PD-L1 Testing for Lung Cancer in 2019: Perspective From the IASLC Pathology Committee

Prognostic Value of 18 F-FDG PET/CT Metabolic Parameters in Resectable Non-small Cell Lung Cancer Treated With Neoadjuvant Immunotherapy Plus Chemotherapy

OBJECTIVE

This study investigates the predictive value of 18 F-FDG PET/CT metabolic parameters in patients with non-small cell lung cancer (NSCLC) undergoing neoadjuvant immunotherapy plus chemotherapy.

METHODS

We conducted a retrospective analysis of clinical data from 131 patients with pathologically confirmed NSCLC who were deemed resectable after 3 cycles of neoadjuvant immunotherapy plus chemotherapy. Pretreatment and post-treatment PET metabolic parameters were evaluated. CT assessments based on immune response evaluation criteria in solid tumors (iRECIST) were compared with PET/CT assessments using the response criteria in solid tumors (PERCIST). ROC curve analysis and Kaplan-Meier survival analysis, including univariate and Cox multivariate analyses, were employed to assess the prognostic value of PET metabolic parameters after treatment.

RESULTS

The PET/CT assessment based on PERCIST showed high consistency with prognosis, while the CT assessment based on iRECIST demonstrated low consistency. Statistically significant differences were observed between the iRECIST and PERCIST criteria ( P <0.001). ROC curve analysis revealed significant differences in post-treatment PET metabolic parameters (postSUVmax, postSUVmean, postSUVpeak, postMTV, and postTLG) as well as the percentage changes in metabolic parameters before and after treatment(Δ) (ΔSUVmax, ΔSUVmean, ΔSUVpeak, ΔMTV, and ΔTLG) ( P <0.05). Optimal cutoff values enabled stratification into high-risk and low-risk groups. Univariate analysis showed significantly higher survival in the low-risk group for all parameters except ΔMTV ( P =0.311), while Cox multivariate analysis identified ΔSUVmax as the most predictive.

CONCLUSIONS

The PERCIST is more accurate than iRECIST in evaluating prognosis for NSCLC neoadjuvant immunotherapy plus chemotherapy. PET metabolic parameters, particularly ΔSUVmax, effectively predict prognosis and support clinical decision-making.

Molecular testing of lung cancer in Australia: consensus best practice recommendations from the Royal College of Pathologists of Australasia in collaboration with the Thoracic Oncology Group of Australasia

Molecular testing plays a critical role in guiding optimal treatment decisions for lung cancer patients across a variety of clinical settings. While guidelines for biomarker testing exist in other jurisdictions, to date no best practice guidelines have been developed for the Australian setting. To address this need, the Royal College of Pathologists of Australasia collaborated with the Thoracic Oncology Group of Australasia to identify state-based pathologists, oncologists and consumer representatives to develop consensus best practice recommendations. Sixteen recommendations were established encompassing appropriate biomarkers, lung cancer subtype, tumour stage, specimen types, assay selection and quality assurance protocols that can inform and standardise best practice in molecular testing of lung cancer. These multidisciplinary evidence-based recommendations are designed to standardise and enhance molecular testing practices for lung cancers and should help ensure laboratories provide high-quality molecular testing of lung cancer for all Australians, including those from regional or remote communities.

The therapeutic efficacy and application prospects of tumor-treating fields (TTFields) in resolving malignant tumors of central nervous system

PURPOSE

Malignancies in the central nervous system (CNS) are among the most prevalent and lethal tumors. Tumor treating fields (TTFields), a physical therapeutic strategy, show significant potential in treating CNS tumors by inducing cell apoptosis, cell-cycle arrest, immune activation, and enhancing anti-PD-1 therapy efficacy. Additionally, TTFields can increase blood-brain barrier (BBB) permeability, further supporting their application in CNS malignancies. This review aims to summarize the advances and mechanisms of TTFields in CNS tumor treatment while addressing its current limitations and challenges.

METHODS

We reviewed existing literature on TTFields, focusing on their effects on glioma and brain metastasis (BM)-related primary tumors. The mechanisms investigated included mitosis and cell cycle interference, inhibition of cell migration and invasion, promotion of apoptosis and protective autophagy, activation of immunogenic cell death (ICD) and immune responses, and modulation of BBB permeability.

RESULTS

TTFields demonstrate inhibitory effects on CNS malignancies, particularly in glioma. They also suppress brain metastasis from primary tumors such as lung cancer, breast cancer, melanoma, and colorectal cancer. Mechanistically, TTFields act through multiple pathways, including disrupting mitosis, impeding cell migration and invasion, enhancing apoptosis and autophagy, activating immune responses, and increasing BBB permeability.

CONCLUSION

TTFields exhibit therapeutic potential in CNS malignancies, especially glioblastoma (GBM), through diverse biological mechanisms. Their ability to enhance BBB permeability and target metastatic tumors suggests promise for broader clinical applications, including brain metastasis treatment.

Genomics guiding personalized first-line immunotherapy response in lung and bladder tumors

BACKGROUND

Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment, particularly in advanced non-small cell lung cancer (NSCLC) and muscle-invasive bladder cancer (MIBC). However, identifying reliable predictive biomarkers for ICI response remains a significant challenge. In this study, we analyzed real-world cohorts of advanced NSCLC and MIBC patients treated with ICI as first-line therapy.

METHODS

Tumor samples underwent Whole Genome Sequencing (WGS) to identify specific somatic variants and assess tumor mutational burden (TMB). Additionally, mutational signature extraction and pathway enrichment analyses were performed to uncover the underlying mechanisms of ICI response. We also characterized HLA-I haplotypes and investigated LINE-1 retrotransposition.

RESULTS

Distinct mutation patterns were identified in patients who responded to treatment, suggesting potential biomarkers for predicting ICI effectiveness. In NSCLC, tumor mutational burden (TMB) did not differ significantly between responders and non-responders, while in MIBC, higher TMB was linked to better responses. Specific mutational signatures and HLA haplotypes were associated with ICI response in both cancers. Pathway analysis showed that NSCLC responders had active inflammatory and immune pathways, while pathways enriched in non-responders related to FGFR3 and neural crest differentiation, associated to resistance mechanisms. In MIBC, responders had alterations in DNA repair, leading to more neoantigens and a stronger ICI response. Importantly, for the first time, we found that LINE-1 activation was positively linked to ICI response, especially in MIBC.

CONCLUSION

These findings reveal promising biomarkers and mechanistic insights, offering a new perspective on predicting ICI response and opening up exciting possibilities for more personalized immunotherapy strategies in NSCLC and MIBC.

PD-L1 Scoring Models for Non-Small Cell Lung Cancer in China: Current Status, AI-Assisted Solutions and Future Perspectives

Immunotherapy has revolutionized the diagnosis and treatment model for patients with advanced non-small cell lung cancer (NSCLC). Numerous clinical trials and real-world reports have confirmed that PD-L1 status is a key factor for the successful use of immunotherapy in NSCLC, by predicting clinical outcomes and identifying patients most likely to benefit from this treatment. Therefore, accurate and standardized evaluation of PD-L1 expression is crucial. Currently, PD-L1 testing in China faces several challenges, including a heavy pathologist workload, a shortage of highly trained pathologists plus the inadequate capacity of diagnostic laboratories, confusion around different scoring methods, cut-off values, and indications, and limited concordance between PD-L1 assays. In this review, we summarize the current status and limitations of PD-L1 testing for patients with NSCLC in China and discuss recent progress in artificial intelligence-assisted PD-L1 scoring. Our review aims to support improvements in clinical PD-L1 testing practice and optimization of the prognosis and outcomes of immunotherapy in this patient population.

Unraveling the immune-activated tumor microenvironment correlated with clinical response to atezolizumab plus bevacizumab in advanced HCC

Background & Aims

Despite atezolizumab plus bevacizumab being a standard treatment for advanced hepatocellular carcinoma (HCC), a significant proportion of patients do not achieve durable benefit. This study aimed to identify predictive biomarkers for this therapy by investigating the role of immune activation within the tumor microenvironment (TME).

Methods

We characterized the intratumoral TME of patients with advanced HCC treated with atezolizumab plus bevacizumab using single cell transcriptomics on pretreatment tumor biopsies from 12 patients. To complement and support these findings, we integrated our single cell data with publicly available bulk RNA-sequencing data from independent clinical trial cohorts.

Results

Patients who responded to combination therapy with atezolizumab plus bevacizumab demonstrated an immune-activated TME, marked by enhanced cytotoxicity and a tumor-specific T cell response. These patients also exhibited an increased proportion of inflammatory cytokine-enriched tumor-associated macrophage clusters with stronger interactions with T cells, an increased population of conventional dendritic cells, and activated antigen-presenting function in tumor endothelial cells. When publicly available bulk RNA-sequencing data from independent clinical trial cohorts were analyzed, these immune activation features were associated with improved progression-free survival (median 10.8 months, 95% CI: 7.3-not reached versus 5.5 months, 95% CI: 4.0-6.7; p <0.001).

Conclusions

These findings suggest that the existence of an activated immune TME before treatment is crucial for a favorable clinical response in patients with HCC treated with atezolizumab plus bevacizumab.

Impact and implications

Only a subset of patients with HCC benefit from combination therapy with atezolizumab plus bevacizumab, limiting its clinical utility. In this study, we used single cell RNA analysis to identify TME features associated with a clinical response to this therapy. Our findings suggest that a pre-existing immune-activated TME is crucial for predicting the response to atezolizumab plus bevacizumab. Specifically, features such as enhanced T cell cytotoxicity, inflammatory cytokine-enriched macrophage clusters, active antigen presentation in endothelial cells, and an increased presence of dendritic cells may aid patient selection and inform therapeutic strategies.

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.

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.

Current Biomarkers in Non-Small Cell Lung Cancer-The Molecular Pathologist's Perspective

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide. Advances in tissue-based biomarkers have significantly enhanced diagnostic and therapeutic approaches in NSCLC, enabling precision medicine strategies. This review provides a comprehensive analysis of the molecular pathologist's practical approach to assessing NSCLC biomarkers across various specimen types (liquid biopsy, broncho-alveolar lavage, transbronchial biopsy/endobronchial ultrasound-guided biopsy, and surgical specimen), including challenges such as biological heterogeneity and preanalytical variability. We discuss the role of programmed death ligand 1 (PD-L1) immunohistochemistry in predicting immunotherapy response, the practice of histopathological tumor regression grading after neoadjuvant chemoimmunotherapy, and the application of DNA- and RNA-based techniques for detecting actionable molecular alterations. Finally, we emphasize the critical need for quality management to ensure the reliability and reproducibility of biomarker testing in NSCLC.

Clinicopathologic and genomic analyses of SMARCA4-mutated non-small cell lung carcinoma implicate the needs for tailored treatment strategies

BACKGROUND

The clinicopathologic and therapeutic significance of SMARCA4 mutation in non-small cell lung carcinoma (NSCLC) remains unclear.

METHODS

We retrieved 575 NSCLC cases from the clinical target sequencing cohort (N = 2157) to compare the clinicopathologic characteristics of groups subclassified based on the presence of truncated or non-truncated SMARCA4 mutations (SMARCA4-truncated, SMARCA4-non-truncated, and SMARCA4-wild type [WT]). The differences in gene expression profiles between these groups were evaluated using the TCGA-LUAD dataset.

RESULTS

Fifty (2.3%) SMARCA4-truncated and 63 (2.9%) SMARCA4-non-truncated NSCLCs were identified. The majority of SMARCA4-truncated NSCLCs were present in male smokers (94.0%) and pathologically diagnosed as adenocarcinoma (76.0%). The SMARCA4-truncated group showed rare targetable driver alterations with a higher tumor mutation burden than the SMARCA4-WT group. Gene expression profile analysis revealed that cancer/testis antigen (CTA) expression was enriched in the SMARCA4-truncated group, with up to 57% of the cases displaying immunoreactivities for MAGEA4, CT45A, and/or PRAME. The SMARCA4-non-truncated group showed heterogeneous clinicopathologic, genomic, and immunohistochemical features that fell between SMARCA4-truncated and WT groups. Both SMARCA4-truncated and non-truncated groups showed significantly poor prognosis with pemetrexed-platinum chemotherapy, yet there was no significant difference in survival following immune checkpoint inhibitor monotherapy.

CONCLUSION

SMARCA4-truncated NSCLC represents a variant of driver-negative NSCLC, mainly occurring in male smokers with poorly differentiated adenocarcinoma histology. In contrast, SMARCA4-non-truncated NSCLC indicates a heterogeneous subpopulation, exhibiting intermediate characteristics between the SMARCA4-truncated and SMARCA4-WT groups. While showing poor response to pemetrexed-platinum chemotherapy, increased CTA expression could be a novel therapeutic target in SMARCA4-mutated NSCLCs.

Enhanced thrombopoiesis supplies PD-L1 to circulating immune cells via the generation of PD-L1-expressing platelets in patients with lung cancer

BACKGROUND

The increased expression of programmed cell death ligand 1 (PD-L1) on a subset of immune cells in the peripheral blood has been frequently observed in patients with cancer, suggesting a relationship with PD-L1 expression in tumor tissues. In this study, we investigated the mechanisms underlying PD-L1 expression on various types of immune cells in the peripheral blood of patients with cancer.

METHODS

PD-L1 expression on various immune cell populations was analyzed in peripheral blood mononuclear cells of 112 patients with non-small cell lung cancer (NSCLC) using flow cytometry. A mouse model of X-ray-induced acute thrombocytopenia was used to investigate the relationship between thrombopoiesis and PD-L1-expressing platelet generation. The clinical significance of PD-L1-expressing platelets was analyzed in a cohort of patients with stage IV NSCLC who received a combination of anti-programmed cell death 1 (PD-1) therapy and chemotherapy.

RESULTS

All immune cell populations, including monocytes, T cells, B cells, and NK cells, showed higher PD-L1 expression in patients with cancer than in healthy controls. However, this increased frequency of PD-L1-expressing cells was not attributed to the expression of the cells themselves. Instead, it was entirely dependent on the direct interaction of the cells with PD-L1-expressing platelets. Notably, the platelet-dependent acquisition of PD-L1 on circulating immune cells of patients with lung cancer was observed in various other cancer types and was mechanistically associated with a surge in thrombopoiesis, resulting in the increased production of PD-L1-expressing reticulated platelets. Clinically, patients with enhanced thrombopoiesis and concurrently high PD-L1-expressing platelets exhibited a better response to anti-PD-1 therapy.

CONCLUSIONS

These findings highlight the role of tumor-associated thrombopoiesis in generating PD-L1-expressing platelets that may serve as a resource for PD-L1-positive cells in the circulation and act as a predictive biomarker for anti-PD-1/PD-L1 therapy.

Prognostic value of the lactate dehydrogenase to albumin ratio in advanced non-small cell lung cancer patients treated with the first-line PD-1 checkpoint inhibitors combined with chemotherapy

Background

This study aimed to investigate the prognostic value of pretreatment lactate dehydrogenase to albumin ratio (LAR) in advanced non-small cell lung cancer (NSCLC) patients treated with first-line programmed cell death protein 1 (PD-1) checkpoint inhibitors and chemotherapy.

Methods

A retrospective cohort study was conducted on advanced NSCLC patients treated with first-line PD-1 checkpoint inhibitors plus chemotherapy at Guangxi Medical University Cancer Hospital. The receiver operating characteristic (ROC) analysis determined the optimal LAR cutoff values for prediction. Univariate and multivariate analyses identified independent prognostic factors, and survival curves were estimated using the Kaplan-Meier method. Subgroup analysis evaluated the association between high LAR and disease progression and death risk.

Results

A total of 210 patients were enrolled, with a mean age of 58.56 ± 10.61 years and a male proportion of approximately 79.05%. ROC analysis found the optimal LAR cutoff value was 5.0, resulting in a sensitivity of 78.87% and a specificity of 44.6% (area under the ROC curve 0.622; P = 0.001). Multivariate analysis revealed a significant positive association between LAR and overall survival (OS) after adjusting for confounders (HR = 2.22, 95% CI = 1.25-3.96, P = 0.007). Subgroup analysis confirmed the relationship between high LAR and the risk of disease progression and death across all patient subgroups.

Conclusions

Pretreatment LAR may be a potential independent prognostic marker for advanced NSCLC patients receiving PD-1 checkpoint inhibitors plus chemotherapy. A large-scale, prospective study is necessary to confirm these findings.

Predicting cancer content in tiles of lung squamous cell carcinoma tumours with validation against pathologist labels

BACKGROUND

A growing body of research is using deep learning to explore the relationship between treatment biomarkers for lung cancer patients and cancer tissue morphology on digitized whole slide images (WSIs) of tumour resections. However, these WSIs typically contain non-cancer tissue, introducing noise during model training. As digital pathology models typically start with splitting WSIs into tiles, we propose a model that can be used to exclude non-cancer tiles from the WSIs of lung squamous cell carcinoma (SqCC) tumours.

METHODS

We obtained 116 WSIs of tumours from 35 different centres from the Cancer Genome Atlas. A pathologist completed or reviewed cancer contours in four regions of interest (ROIs) within each WSIs. We then split the ROIs into tiles labelled with the percentage of cancer tissue within them and trained VGG16 to predict this value, and then we calculated regression error. To measure classification performance and visualize the classification results, we thresholded the predictions and calculated the area under the receiver operating characteristic curve (AUC).

RESULTS

The model's median regression error was 4% with a standard deviation of 35%. At a cancer threshold of 50%, the model had an AUC of 0.83. False positives tended to be in tissues that surround cancer, tiles with <50% cancer, and areas with high immune activity. False negatives tended to be microtomy defects.

CONCLUSIONS

With further validation for each specific research application, the model we describe in this paper could facilitate the development of more effective research pipelines for predicting treatment biomarkers for lung SqCC.

PD-L1 and molecular biomarker expression in non-small cell lung cancer in Tunisian patients

In cancer treatment, PD-1 and PD-L1 inhibitors are thriving. Activated T lymphocytes express PD-1; it works with its ligand PD-L1 to limit T lymphocyte activation and prevent autoimmune disease. The expression of molecular biomarkers and PD-L1 in lung cancer determines the appropriate treatment strategy for patients with lung cancer. The purpose of this study was to look at the prevalence of molecular biomarkers and PD-L1 expression in a large group of Tunisian patients with advanced non-small cell lung cancer. We conducted an observational retrospective study in which medical/treatment history data were extracted retrospectively from medical records and archived tissue samples between January 1, 2019, and December 31, 2021. We gathered 157 patients who had recently been diagnosed with non-small cell lung carcinoma. In 36.9% of the cases, there was no molecular genotyping. EGFR (28.6%), KRAS (5.73%), and ALK gene rearrangement were the most common genotyping mutations (3.8%). ROS1 rearrangement was not present. There was a link between EGFR and gender, HER and age, and KRAS and biopsy tissue origin. Six of the tested cases with PD-L1 met the cut-off (350%). PD-L1 positivity was more common in solid-type adenocarcinoma (1.9%) than in acinar or papillary adenocarcinoma. There were no significant differences in PD-L1 expression across clinical and demographic parameters. High PD-L1 expression and molecular abnormalities were found in one case of EGFR, one case of BRAF, and one case of KRAS (three cases). All of the other specimens with abnormalities had a PD-L1<50%. ALK, ROS1, BRAF, KRAS, and MET were found to be significantly associated with PD-L1 expression. Our study is one of the country's largest, describing a large panel of biomarkers and their clinicopathologic/histopathologic associations in Tunisian lung cancer patients. We have the same molecular profile as European patients with an EGFR mutation, which is not the most common genotype abnormality in Tunisian patients. There is only one mutation at any given time. The expression of PD-L1 is determined by the histologic type and the origin of the biopsy tissue.

Novel Spatial Approaches to Dissect the Lung Cancer Immune Microenvironment

Lung cancer is a deadly disease with the highest rates of mortality. Over recent decades, a better understanding of the biological mechanisms implicated in its pathogenesis has led to the development of targeted therapies and immunotherapy, resulting in improvements in patient outcomes. To better understand lung cancer tumor biology and advance towards precision oncology, a comprehensive tumor profile is necessary. In recent years, novel in situ spatial multiomics approaches have emerged offering a more detailed view of the spatial location of tumor and tumor microenvironment cells, identifying their unique composition and functional status. In this sense, novel multiomics platforms have been developed to evaluate tumor heterogeneity, gene expression, metabolic reprogramming, signaling pathway activation, cell-cell interactions, and immune cell programs. In lung cancer research, several studies have used these spatial technologies to locate cells and associated them with histological features that are relevant to the pathogenesis of lung adenocarcinoma. These advancements may unveil further molecular and immune mechanisms in tumor biology that will lead to the discovery of biomarkers for treatment prediction and prognosis. In this review, we provide an overview of more widely used and emerging pathology-based approaches for spatial immune profiling in lung cancer and how they enhance our understanding of tumor biology and immune response.

PD-L1 expression, tumor-infiltrating lymphocytes, and mismatch repair proteins status in digestive neuroendocrine neoplasms: exploring their potential role as theragnostic and prognostic biomarkers

Theragnostic biomarkers are still needed to select patients with digestive neuroendocrine neoplasms (NENs) for an optimal management. The PD-1/PD-L1 pathway plays a pivotal role in T cells activation and host immune response to cancer and PD-L1 expression in tumor and/or immune cells is used to identify patients who would benefit of treatment with immune checkpoint inhibitors. However, its role as a biomarker is still unclear in digestive NENs. We investigated PD-L1 expression in 68 well-characterized digestive NENs (32 NETs, 32 NECs and 4 MiNENs) and TPS and CPS scores were calculated. In addition, tumor infiltrating T-lymphocytes and mismatch repair protein expression (MMR) were evaluated. All results were correlated with clinicopathological features. PD-L1 expression was higher in NECs than in NETs: TPS > 1% and/or CPS > 1 were observed in 16% of NETs, 68.8% of NECs and 50% of MiNENs (p: 0.05). The mean TPS score in positive cases was 6.3% in NETs, 16.2% in NECs and 5% in MiNENs. The CPS score was 4.8 in NETs, 8.1 in NECs and 6 in MiNENs. MMR-deficient neoplasms were more frequently observed in NECs than in NETs (p: < 0.05) as well as intra-tumor immune infiltration (p: 0.00001). No correlation between PD-L1 expression and survival or other clinicopathological parameters was observed. Our results suggest that treatment with immune checkpoint inhibitors may have a potential role only in selected cases, mainly in NECs and MiNENs.

Expression of claudin 18.2 in poorly cohesive carcinoma and its association with clinicopathologic parameters in East Asian patients

BACKGROUND

Poorly cohesive carcinoma (PCC) is a distinct subtype of gastric cancer with limited therapeutic options. This study investigated claudin (CLDN) 18.2 expression status in PCCs using a 43-13 A clone.

METHODS

We retrospectively collected 178 consecutive surgically resected stage Ⅱ-Ⅲ gastric cancer samples. Tissue microarray blocks were constructed for CLDN18.2 immunohistochemical staining. We studied CLDN18.2 expression and its association with clinicopathologic parameters.

RESULTS

CLDN18.2 positivity (defined by ≥ 75 % of tumor cells showing moderate to strong membranous positivity) was found in 34.8 % of the PCC cases (62/178). Approximately half of the CLDN18.2 positive PCCs demonstrated heterogeneous expression (51.6 %, 32/62). CLDN18.2 positivity was not associated with any clinicopathologic parameters examined. However, CLDN18.2 positivity tended to be more frequent in E-cadherin-positive PCCs (no loss of expression) than in E-cadherin-negative PCCs (loss of expression) (50 % vs. 27.7 %). The CLDN18.2 expression level, represented by the H-score, gradually decreased as the paraffin block storage time increased (P = 0.046). Overall survival and disease-free survival analyses showed no significant difference between CLDN18.2-positive and negative PCCs.

CONCLUSIONS

A significant portion of surgically resected PCC specimens showed CLDN18.2 positivity. Additionally, since the expression level of CLDN18.2 gradually decreases with increased paraffin block storage time, reflex testing can be considered at the time of the cancer diagnosis.

PD-L1+ Lymphocytes Are Associated with CD4+, Foxp3+CD4+, IL17+CD4+ T Cells and Subtypes of Macrophages in Resected Early-Stage Non-Small Cell Lung Cancer

The non-canonical PD-L1 pathway revealed that programmed-death ligand 1 (PD-L1) expression in immune cells also plays a crucial role in immune response. Moreover, immune cell distribution in a tumour microenvironment (TME) is pivotal for tumour genesis. However, the results remain controversial and further research is needed. Distribution of PD-L1-positive (PD-L1+) tumour-infiltrating lymphocytes in the context of TME was assessed in 72 archival I-III stage surgically resected NSCLC tumour specimens. Predominant PD-L1+ lymphocyte distribution in the tumour stroma, compared to islets, was found (p = 0.01). Higher PD-L1+ lymphocyte infiltration was detected in smokers due to their predominance in the stroma. High PD-L1+ lymphocyte infiltration in tumour stroma was more common in tumours with higher CD4+ T cell infiltration in islets and stroma, Foxp3+CD4+ T cell infiltration in islets and lover M1 macrophage infiltration in the stroma (p = 0.034, p = 0.034, p = 0.005 and p = 0.034 respectively). Meanwhile, high PD-L1+ lymphocyte infiltration in islets was predominantly found in tumours with high levels of IL-17A+CD4+ T cells in islets and Foxp3+CD4+ T cells in islets and stroma (p = 0.032, p = 0.009 and p = 0.034, respectively). Significant correlations between PD-L1+ lymphocytes and tumour-infiltrating CD4+, Foxp3+CD4+, IL-17A+CD4+ T cells and M2 macrophages were found. An analysis of the tumour-immune phenotype revealed a significant association between PD-L1 expression and IL17+CD4+ and Foxp3+CD4+ immune phenotypes. PD-L1+ lymphocytes are associated with the distribution of CD4+, Foxp3+CD4+, IL17A+CD4+ T cells, M1 and M2 macrophages in TME of resected NSCLC.

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.

The evolving landscape of immunohistochemistry in cervical and uterine carcinoma in gynecologic oncology: current status and future directions

Immunohistochemistry (IHC) has become an indispensable tool in routine gynecological pathology, particularly with the advancements in molecular understanding and histological classification of gynecological cancers. This evolution has led to new immunostainings for diagnostic and classification purposes. This review describes the diagnostic utility of IHC in gynecological neoplasms, drawing insights from literature reviews, personal experiences, and research findings. It delves into the application of IHC in resolving morphologically equivocal cases, emphasizing its role in achieving an accurate diagnosis. The selection of appropriate immunomarkers for common scenarios encountered in gynecological pathology aids pathologists in navigating complex cases. Specifically, we focus on cervical and endometrial malignancies, elucidating the molecular rationale behind the use of specific immunohistochemical markers. An updated overview of essential immunohistochemical markers provides knowledge for precise diagnosis and classification of gynecological cancers. This review serves as a valuable resource for clinicians and researchers involved in the management and study of gynecological malignancies, facilitating improved patient care and outcomes.

Lymphocyte T Subsets and Outcome of Immune Checkpoint Inhibitors in Melanoma Patients: An Oncologist's Perspective on Current Knowledge

Melanoma is the most aggressive and deadly form of skin cancer, and its incidence has been steadily increasing over the past few decades, particularly in the Caucasian population. Immune checkpoint inhibitors (ICI), anti-PD-1 monotherapy or in combination with anti-CTLA-4, and more recently, anti-PD-1 plus anti-LAG-3 have changed the clinical evolution of this disease. However, a significant percentage of patients do not benefit from these therapies. Therefore, to improve patient selection, it is imperative to look for novel biomarkers. Immune subsets, particularly the quantification of lymphocyte T populations, could contribute to the identification of ICI responders. The main purpose of this review is to thoroughly examine significant published data on the potential role of lymphocyte T subset distribution in peripheral blood (PB) or intratumorally as prognostic and predictive of response biomarkers in advanced melanoma patients treated with ICI regardless of BRAFV600 mutational status.

The gut microbiota improves the efficacy of immune-checkpoint inhibitor immunotherapy against tumors: From association to cause and effect

Immune-checkpoint inhibitors (ICIs), including anti-PD-1/PD-L1 therapeutic antibodies, have markedly enhanced survival across numerous cancer types. However, the limited number of patients with durable benefits creates an urgent need to identify response biomarkers and to develop novel strategies so as to improve response. It is widely recognized that the gut microbiome is a key mediator in shaping immunity. Additionally, the gut microbiome shows significant potential in predicting the response to and enhancing the efficacy of ICI immunotherapy against cancer. Recent studies encompassing mechanistic analyses and clinical trials of microbiome-based therapy have shown a cause-and-effect relationship between the gut microbiome and the modulation of the ICI immunotherapeutic response, greatly contributing to the establishment of novel strategies that will improve response and overcome resistance to ICI treatment. In this review, we outline the current state of research advances and discuss the future directions of utilizing the gut microbiome to enhance the efficacy of ICI immunotherapy against tumors.

Immunotherapy for small cell lung cancer: the current state and future trajectories

Small cell lung cancer (SCLC) constitutes approximately 10% to 15% of all lung cancer diagnoses and represents a pressing global public health challenge due to its high mortality rates. The efficacy of conventional treatments for SCLC is suboptimal, characterized by limited anti-tumoral effects and frequent relapses. In this context, emerging research has pivoted towards immunotherapy combined with chemotherapy, a rapidly advancing field that has shown promise in ameliorating the clinical outcomes of SCLC patients. Through originally developed for non-small cell lung cancer (NSCLC), these therapies have extended new treatment avenues for SCLC. Currently, a nexus of emerging hot-spot treatments has demonstrated significant therapeutic efficacy. Based on the amalgamation of chemotherapy and immunotherapy, and the development of new immunotherapy agents, the treatment of SCLC has seen the hoping future. Progress has been achieved in enhancing the tumor immune microenvironment through the concomitant use of chemotherapy, immunotherapy, and tyrosine kinase inhibitors (TKI), as evinced by emerging clinical trial data. Moreover, a tripartite approach involving immunotherapy, targeted therapy, and chemotherapy appears auspicious for future clinical applications. Overcoming resistance to post-immunotherapy regimens remains an urgent area of exploration. Finally, bispecific antibodies, adoptive cell transfer (ACT), oncolytic virus, monotherapy, including Delta-like ligand 3 (DLL3) and T cell immunoreceptor with Ig and ITIM domains (TIGIT), as well as precision medicine, may present a prospective route towards achieving curative outcomes in SCLC. This review aims to synthesize extant literature and highlight future directions in SCLC treatment, acknowledging the persistent challenges in the field. Furthermore, the continual development of novel therapeutic agents and technologies renders the future of SCLC treatment increasingly optimistic.

[Pathological Diagnostic Testing and Biomarkers for Perioperative System Therapy]

Optimal personalized treatment planning for resectable lung cancer requires quality-assured, standardized and prompt processing of tissue samples in pathological laboratories, as well as the determination of relevant predictive and prognostic biomarkers. Pathological diagnostic testing includes histological tumor typing, staging and tumor grading, resection status and, if necessary, regression grading after neoadjuvant systemic therapy. Histopathological typing is performed according to the current WHO classification and includes adenocarcinomas, squamous cell carcinomas, other non-small cell lung carcinomas (NSCLCs), carcinoids, small cell and large cell neuroendocrine carcinomas. Standardized tumor grading currently plays an important role in invasive non-mucinous adenocarcinoma in particular and enables prognostic risk assessment. The R classification and regression grading are also prognostically relevant. In the early stages of NSCLC, molecular biomarkers such as EGFR, ALK and PD-L1, are relevant for decisions on individual treatment. Testing is performed on FFPE tissue samples and must be carried out in a quality-assured manner and in accordance with international standards.

Rediscovering immunohistochemistry in lung cancer

Several observations indicate that protein expression analysis by immunohistochemistry (IHC) remains relevant in individuals with non-small-cell lung cancer (NSCLC) when considering targeted therapy, as an early step in diagnosis and for therapy selection. Since the advent of next-generation sequencing (NGS), the role of IHC in testing for NSCLC biomarkers has been forgotten or ignored. We discuss how protein-level investigations maintain a critical role in defining sensitivity to lung cancer therapies in oncogene- and non-oncogene-addicted cases and in patients eligible for immunotherapy, suggesting that IHC testing should be reconsidered in clinical practice. We also argue how a panel of IHC tests should be considered complementary to NGS and other genomic assays. This is relevant to current clinical diagnostic practice but with potential future roles to optimize the selection of patients for innovative therapies. At the same time, strict validation of antibodies, assays, scoring systems, and intra- and interobserver reproducibility is needed.

PD-L1 induces autophagy and primary resistance to EGFR-TKIs in EGFR-mutant lung adenocarcinoma via the MAPK signaling pathway

Resistance to epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) is a significant cause of treatment failure and cancer recurrence in non-small cell lung cancer (NSCLC). Approximately 30% of patients with EGFR-activating mutations exhibit primary resistance to EGFR-TKIs. However, the potential mechanisms of primary resistance to EGFR-TKIs remain poorly understood. Recent studies have shown that increased expression of programmed death ligand-1 (PD-L1) is associated with EGFR-TKIs resistance. Therefore, the present study aimed to investigate the mechanism of PD-L1 in primary resistance to EGFR-TKIs in EGFR-mutant lung adenocarcinoma (LUAD) cells. We found that PD-L1 was associated with poor prognosis in patients with EGFR-mutant LUAD, while the combination of EGFR-TKIs with chemotherapy could improve its therapeutic efficacy. In vitro and in vivo experiments revealed that PD-L1 promoted the proliferation and autophagy and inhibited the apoptosis of LUAD cells. Mechanistic studies demonstrated that upregulation of PD-L1 was critical in inducing autophagy through the mitogen-activated protein kinase (MAPK) signaling pathway, which was beneficial for tumor progression and the development of gefitinib resistance. Furthermore, we found that gefitinib combined with pemetrexed could synergistically enhance antitumor efficacy in PD-L1-overexpression LUAD cells. Overall, our study demonstrated that PD-L1 contributed to primary resistance to EGFR-TKIs in EGFR-mutant LUAD cells, which may be mediated by inducing autophagy via the MAPK signaling pathway. These findings not only help improve the prognosis of patients with EGFR-mutant LUAD but also provide a reference for the research of other cancer types.

Nano-Assisted Radiotherapy Strategies: New Opportunities for Treatment of Non-Small Cell Lung Cancer

Lung cancer is the second most commonly diagnosed cancer and a leading cause of cancer-related death, with non-small cell lung cancer (NSCLC) being the most prevalent type. Over 70% of lung cancer patients require radiotherapy (RT), which operates through direct and indirect mechanisms to treat cancer. However, RT can damage healthy tissues and encounter radiological resistance, making it crucial to enhance its precision to optimize treatment outcomes, minimize side effects, and overcome radioresistance. Integrating nanotechnology into RT presents a promising method to increase its efficacy. This review explores various nano-assisted RT strategies aimed at achieving precision treatment. These include using nanomaterials as radiosensitizers, applying nanotechnology to modify the tumor microenvironment, and employing nano-based radioprotectors and radiation-treated cell products for indirect cancer RT. We also explore recent advancements in nano-assisted RT for NSCLC, such as biomimetic targeting that alters mesenchymal stromal cells, magnetic targeting strategies, and nanosensitization with high-atomic number nanomaterials. Finally, we address the existing challenges and future directions of precision RT using nanotechnology, highlighting its potential clinical applications.

Programmed Death Ligand-1 and Tumor Mutation Burden Testing of Patients With Lung Cancer for Selection of Immune Checkpoint Inhibitor Therapies: Guideline From the College of American Pathologists, Association for Molecular Pathology, International Association for the Study of Lung Cancer, Pulmonary Pathology Society, and LUNGevity Foundation

CONTEXT.—

Rapid advancements in the understanding and manipulation of tumor-immune interactions have led to the approval of immune therapies for patients with non-small cell lung cancer. Certain immune checkpoint inhibitor therapies require the use of companion diagnostics, but methodologic variability has led to uncertainty around test selection and implementation in practice.

OBJECTIVE.—

To develop evidence-based guideline recommendations for the testing of immunotherapy/immunomodulatory biomarkers, including programmed death ligand-1 (PD-L1) and tumor mutation burden (TMB), in patients with lung cancer.

DESIGN.—

The College of American Pathologists convened a panel of experts in non-small cell lung cancer and biomarker testing to develop evidence-based recommendations in accordance with the standards for trustworthy clinical practice guidelines established by the National Academy of Medicine. A systematic literature review was conducted to address 8 key questions. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach, recommendations were created from the available evidence, certainty of that evidence, and key judgments as defined in the GRADE Evidence to Decision framework.

RESULTS.—

Six recommendation statements were developed.

CONCLUSIONS.—

This guideline summarizes the current understanding and hurdles associated with the use of PD-L1 expression and TMB testing for immune checkpoint inhibitor therapy selection in patients with advanced non-small cell lung cancer and presents evidence-based recommendations for PD-L1 and TMB testing in the clinical setting.

Genomic and Epigenomic Biomarkers of Immune Checkpoint Immunotherapy Response in Melanoma: Current and Future Perspectives

Immune checkpoint inhibitors (ICIs) demonstrate durable responses, long-term survival benefits, and improved outcomes in cancer patients compared to chemotherapy. However, the majority of cancer patients do not respond to ICIs, and a high proportion of those patients who do respond to ICI therapy develop innate or acquired resistance to ICIs, limiting their clinical utility. The most studied predictive tissue biomarkers for ICI response are PD-L1 immunohistochemical expression, DNA mismatch repair deficiency, and tumour mutation burden, although these are weak predictors of ICI response. The identification of better predictive biomarkers remains an important goal to improve the identification of patients who would benefit from ICIs. Here, we review established and emerging biomarkers of ICI response, focusing on epigenomic and genomic alterations in cancer patients, which have the potential to help guide single-agent ICI immunotherapy or ICI immunotherapy in combination with other ICI immunotherapies or agents. We briefly review the current status of ICI response biomarkers, including investigational biomarkers, and we present insights into several emerging and promising epigenomic biomarker candidates, including current knowledge gaps in the context of ICI immunotherapy response in melanoma patients.

Histogram analysis of multiple diffusion models for predicting advanced non-small cell lung cancer response to chemoimmunotherapy

BACKGROUND

There is an urgent need to find a reliable and effective imaging method to evaluate the therapeutic efficacy of immunochemotherapy in advanced non-small cell lung cancer (NSCLC). This study aimed to investigate the capability of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) histogram analysis based on different region of interest (ROI) selection methods for predicting treatment response to chemoimmunotherapy in advanced NSCLC.

METHODS

Seventy-two stage III or IV NSCLC patients who received chemoimmunotherapy were enrolled in this study. IVIM and DKI were performed before treatment. The patients were classified as responders group and non-responders group according to the Response Evaluation Criteria in Solid Tumors 1.1. The histogram parameters of ADC, Dslow, Dfast, f, Dk and K were measured using whole tumor volume ROI and single slice ROI analysis methods. Variables with statistical differences would be included in stepwise logistic regression analysis to determine independent parameters, by which the combined model was also established. And the receiver operating characteristic curve (ROC) were used to evaluate the prediction performance of histogram parameters and the combined model.

RESULTS

ADC, Dslow, Dk histogram metrics were significantly lower in the responders group than in the non-responders group, while the histogram parameters of f were significantly higher in the responders group than in the non-responders group (all P < 0.05). The mean value of each parameter was better than or equivalent to other histogram metrics, where the mean value of f obtained from whole tumor and single slice both had the highest AUC (AUC = 0.886 and 0.812, respectively) compared to other single parameters. The combined model improved the diagnostic efficiency with an AUC of 0.968 (whole tumor) and 0.893 (single slice), respectively.

CONCLUSIONS

Whole tumor volume ROI demonstrated better diagnostic ability than single slice ROI analysis, which indicated whole tumor histogram analysis of IVIM and DKI hold greater potential than single slice ROI analysis to be a promising tool of predicting therapeutic response to chemoimmunotherapy in advanced NSCLC at initial state.

Clinical significance and biological function of interferon regulatory factor 1 in non-small cell lung cancer

The clinical application and biological function of interferon regulatory factor 1 (IRF1) in non-small cell lung cancer (NSCLC) patients undergoing chemoimmunotherapy remain elusive. The aim of this study was to investigate the predictive and prognostic significance of IRF1 in NSCLC patients. We employed the cBioPortal database to predict frequency changes in IRF1 and explore its target genes. Bioinformatic methods were utilized to analyze the relationship between IRF1 and immune regulatory factors. Retrospective analysis of clinical samples was conducted to assess the predictive and prognostic value of IRF1 in chemoimmunotherapy. Additionally, A549 cells with varying IRF1 expression levels were constructed to investigate its effects on NSCLC cells, while animal experiments were performed to study the role of IRF1 in vivo. Our findings revealed that the primary mutation of IRF1 is deep deletion and it exhibits a close association with immune regulatory factors. KRAS and TP53 are among the target genes of IRF1, with interferon and IL-2 being the predominantly affected pathways. Clinically, IRF1 levels significantly correlate with the efficacy of chemoimmunotherapy. Patients with high IRF1 levels exhibited a median progression-free survival (mPFS) of 9.5 months, whereas those with low IRF1 levels had a shorter mPFS of 5.8 months. IRF1 levels positively correlate with PD-L1 distribution and circulating IL-2 levels. IL-2 enhances the biological function of IRF1 and recapitulates its role in vivo in the knockdown group. Therefore, IRF1 may possess predictive and prognostic value for chemoimmunotherapy in NSCLC patients through the regulation of the IL-2 inflammatory pathway.

PD-L1 expression in squamous cervical carcinomas of Mozambican women living with or without HIV

Programmed death-ligand 1 (PD-L1) is overexpressed in squamous cervical cancer (SCC) and can be used for targeted immunotherapy. The highest mortality rates of SCC are reported in sub-Saharan Africa, where Human immunodeficiency virus (HIV) prevalence is high. In Mozambique most SCC patients present at advanced stages. Thus, there is a need to introduce new treatment options. However, immunocompromised patients were frequently excluded in previous clinical trials. Our aim was to determine if PD-L1 expression in SCC is as prevalent among women living with HIV (WLWH) as among other patients. 575 SCC from Maputo Central Hospital were included. HIV status was available in 266 (46%) cases PD-L1 expression was scored through tumour proportion score (TPS) and combined positive score (CPS). PD-L1 was positive in 20.1% of the cases (n = 110), TPS (score ≥ 25%) and in 26.3% (n = 144), CPS (score ≥ 1). Stratifying according to the HIV status, WLWH were TPS positive in 16.7%, compared to 20.9%, p = 0.43, and concerning CPS 21.1% versus 28.7%, p = 0.19, respectively. PD-L1 status was not influenced by stage, Ki-67 or p16, CD8 expression influenced only CPS status. Our data indicates that the documented effect of PD-L1 therapy on SCC should be confirmed in randomized clinical trials in an HIV endemic milieu.

Endobronchial Ultrasound Guided Transbronchial Needle Aspiration and PD-L1 Yields

PURPOSE

Immunotherapy is a leading approach for treating advanced non-small cell lung cancer (NSCLC) by targeting the PD-1/PD-L1 checkpoint signaling pathway, particularly in tumors expressing high levels of PD-L1 (Jug et al. in J Am Soc Cytopathol 9:485-493, 2020; Perrotta et al. in Chest 158: 1230-1239, 2020). Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a minimally invasive method to obtain tissue for molecular studies, including PD-L1 analysis, in unresectable tumors (Genova et al. in Front Immunol 12: 799455, 2021; Wang et al. in Ann Oncol 29: 1417-1422, 2018). This study aimed to assess the adequacy of PD-L1 assessment in EBUS-TBNA cytology specimens.

METHODS

Data was collected retrospectively from patients who underwent EBUS-TBNA between 2017 and 2021 for suspected lung cancer biopsy. Samples positive for NSCLC were examined for PD-L1 expression. EBUS was performed by experienced practitioners, following institutional guidelines of a minimum of five aspirations from positively identified lesions. Sample adequacy for molecular testing was determined by the pathology department.

RESULTS

The analysis involved 387 NSCLC cases (149 squamous cell, 191 adenocarcinoma, 47 unspecified). Of the 263 EBUS-TBNA specimens tested for PD-L1, 237 (90.1%) were deemed adequate. While 84% adhered to the protocol, adherence did not yield better results. Significantly higher PD-L1 adequacy was observed in squamous cell carcinomas (93.2%) compared to adenocarcinoma (87.6%). The number of aspirations and sedation type did not correlate with PD-L1 adequacy in either cancer type, but lesion size and location had a significant impact in adenocarcinomas. Adenocarcinoma exhibited higher PD-L1 expression (68%) compared to squamous cell carcinoma (48%).

CONCLUSION

EBUS-TBNA offers high yields for assessing immunotherapy markers like PD-L1, with satisfactory adequacy regardless of NSCLC subtype, lesion size, or location.

Molecular Pathology of Lung Cancer

The identification of targetable genomic alterations in lung cancer is required as standard of care to guide optimal therapy selection. With a constantly evolving landscape of ancillary molecular and biomarker testing in lung cancer, pathologists need to be aware of what specimens to test, how the testing should be performed, and which targets to test for to provide the clinically relevant genomic information necessary to treat these patients. Several guideline statements on the topic are currently available to help pathologists and laboratory personnel best use the small specimens obtained from patients with lung cancer for ancillary molecular testing.

A novel subtype based on driver methylation-transcription in lung adenocarcinoma

AIMS

To identify driver methylation genes and a novel subtype of lung adenocarcinoma (LUAD) by multi-omics and elucidate its molecular features and clinical significance.

METHODS

We collected LUAD patients from public databases, and identified driver methylation genes (DMGs) by MethSig and MethylMix algrothms. And novel driver methylation multi-omics subtypes were identified by similarity network fusion (SNF). Furthermore, the prognosis, tumor microenvironment (TME), molecular features and therapy efficiency among subtypes were comprehensively evaluated.

RESULTS

147 overlapped driver methylation were identified and validated. By integrating the mRNA expression and methylation of DMGs using SNF, four distinct patterns, termed as S1-S4, were characterized by differences in prognosis, biological features, and TME. The S2 subtype showed unfavorable prognosis. By comparing the characteristics of the DMGs subtypes with the traditional subtypes, S3 was concentrated in proximal-inflammatory (PI) subtype, and S4 was consisted of terminal respiratory unit (TRU) subtype and PI subtype. By analyzing TME and epithelial mesenchymal transition (EMT) features, increased immune infiltration and higher expression of immune checkpoint genes were found in S3 and S4. While S4 showed higher EMT score and expression of EMT associated genes, indicating S4 may not be as immunosensitive as the S3. Additionally, S3 had lower TIDE and higher IPS score, indicating its increased sensitivity to immunotherapy.

CONCLUSION

The driver methylation-related subtypes of LUAD demonstrate prognostic predictive ability that could help inform treatment response and provide complementary information to the existing subtypes.

PD-L1 expression in resected lung adenocarcinoma: prevalence and prognostic significance in relation to the IASLC grading system

AIMS

Programmed death-ligand 1 (PD-L1) expression is a predictive biomarker for adjuvant immunotherapy and has been linked to poor differentiation in lung adenocarcinoma. However, its prevalence and prognostic role in the context of the novel histologic grade has not been evaluated.

METHODS

We analysed a cohort of 1233 patients with resected lung adenocarcinoma where PD-L1 immunohistochemistry (22C3 assay) was reflexively tested. Tumour PD-L1 expression was correlated with the new standardized International Association for the Study of Lung Cancer (IASLC) histologic grading system (G1, G2, and G3). Clinicopathologic features including patient outcome were analysed.

RESULTS

PD-L1 was positive (≥1%) in 7.0%, 23.5%, and 63.0% of G1, G2, and G3 tumours, respectively. PD-L1 positivity was significantly associated with male sex, smoking, and less sublobar resection among patients with G2 tumours, but this association was less pronounced in those with G3 tumours. PD-L1 was an independent risk factor for recurrence (adjusted hazard ratio [HR] = 3.25, 95% confidence intervals [CI] = 1.93-5.48, P < 0.001) and death (adjusted HR = 2.69, 95% CI = 1.13-6.40, P = 0.026) in the G2 group, but not in the G3 group (adjusted HR for recurrence = 0.94, 95% CI = 0.64-1.40, P = 0.778).

CONCLUSION

PD-L1 expression differs substantially across IASLC grades and identifies aggressive tumours within the G2 subgroup. This knowledge may be used for both prognostication and designing future studies on adjuvant immunotherapy.

Total metabolic tumor volume on 18F-FDG PET/CT is a game-changer for patients with metastatic lung cancer treated with immunotherapy

PURPOSE

Because of atypical response imaging patterns in patients with metastatic non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICPIs), new biomarkers are needed for a better monitoring of treatment efficacy. The aim of this prospective study was to evaluate the prognostic value of volume-derived positron-emission tomography (PET) parameters on baseline and follow-up 18F-fluoro-deoxy-glucose PET (18F-FDG-PET) scans and compare it with the conventional PET Response Criteria in Solid Tumors (PERCIST).

METHODS

Patients with metastatic NSCLC were included in two different single-center prospective trials. 18F-FDG-PET studies were performed before the start of immunotherapy (PETbaseline), after 6-8 weeks (PETinterim1) and after 12-16 weeks (PETinterim2) of treatment, using PERCIST criteria for tumor response assessment. Different metabolic parameters were evaluated: absolute values of maximum standardized uptake value (SUVmax) of the most intense lesion, total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), but also their percentage changes between PET studies (ΔSUVmax, ΔTMTV and ΔTLG). The median follow-up of patients was 31 (7.3-31.8) months. Prognostic values and optimal thresholds of PET parameters were estimated by ROC (Receiver Operating Characteristic) curve analysis of 12-month overall survival (12M-OS) and 6-month progression-free survival (6M-PFS). Tumor progression needed to be confirmed by a multidisciplinary tumor board, considering atypical response patterns on imaging.

RESULTS

110 patients were prospectively included. On PETbaseline, TMTV was predictive of 12M-OS [AUC (Area Under Curve) =0.64; 95% CI: 0.61 to 0.66] whereas SUVmax and TLG were not. On PETinterim1 and PETinterim2, all metabolic parameters were predictive for 12M-OS and 6M-PFS, the residual TMTV on PETinterim1 (TMTV1) being the strongest prognostic biomarker (AUC=0.83 and 0.82; 95% CI: 0.74 to 0.91, for 12M-OS and 6M-PFS, respectively). Using the optimal threshold by ROC curve to classify patients into three TMTV1 subgroups (0 cm3; 0-57 cm3; >57 cm3), TMTV1 prognostic stratification was independent of PERCIST criteria on both PFS and OS, and significantly outperformed them. Subgroup analysis demonstrated that TMTV1 remained a strong prognostic biomarker of 12M-OS for non-responding patients (p=0.0003) according to PERCIST criteria. In the specific group of patients with PERCIST progression on PETinterim1, low residual tumor volume (<57 cm3) was still associated with a very favorable patients' outcome (6M-PFS=73%; 24M-OS=55%).

CONCLUSION

The absolute value of residual metabolic tumor volume, assessed 6-8 weeks after the start of ICPI, is an optimal and independent prognostic measure, exceeding and complementing conventional PERCIST criteria. Oncologists should consider it in patients with first tumor progression according to PERCIST criteria, as it helps identify patients who benefit from continued treatment.

TRIAL REGISTRATION NUMBER

2018-A02116-49; NCT03584334.

Soluble immune-checkpoint factors: a potential immunotherapy biomarker

There is unmet need for additional biomarkers to better select patients with non-small cell lung cancer (NSCLC) that are likely to benefit from immunotherapy in order to improve patient outcomes, reduce patient toxicity, and relieve the growing burden of healthcare costs. In this issue of the JCI, Hayashi and colleagues evaluated soluble forms of the immune checkpoint molecules PD-L1, PD-1, and CTLA-4 in the plasma of patients with advanced NSCLC who had been treated with anti-PD-1/L1 therapy. The findings suggest that these soluble immune-checkpoint factors may provide a complementary biomarker to PD-L1 IHC, although application into the clinic may not be straightforward.

Immunotherapy and lung cytopathology: Overview and possibilities

Immunotherapy has become a promising cancer treatment in the past decade, and IHC is the most commonly used testing method for PDL-1/PD1 evaluation. In general, PD-L1 assays can be performed on both FFPE specimens and cytological samples. However, their use on smears is not yet well-established or validated. Nowadays, digital images and advanced algorithms can aid in interpreting PD-L1 in cytological samples. Understanding the immune environment of non-small cell lung cancer (NSCLC) is critical in developing successful anticancer immunotherapies. The use of a multiplexed immunofluorescence (mIF) assay on cytological samples obtained through minimally invasive methods appears to be a viable option for investigating the immune environment of NSCLC. This review aims to briefly summarize the knowledge of the role of cytopathology in the analysis of PD-L1 by immunocytochemistry (ICC) and future directions of cytopathology in the immunotherapy setting.

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.

Pulmonary Low Malignant Potential Adenocarcinoma: A Validation of the Proposed Criteria for This Novel Subtype

Adenocarcinoma (ADC) is the most common histologic type of lung cancer, including in situ (lepidic), minimally invasive, and invasive forms. While the former 2 types are associated with a favorable outcome, the latter includes tumors with variable behavior, often tumor stage-related. A recent study proposed strict morphologic criteria defining a new subgroup of resected stage I invasive ADC (16% of cases) with favorable outcomes (100% disease-specific survival), named "ADC of low malignant potential (LMP-ADC)." The following criteria were met: ≤3 cm size, nonmucinous histotype, ≥15% lepidic growth, and the absence of the following: high-grade patterns, >1 mitosis/2 mm 2 , necrosis, and vascular/pleural invasion. The aim of the present study was to validate the performance of such criteria to identify LMP-ADC in a series of 274 stage IA resected lung ADCs from a single institution. Thirty-four tumors (12.4%) met the proposed criteria for LMP-ADC, as confirmed by additional stains for mitotic figures, Ki67 index, and elastic fibers (helpful to assess alveolar wall invasion). Minor differences between the lepidic and invasive components were observed regarding cell atypia and proliferation. p53 was normally expressed by invasive tumor cells. Mutations occurred in known lung cancer genes (mostly KRAS and EGFR). Five patients (14.7%) developed disease progression and 2 of them (5.9%) died of the disease. In our series, the disease-specific survival was 94.1%. In conclusion, in resected invasive lung ADC, a subgroup presenting low-grade morphologic features and associated with favorable prognosis does exist. Morphologic criteria for LMP-ADC supported by ancillary techniques represent a valid tool to better define this novel subgroup and to refine the stratification of invasive lung ADC, possibly suggesting modified follow-up protocols, based on the observed indolent behavior in most cases.

Development of novel peptide-based radiotracers for detecting PD-L1 expression and guiding cancer immunotherapy

PURPOSE

Due to tumor heterogeneity, immunohistochemistry (IHC) showed poor accuracy in detecting the expression of programmed cell death ligand-1 (PD-L1) in patients. Positron emission tomography (PET) imaging is considered as a non-invasive technique to detect PD-L1 expression at the molecular level visually, real-timely and quantitatively. This study aimed to develop novel peptide-based radiotracers [68Ga]/[18F]AlF-NOTA-IMB for accurately detecting the PD-L1 expression and guiding the cancer immunotherapy.

METHODS

NOTA-IMB was prepared by connecting 2,2'-(7-(2-((2,5-dioxopyrrolidin-1-yl)oxy)- 2-oxoethyl)-1,4,7-triazonane-1,4-diyl) diacetic acid (NOTA-NHS) with PD-L1-targeted peptide IMB, and further radiolabeled with 68Ga or 18F-AlF. In vitro binding assay was conducted to confirm the ability of [68Ga]/[18F]AlF-NOTA-IMB to detect the expression of PD-L1. In vivo PET imaging of [68Ga]NOTA-IMB and [18F]AlF-NOTA-IMB in different tumor-bearing mice was performed, and dynamic changes of PD-L1 expression level induced by immunotherapy were monitored. Radioautography, western blotting, immunofluorescence staining and biodistribution analysis were carried out to further evaluate the specificity of radiotracers and efficacy of PD-L1 antibody immunotherapy.

RESULTS

[68Ga]NOTA-IMB and [18F]AlF-NOTA-IMB were both successfully prepared with high radiochemical yield (> 95% and > 60%, n = 5) and radiochemical purity (> 95% and > 98%, n = 5). Both tracers showed high affinity to human and murine PD-L1 with the dissociation constant (Kd) of 1.00 ± 0.16/1.09 ± 0.21 nM (A375-hPD-L1, n = 3) and 1.56 ± 0.58/1.21 ± 0.39 nM (MC38, n = 3), respectively. In vitro cell uptake assay revealed that both tracers can specifically bind to PD-L1 positive cancer cells A375-hPD-L1 and MC38 (5.45 ± 0.33/3.65 ± 0.15%AD and 5.87 ± 0.27/2.78 ± 0.08%AD at 120 min, n = 3). In vivo PET imaging and biodistribution analysis showed that the tracer [68Ga]NOTA-IMB and [18F]AlF-NOTA-IMB had high accumulation in A375-hPD-L1 and MC38 tumors, but low uptake in A375 tumor. Treatment of Atezolizumab induced dynamic changes of PD-L1 expression in MC38 tumor-bearing mice, and the tumor uptake of [68Ga]NOTA-IMB decreased from 3.30 ± 0.29%ID/mL to 1.58 ± 0.29%ID/mL (n = 3, P = 0.026) after five treatments. Similarly, the tumor uptake of [18F]AlF-NOTA-IMB decreased from 3.27 ± 0.63%ID/mL to 0.89 ± 0.18%ID/mL (n = 3, P = 0.0004) after five treatments. However, no significant difference was observed in the tumor uptake before and after PBS treatment. Biodistribution, radioautography, western blotting and immunofluorescence staining analysis further demonstrated that the expression level of PD-L1 in tumor-bearing mice treated with Atezolizumab significantly reduced about 3 times and correlated well with the PET imaging results.

CONCLUSION

[68Ga]NOTA-IMB and [18F]AlF-NOTA-IMB were successfully prepared for PET imaging the PD-L1 expression noninvasively and quantitatively. Dynamic changes of PD-L1 expression caused by immunotherapy can be sensitively detected by both tracers. Hence, the peptide-based radiotracers [68Ga]NOTA-IMB and [18F]AlF-NOTA-IMB can be applied for accurately detecting the PD-L1 expression in different tumors and monitoring the efficacy of immunotherapy.

Improving practice in PD-L1 testing of non-small cell lung cancer in the UK: current problems and potential solutions

AIMS

Programmed cell death ligand 1 (PD-L1) expression, used universally to predict response of non-small cell lung cancer (NSCLC) to immune-modulating drugs, is a fragile biomarker due to biological heterogeneity and challenges in interpretation. The aim of this study was to assess current PD-L1 testing practices in the UK, which may help to define strategies to improve its reliability and consistency.

METHODS

A questionnaire covering NSCLC PD-L1 testing practice was devised and members of the Association of Pulmonary Pathologists were invited to complete this online.

RESULTS

Of 44 pathologists identified as involved in PD-L1 testing, 32 (73%) responded. There was good consistency in practice and approach, but there was wide variability in the distribution of PD-L1 scoring. Although the proportions of scores falling into the three groups (negative, low and high) defined by the 1% and 50% 'cut-offs' (38%, 33% and 27%, respectively) reflect the general experience, the range within each group was wide at 23-70%, 10-60% and 15-36%, respectively.

CONCLUSIONS

There is inconsistency in the crucial endpoint of PD-L1 testing of NSCLC, the expression score that guides management. Addressing this requires formal networking of individuals and laboratories to devise a strategy for its reduction.

An increased relative eosinophil count as a predictive dynamic biomarker in non-small cell lung cancer patients treated with immune checkpoint inhibitors

BACKGROUND

An increased relative eosinophil count (REC) has potential as a predictive biomarker for a beneficial clinical response and outcome to cancer immunotherapies. Therefore, the present study investigated the impact of an increased posttreatment REC on the prognosis of non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs).

METHODS

We retrospectively reviewed all 151 patients diagnosed with NSCLC and treated with ICI monotherapy and blood test data between March 2016 and August 2021 at National Hospital Organization Kochi Hospital and Tokushima University.

RESULTS

A total of 151 patients with a mean age of 69 years were included. REC after 4 weeks of initial ICI monotherapy was higher than pretreatment REC in 87 patients but not in 64. REC after 4 weeks of the ICI treatment with and without an increased REC were 4.4 and 1.8%, respectively (p < 0.001). Disease control rates (DCR) were significantly higher in patients with than in those without an increased REC (84% vs. 47%, p < 0.001). The median overall survival (OS) of lung cancer patients with or without an increased REC were 674 and 234 days, respectively. A Kaplan-Meier univariate analysis revealed a significant difference in OS between the two groups (p < 0.001). A Cox proportional regression analysis identified an increased REC as an independent predictor of OS (p = 0.003).

CONCLUSION

ICI-treated NSCLC patients with an increased REC after 4 weeks of treatment had a better DCR and prognosis than the other patients examined.

Immunotherapy Guided by Immunohistochemistry PD-L1 Testing for Patients with NSCLC: A Microsimulation Model-Based Effectiveness and Cost-Effectiveness Analysis

BACKGROUND

On the basis of immunohistochemistry PD-L1 testing results, patients with advanced non-small cell lung cancer (NSCLC) are treated differently. Theoretically, patients with high PD-L1 expression (50% or 1%) should receive PD-1 monotherapy for fewer adverse reactions and cost savings from avoiding chemotherapy; however, there is controversy surrounding the cut-off criteria (1% or 50%) for immunohistochemistry testing and threshold for PD-1 monotherapy.

OBJECTIVE

This study aims to predict the effectiveness and cost-effectiveness of different immunotherapy strategies for patients with NSCLC in China from the healthcare system perspective.

PATIENTS AND METHODS

A microsimulation model was developed to evaluate the effectiveness and cost-effectiveness of three treatment strategies: PD-L1 testing (1%) (PD-1 monotherapy for those with PD-L1 expression at 1% threshold, and combination with chemotherapy for others with immunohistochemistry testing), PD-L1 testing (50%) (PD-1 monotherapy for those with PD-L1 expression at 50% threshold, and combination with chemotherapy for others with immunohistochemistry testing), and No PD-L1 testing (PD-1 combined with chemotherapy without immunohistochemistry testing). The model assumed 1000 patients per strategy, with each patient entering a unique clinical path prior to receiving treatment on the basis of PD-L1 test results. Clinical inputs were derived from clinical trials. Cost and utility parameters were obtained from the database and literature. One-way probabilistic sensitivity analyses (PSA) and six scenario analyses were used to test the model's robustness.

RESULTS

The study revealed a hierarchy of survival benefits across three strategies, with No PD-L1 testing demonstrating the most survival advantage, followed by PD-L1 testing (50%), and finally, PD-L1 testing (1%). The comparative analysis demonstrated that No PD-L1 testing significantly enhanced overall survival (OS) (HR 0.85, 95% CI 0.78-0.93), progression-free survival (HR 0.82, 95% CI 0.75-0.90), and progression-free2 survival (PFS2) (HR 0.91, 95% CI 0.83-0.99) when juxtaposed against PD-L1 testing (1%). However, these improvements were not as pronounced when compared with PD-L1 testing (50%), particularly in relation to PFS, PFS2, and OS. The cost-effectiveness analysis further unveiled incremental cost-utility ratios (ICUR), with No PD-L1 testing versus PD-L1 testing (50%) at $34,003 per quality-adjusted life year (QALY) and No PD-L1 testing versus PD-L1 testing (1%) at $34,804 per QALY. In parallel, the ICUR for PD-L1 testing (50%) versus PD-L1 testing (1%) stood at $35,713 per QALY. Remarkably, the PSA result under a willingness-to-pay (WTP) threshold of $10,144 per QALY, with a 100% probability, demonstrated PD-L1 testing (1%) as the most cost-effective option.

CONCLUSIONS

The survival benefits of PD-1 monotherapy for high expression with PD-L1 immunohistochemistry testing are inferior to those of PD-1 combined with chemotherapy without testing, but it is found to be more cost-effective at the WTP thresholds in China and holds great potential in increasing affordability and reducing the economic burden.

Functional Flow Cytometry to Predict PD-L1 Conformational Changes

The programmed cell death protein 1/programmed cell death protein ligand 1 (PD-1/PD-L1) axis is one of the most widely recognized targets for cancer immunotherapy. Importantly, PD-L1 conformational changes can hinder target binding when living cells are used. Antibody affinity, equilibrium binding, association and dissociation rates, and other affinity-related constants are fundamental to ensure target saturation. Here, PD-L1 changes in conformation and their potential impact on PD-L1 function and mutation are explored. Specifically, we present detailed flow cytometry procedures to analyze PD-L1 reactivity in myeloid-derived suppressor cells (MDSCs). This approach can also be used to study the contribution of protein conformational changes in living cells. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Sample preparation for PD-L1+ myeloid-derived suppressor cells detection by flow cytometry Basic Protocol 2: Protocol preparation, sample acquisition, and gating strategy for flow cytometric screening of PD-L1+ myeloid-derived suppressor cells in patients with lung cancer Support Protocol 1: Bioinformatic tools for the analysis of flow cytometric data.

Multiparametric MRI for evaluation of pathological response to the neoadjuvant chemo-immunotherapy in resectable non-small-cell lung cancer

OBJECTIVES

This study aimed to explore the predictive value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and diffusion kurtosis imaging (DKI) quantitative parameters for the response to neoadjuvant chemo-immunotherapy (NCIT) in resectable non-small-cell lung cancer (NSCLC) patients, so as to provide a basis for clinical individualized precision treatment.

METHODS

Treatment naive locally advanced NSCLC patients who enrolled in 3 prospective, open-label, and single-arm clinical trials and received NCIT were retrospectively analyzed in this study. Functional MRI imaging was performed at baseline and following 3 weeks of treatment as an exploratory endpoint to evaluate treatment efficacy. Univariate and multivariate logistic regressions were used to identify independent predictive parameters for NCIT response. Prediction models were built with statistically significant quantitative parameters and their combinations.

RESULTS

In total of 32 patients, 13 were classified as complete pathological response (pCR) and 19 were non-pCR. Post-NCIT ADC, ΔADC, and ΔD values in the pCR group were significantly higher than those in the non-pCR group, while the pre-NCIT D, post-NCIT Kapp, and ΔKapp were significantly lower than those in non-pCR group. Multivariate logistic regression analysis demonstrated that pre-NCIT D and post-NCIT Kapp values were independent predictors for NCIT response. The combined predictive model, which consisted of IVIM-DWI and DKI, showed the best prediction performance with AUC of 0.889.

CONCLUSIONS

The pre-NCIT D, post-NCIT parameters (ADC and Kapp) and Δ parameters (ΔADC, ΔD, and ΔKapp) were effective biomarkers for predicting pathologic response, and pre-NCIT D and post-NCIT Kapp values were independent predictors of NCIT response for NSCLC patients.

CLINICAL RELEVANCE STATEMENT

This exploratory study indicated that IVIM-DWI and DKI MRI imaging would predict pathologic response of neoadjuvant chemo-immunotherapy in locally advanced NSCLC patients at initial state and early treatment, which could help make clinical individualized treatment strategies.

KEY POINTS

• Effective NCIT treatment resulted in increased ADC and D values for NSCLC patients. • The residual tumors in non-pCR group tend to have higher microstructural complexity and heterogeneity, as measured by Kapp. • Pre-NCIT D and post-NCIT Kapp values were independent predictors of NCIT response.

Prior antibiotic administration disrupts anti-PD-1 responses in advanced gastric cancer by altering the gut microbiome and systemic immune response

Evidence on whether prior antibiotic (pATB) administration modulates outcomes of programmed cell death protein-1 (PD-1) inhibitors in advanced gastric cancer (AGC) is scarce. In this study, we find that pATB administration is consistently associated with poor progression-free survival (PFS) and overall survival (OS) in multiple cohorts consisting of patients with AGC treated with PD-1 inhibitors. In contrast, pATB does not affect outcomes among patients treated with irinotecan. Multivariable analysis of the overall patients treated with PD-1 inhibitors confirms that pATB administration independently predicts worse PFS and OS. Administration of pATBs is associated with diminished gut microbiome diversity, reduced abundance of Lactobacillus gasseri, and disproportional enrichment of circulating exhaustive CD8+ T cells, all of which are associated with worse outcomes. Considering the inferior treatment response and poor survival outcomes by pATB administration followed by PD-1 blockade, ATBs should be prescribed with caution in patients with AGC who are planning to receive PD-1 inhibitors.

Immune micro-environment analysis and establishment of response prediction model for PD-1 blockade immunotherapy in glioblastoma based on transcriptome deconvolution

PURPOSE

Only a small proportion of patients obtain survival benefit from PD-1 blockade immunotherapy due to the highly heterogeneous and suppressed immune micro-environment of GBM. We aimed at revealing the characteristics of tumor micro-environment (TME) of GBM related to response to PD-1 inhibitors and constructing a response prediction model for screening patients possibly benefit from PD-1 inhibitors.

METHODS

Based on the composition and expression profiles of cell subpopulations calculated by deconvoluting the GBM bulk RNA-seq, differentially expressed gene analysis and gene set enrichment analysis (GSEA) were performed to explore genes and pathways related to response to PD-1 inhibitors. Further by combining least absolute shrinkage and selection operator (LASSO) regression and expression correlation with PD-L1, the response prediction genes of PD-1 inhibitors were identified and the response prediction model was constructed through binary logistic regression.

RESULTS

The comparison of abundances of tumor infiltrating immune cells showed that the abundance of M0 macrophages of responders was lower, while the abundance of activated dendritic cells (DCs) was higher before PD-1 inhibitors treatment; the abundances of plasma cells and M0 macrophages of responders were lower after PD-1 inhibitors treatment. In addition, GSEA showed that the main up-regulation pathways in the tumor micro-environment of responders before PD-1 inhibitors treatment included the regulation of T-helper 1 type immune response, the positive regulation of natural killer cell-mediated cytotoxicity, p53 signaling pathway, homotypic cell-cell adhesion, etc., the main down-regulation pathways included the activation of microglia and myeloid leukocytes, Ras signaling pathway, etc. Afterward, ITGAX, LRRFIP1 and FMN1 were identified as the key response prediction genes of PD-1 inhibitors and the response prediction model based on them showed good predictive performance with potential value of clinical application in its validation and verification.

CONCLUSIONS

ITGAX, LRRFIP1 and FMN1 were identified as the response prediction genes of PD-1 inhibitors and the response prediction model based on them was proved to have potential clinical value.

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.