of origin, histological subtype, and metastatic biopsy site. We found that TIL distribution in metastases did not vary according to PT organ of origin, histological subtype, or metastatic biopsy site, with a median of 10% (range: 0-70). TILs were decreased in metastases compared to PT (20% [5-60] versus 10% [0-40], p < 0.0001). CPS varied according to histological subtype (p = 0.02) and biopsy site (p < 0.02). TPS varied according to PT organ of origin (p = 0.003), histological subtype (p = 0.0004), and metastatic biopsy site (p = 0.00004). TPS was higher in metastases than in PT (p < 0.0001). TILs in metastases did not correlate with overall survival. In conclusion, metastases harbored fewer TILs than matched PT, regardless of PT organ of origin, histological subtype, and metastatic biopsy site. PD-L1 expression increased with disease progression. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Temporal Effect on PD-L1 Detection and Novel Insights Into Its Clinical Implications in Non-Small Cell Lung Cancer

OBJECTIVES

Several studies rely on archived tissue blocks to assess the PD-L1 scores; however, a detailed analysis of potential variations of scores between fresh and archived tissue blocks still lacks. In addition, the prognostic implications of PD-L1 in lung cancers have not yet been completely understood. Here, we aimed to investigate the temporal variation in PD-L1 scores from clinical samples and the clinical implications of PD-L1 in non-small cell lung cancer (NSCLC).

METHODS

NSCLC cases from January 2005 to June 2023 were considered for this study, and PD-L1 scores in archived and fresh tissue blocks were analyzed. Association of PD-L1 with various driver mutations was explored, and implications of PD-L1 in progression-free survival (PFS) and overall survival (OS) were analyzed.

RESULTS

Our study revealed a significant disparity in PD-L1 scores between archived and fresh tissue blocks, and a temporal variation in scores within 6 months of tissue acquisition. Advanced-stage primary tumors, metastatic lymph nodes, and visceral pleural invasion revealed higher PD-L1 expression as presented by tumor proportion score (TPS). Notably, in fully resected stage I/II NSCLC cases, OS was better in the high PD-L1 (≥ 50% TPS) cohort with driver mutations compared to cases without driver mutations (hazard ratio-0.5129, 95% confidence interval 0.2058-1.084, p = 0.0779). In contrast, high PD-L1 was associated with worse OS compared to no PD-L1 (< 1% TPS) (hazard ratio-2.431, 95% confidence interval 1.144-6.656, p = 0.0242) in the cohort without driver mutations. Furthermore, the presence of a KRAS mutation favored the outcome of anti-PD-L1/PD1 immunotherapy in advanced NSCLC.

CONCLUSION

PD-L1 detection from tissue blocks was found to vary temporally, urging for a prioritized consideration for patients with marginal scores when archived blocks are employed for its detection. Prognostic roles of PD-L1 were associated with driver mutations, and KRAS mutations favored the outcome of anti-PD-L1/PD1 therapy in advanced NSCLC.

[18F]AlF-NOTA-PCP2: a novel PET/CT tracer for enhanced PD-L1 heterogeneity imaging and comparative analysis with [18F]AlF-NOTA-WL12 in glioblastoma xenografts

PURPOSE

The unsatisfactory efficacy of PD-L1 antibodies in glioblastoma (GBM) is largely due to the temporal and spatial heterogeneity of PD-L1 expression. Molecular imaging can enhance understanding of the tumor immune microenvironment and guide immunotherapy. However, highly sensitive imaging agents capable of effectively visualizing PD-L1 heterogeneity are limited. This study introduces a novel PET tracer, offering improved imaging of PD-L1 heterogeneity in GBM xenografts, with a comparative analysis to [18F]AlF-NOTA-WL12.

METHODS

[18F]AlF-NOTA-PCP2 was synthesized with high purity and its affinity for PD-L1 was characterized using surface plasmon resonance (SPR) and cell binding assays. Its specificity for PD-L1 was evaluated both in vitro using various cell lines and in vivo with GBM xenograft models in NOD/SCID mice. PET/CT imaging was conducted to evaluate the tracer's biodistribution, pharmacokinetics, and ability to quantify tumoral spatial heterogeneity of PD-L1 expression. A focused comparative analysis between [18F]AlF-NOTA-PCP2 and [18F]AlF-NOTA-WL12 was conducted, examining binding affinity, biodistribution, pharmacokinetics, and imaging effectiveness in GBM xenografts. Additionally, human radiation dosimetry estimates compared the safety profiles of both tracers.

RESULTS

[18F]AlF-NOTA-PCP2 demonstrated high radiochemical purity (> 95%) and a strong affinity for PD-L1, comparable to [18F]AlF-NOTA-WL12. In vitro and in vivo studies confirmed its specificity for PD-L1, with increased uptake in PD-L1 expressing cells and tumors. Toxicological profiles indicated no significant abnormalities in serum biochemical indicators or major organ tissues. MicroPET/CT imaging showed [18F]AlF-NOTA-PCP2's effectiveness in visualizing PD-L1 expression levels and spatial heterogeneity in GBM xenografts. Comparative studies revealed [18F]AlF-NOTA-PCP2's improved pharmacokinetic properties, including higher tumor-to-blood ratios and lower nonspecific liver uptake, as well as reduced radiation exposure compared to [18F]AlF-NOTA-WL12.

CONCLUSION

[18F]AlF-NOTA-PCP2 distinguishes itself as an exceptionally sensitive PET/CT tracer, adept at non-invasively and accurately quantifying PD-L1 expression and its spatial heterogeneity in tumors, especially in GBM. Its favorable pharmacokinetic properties, safety profile, and high affinity for PD-L1 highlight its potential for enhancing the precision of cancer immunotherapy and guiding individualized treatment strategies. While promising, its clinical translation, especially in brain imaging, necessitates further validation in clinical trials.

Circulating tumor DNA (ctDNA) application in investigation of cancer: Bench to bedside

Now, genomics forms the core of the precision medicine concept. Comprehensive investigations of tumor genomes have made it possible to characterize tumors at the molecular level and, specifically, to identify the fundamental processes that cause condition. A variety of kinds of tumors have seen better outcomes for patients as a result of the development of novel medicines to tackle these genetic-driving processes. Since therapy may exert selective pressure on cancers, non-invasive methods such as liquid biopsies can provide the opportunity for rich reservoirs of crucial and real-time genetic data. Liquid biopsies depend on the identification of circulating cells from tumors, circulating tumor DNA (ctDNA), RNA, proteins, lipids, and metabolites found in patient biofluids, as well as cell-free DNA (cfDNA), which exists in those with cancer. Although it is theoretically possible to examine biological fluids other than plasma, such as pleural fluid, urine, saliva, stool, cerebrospinal fluid, and ascites, we will limit our discussion to blood and solely cfDNA here for the sake of conciseness. Yet, the pace of wider clinical acceptance has been gradual, partly due to the increased difficulty of choosing the best analysis for the given clinical issue, interpreting the findings, and delaying proof of value from clinical trials. Our goal in this review is to discuss the current clinical value of ctDNA in cancers and how clinical oncology systems might incorporate procedures for ctDNA testing.

Head-to-head comparison of composite and individual biomarkers to predict clinical benefit to PD-1 blockade in non-small cell lung cancer

BACKGROUND

The efficacy of PD-1 blocking agents in advanced NSCLC has shown prolonged effectiveness, but only in a minority of patients. Multiple biomarkers have been explored to predict treatment benefit, yet their combined performance remains inadequately examined. In this study, we assessed the combined predictive performance of multiple biomarkers in NSCLC patients treated with nivolumab.

METHODS

Pretreatment samples from 135 patients receiving nivolumab were used to evaluate the predictive performance of CD8 tumor-infiltrating lymphocytes (TILs), intratumoral (IT) localization of CD8 TILs, PD-1 high expressing TILs (PD1T TILs), CD3 TILs, CD20 B-cells, tertiary lymphoid structures (TLS), PD-L1 tumor proportion score (TPS) and the Tumor Inflammation score (TIS). Patients were randomly assigned to a training (n = 55) and validation cohort (n = 80). The primary outcome measure was Disease Control at 6 months (DC 6m) and the secondary outcome measure was DC at 12 months (DC 12m).

RESULTS

In the validation cohort, the two best performing composite biomarkers (i.e. CD8+IT-CD8 and CD3+IT-CD8) demonstrated similar or lower sensitivity (64% and 83%) and NPV (76% and 85%) compared to individual biomarkers PD-1T TILs and TIS (sensitivity: 72% and 83%, NPV: 86% and 84%) for DC 6m, respectively. Additionally, at 12 months, both selected composite biomarkers (CD8+IT-CD8 and CD8+TIS) demonstrated inferior predictive performance compared to PD-1T TILs and TIS alone. PD-1T TILs and TIS showed high sensitivity (86% and 100%) and NPV (95% and 100%) for DC 12m. PD-1T TILs could more accurately discriminate patients with no long-term benefit, as specificity was substantially higher compared to TIS (74% versus 39%).

CONCLUSION

Composite biomarkers did not show improved predictive performance compared to PD-1T TILs and TIS alone for both the 6- and 12-month endpoints. PD-1T TILs and TIS identified patients with DC 12m with high sensitivity. Patients with no long-term benefit to PD-1 blockade were most accurately identified by PD-1T TILs.

Identification and validation of GIMAP family genes as immune-related prognostic biomarkers in lung adenocarcinoma

Background

The GIMAP family genes play a key role in immune function. Increasing evidence suggests that GIMAP genes were implicated in the tumorigenesis of lung adenocarcinoma (LUAD). This study aimed to investigate the clinical significance of GIMAP family genes in LUAD.

Methods

In this study, we explored the expression, mutation, prognostic value of GIMAP family genes and the correlation with immune microenvironment in LUAD. We further investigated the relationship between GIMAP family genes expression and immunotherapy response in GEO LUAD and melanoma cohorts.

Results

Among the GIMAP family genes, the expression levels of GIMAP1, GIMAP2, GIMAP4, GIMAP5, GIMAP6, GIMAP7, and GIMAP8 were significantly lower in LUAD tumor tissues than normal tissues. Most GIMAP genes were closely related to age, tumor grade and T stage, but not significantly related to sex, N stage and M stage. In the overall population, patients with high expression of GIMAP family genes had a significant longer overall survival (OS). GO and KEGG enrichment analysis showed that GIMAP family genes were highly enriched in immune-related biological process. The expression of GIMAP family genes was positively correlated with immune cell infiltration and immune checkpoint molecules. Furthermore, high expression of GIMAP family genes were correlated with therapeutic response to immunotherapy in LUAD and melanoma patients.

Conclusion

In this study, we identified that GIMAP family genes were significantly associated with immune cell infiltration and immune checkpoint molecules. They potentially play a critical role in anti-tumor immunity and serve as immunotherapy biomarkers.

Mutational variant allele frequency profile as a biomarker of response to immune checkpoint blockade in non-small cell lung Cancer

INTRODUCTION

Identifying new biomarkers for predicting immune checkpoint inhibitors (ICIs) response in non-small cell lung cancer (NSCLC) is crucial. We aimed to assess the variant allele frequency (VAF)-related profile as a novel biomarker for NSCLC personalized therapy.

METHODS

We utilized genomic data of 915 NSCLC patients via cBioPortal and a local cohort of 23 patients for model construction and mutational analysis. Genomic, transcriptomic data from 952 TCGA NSCLC patients, and immunofluorescence (IF) assessment with the local cohort supported mechanism analysis.

RESULTS

Utilizing the random forest algorithm, a 15-gene VAF-related model was established, differentiating patients with durable clinical benefit (DCB) from no durable benefit (NDB). The model demonstrated robust performance, with ROC-AUC values of 0.905, 0.737, and 0.711 across training (n = 313), internal validation (n = 133), and external validation (n = 157) cohorts. Stratification by the model into high- and low-score groups correlated significantly with both progression-free survival (PFS) (training: P < 0.0001, internal validation: P < 0.0001, external validation: P = 0.0066) and overall survival (OS) (n = 341) (P < 0.0001). Notably, the stratification system was independent of PD-L1 (P < 0.0001) and TMB (P < 0.0001). High-score patients exhibited an increased DCB ratio and longer PFS across both PD-L1 and TMB subgroups. Additionally, the high-score group appeared influenced by tobacco exposure, with activated DNA damage response pathways. Whereas, immune/inflammation-related pathways were enriched in the low-score group. Tumor immune microenvironment analyses revealed higher proportions of exhausted/effector memory CD8 + T cells in the high-score group.

CONCLUSIONS

The mutational VAF profile is a promising biomarker for ICI therapy in NSCLC, with enhanced therapeutic stratification and management as a supplement to PD-L1 or TMB.

Heterogeneity in PD-L1 expression between primary and metastatic lymph nodes: a predictor of EGFR-TKI therapy response in non-small cell lung cancer

BACKGROUND

There is inconclusive evidence to suggest that the expression of programmed cell death ligand 1 (PD-L1) is a putative predictor of response to EGFR-TKI therapy in advanced EGFR-mutant non-small cell lung cancer (NSCLC). We evaluated the heterogeneity in PD-L1 expression in the primary lung site and metastatic lymph nodes to analyze the association between PD-L1 expression and response for patients treated with EGFR-TKI.

METHODS

This study reviewed 184 advanced NSCLC patients with EGFR mutations who received first-generation EGFR-TKI as first-line treatment from 2020 to 2021 at Shanghai Chest Hospital. The patients were divided into the primary lung site group (n = 100) and the metastatic lymph nodes group (n = 84) according to the biopsy site. The patients in each group were divided into TPS < 1%, TPS 1-49%, and TPS ≥ 50% groups according to PD-L1 expression.

RESULTS

The median PFS was 7 (95% CI: 5.7-8.3) months, and the median OS was 26 (95% CI: 23.5-28.5) months for all patients. No correlation existed between PFS or OS and PD-L1 expression. The median PFS in the primary lung site group was 11 months (95% CI: 9.6-12.4) in the TPS < 1% group, 8 months (95% CI: 6.6-9.4) in TPS 1-49% group, and 4 months (95% CI: 3.2-4.8) in TPS ≥ 50% group, with statistically significant differences (p = 0.000). The median OS of the TPS < 1% group and TPS ≥ 50% group showed a statistically significant difference (p = 0.008) in the primary lung site group. In contrast, PD-L1 expression in the lymph nodes of EGFR-mutant patients was unrelated to PFS or OS after EGFR-TKI therapy.

CONCLUSION

PD-L1 expression from the primary lung site might predict clinical benefit from EGFR-TKI, whereas PD-L1 from metastatic lymph nodes did not.

TRIAL REGISTRATION

This retrospective study was approved by the Ethics Committee of Shanghai Chest Hospital (ID: IS23060) and performed following the Helsinki Declaration of 1964 (revised 2008).

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.

Immunomodulatory Precision: A Narrative Review Exploring the Critical Role of Immune Checkpoint Inhibitors in Cancer Treatment

An immune checkpoint is a signaling pathway that regulates the recognition of antigens by T-cell receptors (TCRs) during an immune response. These checkpoints play a pivotal role in suppressing excessive immune responses and maintaining immune homeostasis against viral or microbial infections. There are several FDA-approved immune checkpoint inhibitors (ICIs), including ipilimumab, pembrolizumab, and avelumab. These ICIs target cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), programmed cell death protein 1 (PD-1), and programmed death ligand 1 (PD-L1). Furthermore, ongoing efforts are focused on developing new ICIs with emerging potential. In comparison to conventional treatments, ICIs offer the advantages of reduced side effects and durable responses. There is growing interest in the potential of combining different ICIs with chemotherapy, radiation therapy, or targeted therapies. This article comprehensively reviews the classification, mechanism of action, application, and combination strategies of ICIs in various cancers and discusses their current limitations. Our objective is to contribute to the future development of more effective anticancer drugs targeting immune checkpoints.

The efficacy of immune checkpoint inhibitors on low PD-L1 cervical cancer: A meta-analysis

Background and Aims

The effectiveness of immune checkpoint inhibitors (ICIs) in low programmed death ligand 1 (PD-L1) expression in cervical cancer (CC) patients remains unknown. We aimed to evaluate the efficacy of ICIs in low PD-L1 expression CC patients.

Methods

The study is an individual patient data (IPD)-based meta-analysis. IPD were compiled through KMSubtraction and IPDfromKM methodologies from high-quality randomized clinical trials and single-arm studies which reported overall survival (OS) or progression-free survival (PFS) stratified by PD-L1 expression. Kaplan-Meier curves and Cox regression analysis were employed to evaluate the survival benefits of ICIs.

Results

A total of eight studies and 1110 cases were included in the analysis. Within the low PD-L1 expression subgroup, ICI combination therapy, but not ICI monotherapy, demonstrated significant OS benefits over non-ICI treatment (hazard ratio [HR] = 0.61, 95% confidence interval [CI]: 0.36-1.04, p = 0.06). Concerning PFS, ICI monotherapy was associated with a negative effect compared to non-ICI treatment (HR = 4.59, 95% CI: 2.32-9.07, p < 0.001). Notably, both OS and PFS outcomes were unfavorable for ICI monotherapy compared to both non-ICI and ICI combination therapy in the combined positive score <1 subgroup (OS: HR = 2.60, 95% CI: 1.31-5.16, p = 0.008; PFS: HR = 7.59, 95% CI: 3.53-16.31, p < 0.001).

Conclusion

In patients with CC and low PD-L1 expression, ICI monotherapy may not be considered as the optimal treatment strategy when compared to non-ICI treatment or ICI combination therapy.

Registration

CRD42023395103.

Multi-omics Analysis Reveals Immune Features Associated with Immunotherapy Benefit in Patients with Squamous Cell Lung Cancer from Phase III Lung-MAP S1400I Trial

PURPOSE

Identifying molecular and immune features to guide immune checkpoint inhibitor (ICI)-based regimens remains an unmet clinical need.

EXPERIMENTAL DESIGN

Tissue and longitudinal blood specimens from phase III trial S1400I in patients with metastatic squamous non-small cell carcinoma (SqNSCLC) treated with nivolumab monotherapy (nivo) or nivolumab plus ipilimumab (nivo+ipi) were subjected to multi-omics analyses including multiplex immunofluorescence (mIF), nCounter PanCancer Immune Profiling Panel, whole-exome sequencing, and Olink.

RESULTS

Higher immune scores from immune gene expression profiling or immune cell infiltration by mIF were associated with response to ICIs and improved survival, except regulatory T cells, which were associated with worse overall survival (OS) for patients receiving nivo+ipi. Immune cell density and closer proximity of CD8+GZB+ T cells to malignant cells were associated with superior progression-free survival and OS. The cold immune landscape of NSCLC was associated with a higher level of chromosomal copy-number variation (CNV) burden. Patients with LRP1B-mutant tumors had a shorter survival than patients with LRP1B-wild-type tumors. Olink assays revealed soluble proteins such as LAMP3 increased in responders while IL6 and CXCL13 increased in nonresponders. Upregulation of serum CXCL13, MMP12, CSF-1, and IL8 were associated with worse survival before radiologic progression.

CONCLUSIONS

The frequency, distribution, and clustering of immune cells relative to malignant ones can impact ICI efficacy in patients with SqNSCLC. High CNV burden may contribute to the cold immune microenvironment. Soluble inflammation/immune-related proteins in the blood have the potential to monitor therapeutic benefit from ICI treatment in patients with SqNSCLC.

Sotorasib in KRAS G12C-mutated non-small cell lung cancer: A multicenter real-world experience from the compassionate use program in Germany

BACKGROUND

Sotorasib is a first-in-class KRAS p.G12C-inhibitor that has entered clinical trials in pretreated patients with non-small cell lung cancer (NSCLC) in 2018. First response rates were promising in the CodeBreaK trials. It remains unclear whether response to sotorasib and outcomes differ in a real-world setting when including patients underrepresented in clinical trials.

METHODS

Patients with KRAS p.G12C-mutated advanced or metastatic NSCLC received sotorasib within the German multicenter sotorasib compassionate use program between 2020 to 2022. Data on efficacy, tolerability, and survival were analyzed in the full cohort and in subgroups of special interest such as co-occurring mutations and across PD-L1 expression levels.

RESULTS

We analyzed 163 patients who received sotorasib after a median of two treatment lines (range, 0 to 7). Every fourth patient had a poor performance status and 38% had brain metastases (BM). The objective response rate was 38.7%. The median overall survival was 9.8 months (95% CI, 6.5 to not reached). Median real-world (rw) progression-free survival was 4.8 months (9% CI, 3.9 to 5.9). Dose reductions and permanent discontinuation were necessary in 35 (21.5%) and 7 (4.3%) patients, respectively. Efficacy seems to be influenced by PD-L1 expression and a co-occurring KEAP1 mutation. KEAP1 was associated with an inferior survival. Other factors such as BM, STK11, and TP53 mutations had no impact on response and survival.

CONCLUSION

First results from a real-world population confirm promising efficacy of sotorasib for the treatment of advanced KRAS p.G12C-mutated NSCLC. Patients with co-occurring KEAP1 mutations seem to derive less benefit.

Non-tumor-related prognostic factors for immunotherapy-chemotherapy or immunotherapy alone as first-line in advanced non-small cell lung cancer (NSCLC)

Besides programmed death ligand 1 (PD-L1) expression, rapid, cost-effective and validated scores or models are critical for the prognosis and prediction of patients received immune checkpoint inhibitors (ICIs). In this retrospective study, 182 patients with NSCLC receiving ICIs from 2015 to 2022 were divided 1:1 into a training cohort and a validation cohort. We identified a score established by three factors and analyzed the prognostic implications by Kaplan-Meier approach (Log rank test) and time-dependent receiver operating characteristic (ROC) analyses. A non-tumor-related score (NTRS) was established that could be used as a prognostic factor (HR 2.260, 95% CI 1.559-3.276, P < 0.001 in training cohort; HR 2.114, 95% CI 1.493-2.994, P < 0.001 in validation cohort) and had a high time-dependent ROC for overall survival (OS) (AUC 0.670-0.782 in training cohort; AUC 0.682-0.841 in validation cohort). PD-L1 (1-49%) and NTRS (score = 0, 1, 2, 3) combination significantly improved the assessment of patients' OS and progress-free survival (PFS), which was statistically different in training cohorts (P < 0.001 for OS, 0.012 for PFS) and validation cohorts (P = 0.01 for OS, < 0.001 for PFS). The NTRS provided a better assessment of durable clinical benefit (DCB) compared to PD-L1 expression (P = 0.009 vs. 0.232 in training cohort; P = 0.004 vs. 0.434 in validation cohort). NTRS may help improve prognosis stratification of patients receiving ICIs in first-line NSCLC and may be combined with tumor-related parameters.

Genomic discordances and heterogeneous mutational burden, PD-L1 expression and immune infiltrates of non-small cell lung cancer metastasis

AIMS

To investigate the genomic discordances and heterogeneous mutational burden, PD-L1 expression and immune cell (IC) infiltrates of non-small cell lung cancer (NSCLC) metastasis.

METHODS

Surgical samples from 41 cases of NSCLC with metastatic tumours (MTs) and paired primary tumours (PTs) were collected. PD-L1 expression and ICs were quantified using image-based immunohistochemistry profiling. Whole exome sequencing was employed to explore discrepancies in genomic characteristics, tumour mutational burden (TMB) and tumour neoantigen burden (TNB) in 28 cases.

RESULTS

Non-synonymous mutations in MTs were slightly more than in PTs, with only 42.34% of mutations shared between paired PTs and MTs. The heterogeneity of TMB showed no significant difference (p=0.785) between MTs and PTs, while TNB significantly increased in MTs (p=0.013). MTs generally exhibited a higher density of PD-L1+ cells and a higher tumour proportion score with a lower density of IC infiltrates. Subgroup analysis considering clinicopathological factors revealed that the heterogeneity of immune biomarkers was closely associated with the histology of lung adenocarcinoma, metastatic sites of extrapulmonary, time intervals and treatment history. Prognosis analysis indicated that a high density of CD8+ T cells was a low-risk factor, whereas a high density of PD-L1+ cells in MTs was a high-risk factor for cancer-related death in metastatic NSCLC.

CONCLUSIONS

The mutational burden, PD-L1 expression and IC infiltrates undergo changes during NSCLC metastasis, which may impact the immunotherapeutic benefits in patients with NSCLC with metastatic progression and should be monitored according to clinical scenarios.

Progress of immune checkpoint inhibitors therapy for non-small cell lung cancer with liver metastases

Nearly one-fifth of patients with non-small cell Lung Cancer (NSCLC) will develop liver metastases (LMs), and the overall treatment strategy of LMs will directly affect the survival of patients. However, some retrospective studies have found that patients receiving chemotherapy or targeted therapy have a poorer prognosis once LMs develop. In recent years, multiple randomised controlled trials (RCTS) have shown significant improvements in outcomes for patients with advanced lung cancer following the introduction of immune checkpoint inhibitors (ICIs) compared to conventional chemotherapy. ICIs is safe and effective in patients with LMs, although patients with LMs are mostly underrepresented in randomised clinical trials. However, NSCLC patients with LMs have a significantly worse prognosis than those without LMs when treated with ICIs, and the mechanism by which LMs induce systemic anti-tumour immunity reduction is unknown, so the management of LMs in patients with NSCLC is a clinical challenge that requires more optimised therapies to achieve effective disease control. In this review, we summarised the mechanism of ICIs in the treatment of LMs, the clinical research and treatment progress of ICIs and their combination with other therapies in patients with LMs from NSCLC.

Comparison of primary and metastatic site-related PD-L1 expression in predicting ORR in patients with advanced NSCLC who received ICB-based therapy

BACKGROUND

Whether the value of PD-L1 expression from metastatic sites to predict the efficacy of immune checkpoint blockade (ICB)-based treatment is equivalent to that from a primary tumor is uncertain. This study aimed to compare the utility of PD-L1 TPS from a primary lung tumor and metastatic sites to predict the overall response rate (ORR) of first-line ICB-based treatment.

METHODS

This study included 249 patients with advanced non-small cell lung cancer (NSCLC) who received first-line ICB-based treatment. All subjects underwent PD-L1 testing prior to ICB-based treatment and were divided into two cohorts corresponding to the different biopsy sites: lung primary site-sampled cohort (PT cohort, n = 167) and metastatic site-sampled cohort (MT cohort, n = 82).

RESULTS

There was no statistical significance in PD-L1 TPS distribution between the two cohorts (p = 0.742). PD-L1 TPS ≥50% was also related to high ORR compared with PD-L1 < 50% in the PT cohort (34.3% vs. 14.1%, p = 0.004). In contrast, ICB-based therapy could bring comparable ORR (35.1% vs. 33.3%, p = 0.871) in the MT cohort regardless of PD-L1 TPS status (≥50%, or <50%). As supported, when the cutoff value of TPS was selected as 50%, it was suggested that PT-related PD-L1 was the independent predictor of ORR (OR 2.870, 95% CI: 1.231-6.694, p = 0.015) rather than MT-related PD-L1 (OR 0.689, 95% CI: 0.236-2.013, p = 0.495). Furthermore, ROC proved that PT-related PD-L1 expression manifested a better AUC of 0.621 (p = 0.026) than that of MT-related PD-L1 (AUC = 0.565, p = 0.362).

CONCLUSION

Compared with PT-related PD-L1 expression, MT-related PD-L1 expression showed limited value in predicting ORR in patients with advanced NSCLC receiving ICB-based therapy. It was concluded that even patients with low MT-related PD-L1 expression could benefit from ICB-based therapy.

Genetic Intratumor Heterogeneity Remodels the Immune Microenvironment and Induces Immune Evasion in Brain Metastasis of Lung Cancer

INTRODUCTION

Brain metastasis, with the highest incidence in patients with lung cancer, significantly worsens prognosis and poses challenges to clinical management. To date, how brain metastasis evades immune elimination remains unknown.

METHODS

Whole-exome sequencing and RNA sequencing were performed on 30 matched brain metastasis, primary lung adenocarcinoma, and normal tissues. Data from The Cancer Genome Atlas primary lung adenocarcinoma cohort, including multiplex immunofluorescence, were used to support the findings of bioinformatics analysis.

RESULTS

Our study highlights the key role of intratumor heterogeneity of genomic alterations in the metastasis process, mainly caused by homologous recombination deficiency or other somatic copy number alteration-associated mutation mechanisms, leading to increased genomic instability and genomic complexity. We further proposed a selection model of brain metastatic evolution in which intratumor heterogeneity drives immune remodeling, leading to immune escape through different mechanisms under local immune pressure.

CONCLUSIONS

Our findings provide novel insights into the metastatic process and immune escape mechanisms of brain metastasis and pave the way for precise immunotherapeutic strategies for patients with lung cancer with brain metastasis.

Pembrolizumab-combination therapy for NSCLC- effectiveness and predictive factors in real-world practice

Introduction

Pembrolizumab combined with chemotherapy has become the standard of care for patients with non-small-cell lung cancer (NSCLC) and the expression of programmed death ligand 1 (PD-L1) in <50% of tumour cells (TC).

Methods

We evaluated the efficacy of the treatment in real-world practice, paying attention to the predictive factors, with a special focus on low level of PD-L1 expression. This study is a multicenter retrospective analysis of patients with stage IV NSCLC.

Results

A group of 339 consecutive patients was analysed, among them 51% patients with low PD-L1 expression. In the overall population, the ORR was 40.6%, median PFS and OS were 13 months (95% CI 11.4-15) and 16.8 months (95% CI 13.3-20.3), respectively. In multivariate analysis for the entire study population, performance status - ECOG 1 vs. 0 (HR 2.2, 95%CI 1.1-4.6; p=0.02), neutrophil to lymphocyte ratio (NLR)>3 (HR 2.3, 95%CI 1.3-4.2; p=0.04), presence of liver (HR 2.0, 95%CI 1-3.7; p=0. 03) and bone metastases (HR 1.3, 95%CI 1-3; p=0.04), weight loss (HR 1.8, 95%CI 1.1-2.8; p=0.01) and sum of measurable lesions diameters >110 mm (HR 1.7, 95%CI 1-2.9, p=0.049) had a negative impact on OS.

Conclusions

In the real world, patients can clinically benefit from immunochemotherapy, regardless of the expression of PD-L1 and the histological type. Other clinicopathological factors such as performance status, extent, and location of secondary lesions have prognostic significance.

Reconstruction of unreported subgroup survival data with PD-L1-low expression in advanced/metastatic triple-negative breast cancer using innovative KMSubtraction workflow

BACKGROUND

Among patients with advanced/metastatic triple-negative breast cancer (TNBC) with high/positive programmed death-ligand 1 (PD-L1) expression, a superior survival outcome has been demonstrated with immune checkpoint inhibitors (ICIs). However, it remains unclear whether ICIs are beneficial for patients with low PD-L1 levels. Here, we derived survival data for subgroups with low PD-L1-expressing and conducted a pooled analysis.

METHODS

After a systematic search of Embase, PubMed, MEDLINE, and CENTRAL from inception until May 18, 2023, randomized controlled trials (RCTs) reporting progression-free survival (PFS), overall survival (OS), or duration of response (DOR) for metastatic TNBC treated with ICI-based regimens were included. Kaplan-Meier curves were extracted for the intention-to-treat population and high PD-L1 subgroups. KMSubtraction was used when survival curves were not provided for subgroups with low PD-L1 expression. A pooled analysis of survival data was then conducted.

RESULTS

A total of 3022 patients were included in four RCTs: Impassion130, Impassion131, KEYNOTE-119, and KEYNOTE-355. Unreported low PD-L1-expressing subgroups were identified, including PD-L1 immune cell (IC)<1%, combined positive score (CPS)<1, and 1≤CPS<10. Compared with chemotherapy, ICI-chemotherapy combinations did not significantly differ in OS, PFS, or DOR in the Impassion PD-L1<1%, KEYNOTE-355 PD-L1 CPS<1, and KEYNOTE-355 1≤CPS<10 subgroups. In the KEYNOTE-119 CPS<1 subgroup, the risk of tumor progression was increased with pembrolizumab (HR, 2.23; 95% CI, 1.62 to 3.08; p<0.001), as well as in the 1≤CPS<10 subgroup (HR, 1.64; 95% CI, 1.22 to 2.20; p<0.001). A pooled analysis using a scoring system found no significant difference in OS and PFS among the subgroups with an IC of <1% between immunochemotherapy and chemotherapy. OS (HR, 1.07; 95% CI, 0.91 to 1.26), PFS (HR, 0.96; 95% CI, 0.84 to 1.10), and DOR were also not significantly different in pooled analysis of first-line trials for those with low PD-L1 expression.

CONCLUSION

ICI-based regimens are not associated with a survival benefit versus chemotherapy in subgroups of advanced/metastatic TNBC that express low PD-L1 levels.

Caloric restriction and metformin selectively improved LKB1-mutated NSCLC tumor response to chemo- and chemo-immunotherapy

BACKGROUND

About 10% of NSCLCs are mutated in KRAS and impaired in STK11/LKB1, a genetic background associated with poor prognosis, caused by an increase in metastatic burden and resistance to standard therapy. LKB1 is a protein involved in a number of biological processes and is particularly important for its role in the regulation of cell metabolism. LKB1 alterations lead to protein loss that causes mitochondria and metabolic dysfunction that makes cells unable to respond to metabolic stress. Different studies have shown how it is possible to interfere with cancer metabolism using metformin and caloric restriction (CR) and both modify the tumor microenvironment (TME), stimulating the switch from "cold" to "hot". Given the poor therapeutic response of KRASmut/LKB1mut patients, and the role of LKB1 in cell metabolism, we examined whether the addition of metformin and CR enhanced the response to chemo or chemo-immunotherapy in LKB1 impaired tumors.

METHODS

Mouse cell lines were derived from lung nodules of transgenic mice carrying KRASG12D with either functional LKB1 (KRASG12D/LKB1wt) or mutated LKB1 (KRASG12D/LKB1mut). Once stabilized in vitro, these cell lines were inoculated subcutaneously and intramuscularly into immunocompetent mice. Additionally, a patient-derived xenograft (PDX) model was established by directly implanting tumor fragments from patient into immunocompromised mice. The mice bearing these tumor models were subjected to treatment with chemotherapy or chemo-immunotherapy, both as standalone regimens and in combination with metformin and CR.

RESULTS

Our preclinical results indicate that in NSCLC KRASmut/LKB1mut tumors, metformin and CR do enhance the response to chemo and chemo-immunotherapy, inducing a metabolic stress condition that these tumors are not able to overcome. Analysis of immune infiltrating cells did not bring to light any strong correlation between the TME immune-modulation and the tumor response to metformin and CR.

CONCLUSION

Our in vitro and in vivo preliminary studies confirm our hypothesis that the addition of metformin and CR is able to improve the antitumor activity of chemo and chemoimmunotherapy in LKB1 impaired tumors, exploiting their inability to overcome metabolic stress.

Effect of storage time of paraffin sections on the expression of PD-L1 (SP142) in invasive breast cancer

BACKGROUND

PD-L1 staining using long-stored paraffin sections may not be consistent with the true PD-L1 expression of patients. Therefore, it is necessary to explore the expression of PD-L1(SP142) in paraffin sections of invasive breast cancer with different storage times and the optimal storage temperature for unstained paraffin sections.

METHODS

The study included 71 cases of PD-L1(SP142) positive breast cancer. The unstained paraffin sections were stored at room temperature conditions (20-25 °C), 4 °C, -20 °C and - 80 °C, respectively. PD-L1 staining was performed at 1, 2, 3, 4, 8, 12 and 24 weeks of storage. PD-L1 expression was assessed with a continuity score.

RESULTS

The PD-L1 antigen was gradually lost as the storage time of paraffin sections increased. The PD-L1 positivity rate was 97.18% at 1 week for the sections stored at room temperature, and decreased from 83.10 to 71.83% for the sections stored for 2 weeks to 4 weeks, and 61.97%, 54.93%, and 32.93% for 8, 12, and 24 weeks, respectively. When stored at low temperatures of 4 °C, -20 °C and - 80 °C, the positivity rate decreases with the same trend but more slowly compared to room temperature. The mean IC score of PD-L1 also showed a gradual decrease in all cases. In the consistency analysis, PD-L1 expression in slices stored at room temperature for 2 weeks was consistent with PD-L1 expression in fresh slices (ICC ≥ 0.9 for all slices), and PD-L1 expression in slices stored at 4 °C or -20 °C for 4 weeks was consistent with PD-L1 expression in fresh slices (ICC ≥ 0.9 for all slices). When stored under refrigeration at -80 °C, PD-L1 expression in slices stored for 3 weeks was consistent with that in fresh slices (ICC ≥ 0.9).

CONCLUSIONS

To our knowledge, this is the first article on the effect of preservation time and preservation temperature of paraffin sections on PD-L1 expression in breast cancer. Long-term storage of paraffin sections of unstained invasive breast cancer can lead to antigen loss of PD-L1 (SP142). Refrigerated storage of paraffin sections can delay antigen loss, with best results at 4 °C or -20 °C, and a storage time of no more than 4 weeks is recommended.

Correlation of tumor PD-L1 expression in different tissue types and outcome of PD-1-based immunotherapy in metastatic melanoma - analysis of the DeCOG prospective multicenter cohort study ADOREG/TRIM

BACKGROUND

PD-1-based immune checkpoint inhibition (ICI) is the major backbone of current melanoma therapy. Tumor PD-L1 expression represents one of few biomarkers predicting ICI therapy outcome. The objective of the present study was to systematically investigate whether the type of tumor tissue examined for PD-L1 expression has an impact on the correlation with ICI therapy outcome.

METHODS

Pre-treatment tumor tissue was collected within the prospective DeCOG cohort study ADOREG/TRIM (CA209-578; NCT05750511) between February 2014 and May 2020 from 448 consecutive patients who received PD-1-based ICI for non-resectable metastatic melanoma. The primary study endpoint was best overall response (BOR), secondary endpoints were progression-free (PFS) and overall survival (OS). All endpoints were correlated with tumor PD-L1 expression (quantified with clone 28-8; cutoff ≥5%) and stratified by tissue type.

FINDINGS

Tumor PD-L1 was determined in 95 primary tumors (PT; 36.8% positivity), 153 skin/subcutaneous (34.0% positivity), 115 lymph node (LN; 50.4% positivity), and 85 organ (40.8% positivity) metastases. Tumor PD-L1 correlated with BOR if determined in LN (OR = 0.319; 95% CI = 0.138-0.762; P = 0.010), but not in skin/subcutaneous metastases (OR = 0.656; 95% CI = 0.311-1.341; P = 0.26). PD-L1 positivity determined on LN metastases was associated with favorable survival (PFS, HR = 0.490; 95% CI = 0.310-0.775; P = 0.002; OS, HR = 0.519; 95% CI = 0.307-0.880; P = 0.014). PD-L1 positivity determined in PT (PFS, HR = 0.757; 95% CI = 0.467-1.226; P = 0.27; OS; HR = 0.528; 95% CI = 0.305-0.913; P = 0.032) was correlated with survival to a lesser extent. No relevant survival differences were detected by PD-L1 determined in skin/subcutaneous metastases (PFS, HR = 0.825; 95% CI = 0.555-1.226; P = 0.35; OS, HR = 1.083; 95% CI = 0.698-1.681; P = 0.72).

INTERPRETATION

For PD-1-based immunotherapy in melanoma, tumor PD-L1 determined in LN metastases was stronger correlated with therapy outcome than that assessed in PT or organ metastases. PD-L1 determined in skin/subcutaneous metastases showed no outcome correlation and therefore should be used with caution for clinical decision making.

FUNDING

Bristol-Myers Squibb (ADOREG/TRIM, NCT05750511); German Research Foundation (DFG; Clinician Scientist Program UMEA); Else Kröner-Fresenius-Stiftung (EKFS; Medical Scientist Academy UMESciA).

The progresses of relevant factors on the efficacy of immune checkpoint inhibitors in the non-small cell lung cancer patients

Lung cancer has the highest mortality rate of all cancers worldwide. Although immune checkpoint inhibitor (ICI)-based therapy can improve the survival of patients with lung cancer, its efficacy is affected by many factors. Therefore, it is necessary to identify factors that affect the efficacy of ICI-based treatment and establish a model for predicting drug response and resistance before and during treatment for individualized and accurate treatment of patients. This review summarizes the clinical and biological factors related to ICI-based treatment of non-small cell lung cancer (NSCLC) and the recent research progress of predictive models for assessing ICI efficacy.

Deciphering transcriptomic determinants of the divergent link between PD-L1 and immunotherapy efficacy

Programmed cell death ligand 1 (PD-L1) expression remains the most widely used biomarker for predicting response to immune checkpoint inhibitors (ICI), but its predictiveness varies considerably. Identification of factors accounting for the varying PD-L1 performance is urgently needed. Here, using data from three independent trials comprising 1239 patients, we have identified subsets of cancer with distinct PD-L1 predictiveness based on tumor transcriptome. In the Predictiveness-High (PH) group, PD-L1+ tumors show better overall survival, progression-free survival, and objective response rate with ICI than PD-L1- tumors across three trials. However, the Predictiveness-Low (PL) group demonstrates an opposite trend towards better outcomes for PD-L1- tumors. PD-L1+ tumors from the PH group demonstrate the superiority of ICI over chemotherapy, whereas PD-L1+ tumors from the PL group show comparable efficacy between two treatments or exhibit an opposite trend favoring chemotherapy. This observation of context-dependent predictiveness remains strong regardless of immune subtype (Immune-Enriched or Non-Immune), PD-L1 regulation mechanism (adaptative or constitutive), tumor mutation burden, or neoantigen load. This work illuminates avenues for optimizing the use of PD-L1 expression in clinical decision-making and trial design, although this exploratory concept should be further confirmed in large trials.

A case of discordant histology and expression of programmed death ligand 1 between primary tumor and brain metastases in adenosquamous carcinoma of the lung

A patient presented with vomiting and gait disturbance. Investigation revealed a single cerebellar tumor and another tumor in the upper lobe of the left lung. Based on the severe vomiting and gait disturbance, we removed the cerebellar tumor first, achieving resolution of symptoms. The cerebellar tumor was pathologically diagnosed as metastatic lung adenocarcinoma. No other metastases were identified, including in the mediastinal lymph nodes. We therefore resected the primary lung tumor. On final pathological analysis, the tumor in the upper lobe of the left lung was diagnosed as adenosquamous carcinoma with no lymph node metastasis. PD-L1 expression was low in the primary lung adenosquamous carcinoma and high in the cerebellar metastasis. Furthermore, both tumors were KRASG12C -positive. Tumor PD-L1 expression is considered important for immune escape. In this case, adenocarcinoma cells in the primary adenosquamous carcinoma may have migrated to form a cerebellar metastasis. In advanced lung cancer, tumor growth may be observed in some lesions even when many other lesions are controlled by chemo- or immunotherapy. Biopsy to confirm histology and PD-L1 expression is worth considering, depending on the location of the metastases and the invasiveness of the biopsy procedure.

Patlak-Ki derived from ultra-high sensitivity dynamic total body [18F]FDG PET/CT correlates with the response to induction immuno-chemotherapy in locally advanced non-small cell lung cancer patients

PURPOSE

This study aimed to investigate the predictive value of metabolic features in response to induction immuno-chemotherapy in patients with locally advanced non-small cell cancer (LA-NSCLC), using ultra-high sensitivity dynamic total body [18F]FDG PET/CT.

METHODS

The study analyzed LA-NSCLC patients who received two cycles of induction immuno-chemotherapy and underwent a 60-min dynamic total body [18F]FDG PET/CT scan before treatment. The primary tumors (PTs) were manually delineated, and their metabolic features, including the Patlak-Ki, Patlak-Intercept, maximum SUV (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were evaluated. The overall response rate (ORR) to induction immuno-chemotherapy was evaluated according to RECIST 1.1 criteria. The Patlak-Ki of PTs was calculated from the 20-60 min frames using the Patlak graphical analysis. The best feature was selected using Laplacian feature importance scores, and an unsupervised K-Means method was applied to cluster patients. ROC curve was used to examine the effect of selected metabolic feature in predicting tumor response to treatment. The targeted next generation sequencing on 1021 genes was conducted. The expressions of CD68, CD86, CD163, CD206, CD33, CD34, Ki67 and VEGFA were assayed through immunohistochemistry. The independent samples t test and the Mann-Whitney U test were applied in the intergroup comparison. Statistical significance was considered at P < 0.05.

RESULTS

Thirty-seven LA-NSCLC patients were analyzed between September 2020 and November 2021. All patients received two cycles of induction chemotherapy combined with Nivolumab/ Camrelizumab. The Laplacian scores showed that the Patlak-Ki of PTs had the highest importance for patient clustering, and the unsupervised K-Means derived decision boundary of Patlak-Ki was 2.779 ml/min/100 g. Patients were categorized into two groups based on their Patlak-Ki values: high FDG Patlak-Ki (H-FDG-Ki, Patlak-Ki > 2.779 ml/min/100 g) group (n = 23) and low FDG Patlak-Ki (L-FDG-Ki, Patlak-Ki ≤ 2.779 ml/min/100 g) group (n = 14). The ORR to induction immuno-chemotherapy was 67.6% (25/37) in the whole cohort, with 87% (20/23) in H-FDG-Ki group and 35.7% (5/14) in L-FDG-Ki group (P = 0.001). The sensitivity and specificity of Patlak-Ki in predicting the treatment response were 80% and 75%, respectively [AUC = 0.775 (95%CI 0.605-0.945)]. The expression of CD3+/CD8+ T cells and CD86+/CD163+/CD206+ macrophages were higher in the H-FDG-Ki group, while Ki67, CD33+ myeloid cells, CD34+ micro-vessel density (MVD) and tumor mutation burden (TMB) were comparable between the two groups.

CONCLUSIONS

The total body [18F]FDG PET/CT scanner performed a dynamic acquisition of the entire body and clustered LA-NSCLC patients into H-FDG-Ki and L-FDG-Ki groups based on the Patlak-Ki. Patients with H-FDG-Ki demonstrated better response to induction immuno-chemotherapy and higher levels of immune cell infiltration in the PTs compared to those with L-FDG-Ki. Further studies with a larger patient cohort are required to validate these findings.

Machine learning for prediction of immunotherapeutic outcome in non-small-cell lung cancer based on circulating cytokine signatures

BACKGROUND

Immune checkpoint inhibitor (ICI) therapy has substantially improved the overall survival (OS) in patients with non-small-cell lung cancer (NSCLC); however, its response rate is still modest. In this study, we developed a machine learning-based platform, namely the Cytokine-based ICI Response Index (CIRI), to predict the ICI response of patients with NSCLC based on the peripheral blood cytokine profiles.

METHODS

We enrolled 123 and 99 patients with NSCLC who received anti-PD-1/PD-L1 monotherapy or combined chemotherapy in the training and validation cohorts, respectively. The plasma concentrations of 93 cytokines were examined in the peripheral blood obtained from patients at baseline (pre) and 6 weeks after treatment (early during treatment: edt). Ensemble learning random survival forest classifiers were developed to select feature cytokines and predict the OS of patients undergoing ICI therapy.

RESULTS

Fourteen and 19 cytokines at baseline and on treatment, respectively, were selected to generate CIRI models (namely preCIRI14 and edtCIRI19), both of which successfully identified patients with worse OS in two completely independent cohorts. At the population level, the prediction accuracies of preCIRI14 and edtCIRI19, as indicated by the concordance indices (C-indices), were 0.700 and 0.751 in the validation cohort, respectively. At the individual level, patients with higher CIRI scores demonstrated worse OS [hazard ratio (HR): 0.274 and 0.163, and p<0.0001 and p=0.0044 in preCIRI14 and edtCIRI19, respectively]. By including other circulating and clinical features, improved prediction efficacy was observed in advanced models (preCIRI21 and edtCIRI27). The C-indices in the validation cohort were 0.764 and 0.757, respectively, whereas the HRs of preCIRI21 and edtCIRI27 were 0.141 (p<0.0001) and 0.158 (p=0.038), respectively.

CONCLUSIONS

The CIRI model is highly accurate and reproducible in determining the patients with NSCLC who would benefit from anti-PD-1/PD-L1 therapy with prolonged OS and may aid in clinical decision-making before and/or at the early stage of treatment.

Programmed Death-Ligand 1 Copy Number Alteration as an Adjunct Biomarker of Response to Immunotherapy in Advanced NSCLC

INTRODUCTION

This study aimed to evaluate the value of programmed death-ligand 1 (PD-L1) copy number (CN) alteration as an additional biomarker to standard immunohistochemistry (IHC) in predicting response to immune checkpoint inhibitor (ICI) therapy in advanced NSCLC.

METHODS

Before ICI monotherapy, tumor PD-L1 CN alteration (gain, neutral, or loss) was called using whole-exome sequencing data and compared with IHC results (tumor proportion score ≥50, 1-49, or 0). Progression-free survival (PFS) and overall survival were correlated with both biomarkers. In addition, the impact of CN alteration was further evaluated in two independent cohorts using next-generation sequencing panel.

RESULTS

A total of 291 patients with advanced-stage NSCLC met the study inclusion criteria. Although the IHC classification distinguished the best responsive group (tumor proportion score ≥ 50), the CN-based classification distinguished the worst responsive group (CN loss) from the others (PFS, p = 0.020; overall survival, p = 0.004). After adjusting for IHC results, CN loss was an independent risk factor for progression (adjusted hazard ratio = 1.32, 95% confidence interval: 1.00-1.73, p = 0.049) and death (adjusted hazard ratio = 1.39, 95% confidence interval: 1.05-1.85, p = 0.022). A risk classification system was developed on the basis of IHC and CN profiles, which outperformed the conventional IHC system. In the validation cohorts, CN loss determined by next-generation sequencing panel was independently associated with worse PFS after ICI treatment, revealing its practical value.

CONCLUSIONS

This is the first study to directly compare CN alterations with IHC results and survival outcomes after anti-PD-(L)1 therapy. Tumor PD-L1 CN loss can serve as an adjunct biomarker to predict the lack of response. Prospective studies are required to further validate this biomarker.

New Actions on Actionable Mutations in Lung Cancers

Actionable mutations refer to DNA alterations that, if detected, would be expected to affect patients' response to treatments [...].