Immune checkpoint therapy-current perspectives and future directions.

Immune checkpoint therapy (ICT) has dramatically altered clinical outcomes for cancer patients and conferred durable clinical benefits, including cure in a subset of patients. Varying response rates across tumor types and the need for predictive biomarkers to optimize patient selection to maximize efficacy and minimize toxicities prompted efforts to unravel immune and non-immune factors regulating the responses to ICT. This review highlights the biology of anti-tumor immunity underlying response and resistance to ICT, discusses efforts to address the current challenges with ICT, and outlines strategies to guide the development of subsequent clinical trials and combinatorial efforts with ICT.

Endocytosis Inhibition in Humans to Improve Responses to ADCC-Mediating Antibodies.

A safe and controlled manipulation of endocytosis in vivo may have disruptive therapeutic potential. Here, we demonstrate that the anti-emetic/anti-psychotic prochlorperazine can be repurposed to reversibly inhibit the in vivo endocytosis of membrane proteins targeted by therapeutic monoclonal antibodies, as directly demonstrated by our human tumor ex vivo assay. Temporary endocytosis inhibition results in enhanced target availability and improved efficiency of natural killer cell-mediated antibody-dependent cellular cytotoxicity (ADCC), a mediator of clinical responses induced by IgG1 antibodies, demonstrated here for cetuximab, trastuzumab, and avelumab. Extensive analysis of downstream signaling pathways ruled out on-target toxicities. By overcoming the heterogeneity of drug target availability that frequently characterizes poorly responsive or resistant tumors, clinical application of reversible endocytosis inhibition may considerably improve the clinical benefit of ADCC-mediating therapeutic antibodies.

Inhibition of PD-L1 expression in non-small cell lung cancer may reduce vasculogenic mimicry formation by inhibiting the epithelial mesenchymal transformation process.

Non-small cell lung cancer (NSCLC) is a kind of highly malignant tumor. Studies have shown that Vasculogenic mimicry (VM) may be responsible for dismal prognosis in NSCLC. Immunotherapy with programmed death-1 (PD-1) or programmed death ligand-1 (PD-L1) has significantly altered the treatment of assorted cancers, including NSCLC, but its role and mechanism in the formation of Vasculogenic mimicry (VM) in NSCLC remains unclear. This study aimed to investigate the role of the anti-PD-L1 antibody in the formation of VM in NSCLC and its possible mechanisms. The results showed that anti-PD-L1 antibody therapy could inhibit the growth of NSCLC-transplanted tumors and reduce the formation of VMs. In addition, this study found that anti-PD-L1 antibodies could increase the expression of the epithelial-mesenchymal transition (EMT) related factor E-cadherin. zinc finger E-box binding homeobox 1 (ZEB1) is an important transcription factor regulating EMT. Knocking down ZEB1 could significantly inhibit tumor growth, as well as the expression of VE-cadherin and mmp2, while remarkably increase the expression of E-cadherin. During this process, the formation of VM was inhibited by knowing down ZEB1 in both in vitro and in vivo experiments of the constructed ZEB1 knockdown stable transfected cell strains. Therefore, in this study, we found that anti-PD-L1 antibodies may reduce the formation of VMs by inhibiting the EMT process.

Identification, binding, and structural characterization of single domain anti-PD-L1 antibodies inhibitory of immune regulatory proteins PD-1 and CD80.

Programmed death-ligand 1 (PD-L1) is a key immune regulatory protein that interacts with programmed cell death protein 1 (PD-1), leading to T-cell suppression. Whilst this interaction is key in self-tolerance, cancer cells evade the immune system by overexpressing PD-L1. Inhibition of the PD-1/PD-L1 pathway with standard monoclonal antibodies has proven a highly effective cancer treatment; however, single domain antibodies (VHH) may offer numerous potential benefits. Here, we report the identification and characterization of a diverse panel of 16 novel VHHs specific to PD-L1. The panel of VHHs demonstrate affinities of 0.7 nM to 5.1 µM and were able to completely inhibit PD-1 binding to PD-L1. The binding site for each VHH on PD-L1 was determined using NMR chemical shift perturbation mapping and revealed a common binding surface encompassing the PD-1-binding site. Additionally, we solved crystal structures of two representative VHHs in complex with PD-L1, which revealed unique binding modes. Similar NMR experiments were used to identify the binding site of CD80 on PD-L1, which is another immune response regulatory element and interacts with PD-L1 localized on the same cell surface. CD80 and PD-1 were revealed to share a highly overlapping binding site on PD-L1, with the panel of VHHs identified expected to inhibit CD80 binding. Comparison of the CD80 and PD-1 binding sites on PD-L1 enabled the identification of a potential antibody binding region able to confer specificity for the inhibition of PD-1 binding only, which may offer therapeutic benefits to counteract cancer cell evasion of the immune system.

Membranous translocation of murine double minute 2 promotes the increased renal tubular immunogenicity in ischemia-reperfusion-induced acute kidney injury.

Kidneys from donors with prolonged warm and cold ischemia are prone to post-transplant T cell-mediated rejection (TCMR) due to ischemia-reperfusion injury (IRI). However, the precise mechanisms still remain obscure. Renal tubular epithelial cells (TECs) are the main target during IRI. Meanwhile, we reported previously that murine double minute 2 (MDM2) actively participates in TEC homeostasis during IRI. In this study, we established a murine model of renal IRI and a cell model of hypoxia/reoxygenation by culturing immortalized rat renal proximal tubule cells (NRK-52E) in a hypoxic environment for different time points followed by 24 hours of reoxygenation or incubating NRK-52E cells in a chemical anoxia/recovery environment. We found that during renal IRI, MDM2 expression increased on the membrane of TECs and aggregated mainly on the basolateral side. This process was accompanied by a reduction of a transmembrane protein programmed death-ligand 1 (PD-L1), a co-inhibitory second signal for T cells in TECs. By using mutant plasmids of MDM2 to anchor MDM2 on the cell membrane or nuclei, we found that the upregulation of membrane MDM2 could promote the ubiquitination of PD-L1 and lead to its ubiquitination-proteasome degradation. Lastly, we set up a co-culture system of TECs and CD4+ T cells in vitro; our results revealed that the immunogenicity of TECs was enhanced during IRI. In conclusion, our findings suggest that the increased immunogenicity of TECs during IRI may be related to ubiquitinated degradation of PD-L1 by increased MDM2 on the cell membrane, which consequently results in T cell activation and TCMR.

A Pipeline for Evaluation of Machine Learning/Artificial Intelligence Models to Quantify Programmed Death Ligand 1 Immunohistochemistry.

Immunohistochemistry (IHC) is used to guide treatment decisions in multiple cancer types. For treatment with checkpoint inhibitors, programmed death ligand 1 (PD-L1) IHC is used as a companion diagnostic. However, the scoring of PD-L1 is complicated by its expression in cancer and immune cells. Separation of cancer and noncancer regions is needed to calculate tumor proportion scores (TPS) of PD-L1, which is based on the percentage of PD-L1-positive cancer cells. Evaluation of PD-L1 expression requires highly experienced pathologists and is often challenging and time-consuming. Here, we used a multi-institutional cohort of 77 lung cancer cases stained centrally with the PD-L1 22C3 clone. We developed a 4-step pipeline for measuring TPS that includes the coregistration of hematoxylin and eosin, PD-L1, and negative control (NC) digital slides for exclusion of necrosis, segmentation of cancer regions, and quantification of PD-L1+ cells. As cancer segmentation is a challenging step for TPS generation, we trained DeepLab V3 in the Visiopharm software package to outline cancer regions in PD-L1 and NC images and evaluated the model performance by mean intersection over union (mIoU) against manual outlines. Only 14 cases were required to accomplish a mIoU of 0.82 for cancer segmentation in hematoxylin-stained NC cases. For PD-L1-stained slides, a model trained on PD-L1 tiles augmented by registered NC tiles achieved a mIoU of 0.79. In segmented cancer regions from whole slide images, the digital TPS achieved an accuracy of 75% against the manual TPS scores from the pathology report. Major reasons for algorithmic inaccuracies include the inclusion of immune cells in cancer outlines and poor nuclear segmentation of cancer cells. Our transparent and stepwise approach and performance metrics can be applied to any IHC assay to provide pathologists with important insights on when to apply and how to evaluate commercial automated IHC scoring systems.

Consistency Analysis of Programmed Death Ligand 1 Expression in Non-Small Cell Lung Cancer Between Pleural Effusion and Matched Primary Lung Cancer Tissues by Immunohistochemical Double Staining.

In clinical practice, programmed death ligand 1 (PD-L1) detection is prone to nonspecific staining due to the complex cellular composition of pleural effusion smears. In this study, diaminobenzidine (DAB) and 3-amino-9-ethylcarbazole (AEC) immunohistochemistry double staining was performed to investigate PD-L1 expression in tumor cells from malignant pleural effusion (MPE). MPE was considered as a metastasis in non-small cell lung cancer patients; thus, the heterogeneity between metastatic and primary lung cancer was revealed as well. Ninety paired specimens of MPE cell blocks and matched primary lung cancer tissues from non-small cell lung cancer patients were subjected to PD-L1 and thyroid transcription factor-1(TTF-1)/p63 immunohistochemistry double staining. Two experienced pathologists independently evaluated PD-L1 expression using 3 cutoffs (1%, 10%, and 50%). PD-L1 expression in MPE was strongly correlated with that in matched primary lung cancer tissues (R = 0.813; P < .001). Using a 4-tier scale (cutoffs: 1%, 10%, and 50%), the concordance was 71.1% (Cohen's κ = .534). Using a 2-tier scale, the concordance was 75.6% (1%, Cohen's κ = 0.53), 78.9% (10%, Cohen's κ = 0.574), and 95.6% (50%, Cohen's κ = 0.754). The rates of PD-L1 positivity in MPE (56.7%) were higher than that in lung tissues (32.2%). All 27 discordant cases had higher scores in MPE. The double-staining method provided superior identification of PD-L1-positive tumor cells on a background with nonspecific staining. In conclusion, PD-L1 expression was moderately concordant between metastatic MPE cell blocks and matched primary lung carcinoma tissues, with variability related to tumor heterogeneity. MPE should be considered to detect PD-L1 when histological specimens are unattainable, especially when PD-L1 expression is >50%. PD-L1 positivity rates were higher in MPE. Double staining can improve PD-L1 detection by reducing false-negative/positive results.

Characteristics of clinical trials of new oncology drugs approved in China.

BACKGROUND: Since reforms were introduced to incentivize drug innovation in 2015, the Chinese pharmaceutical market has experienced unprecedented prosperity, with more new drugs than ever before, especially anticancer treatments. In 2021, Chinese regulatory agencies issued the new guideline for clinical research and development of antitumor drugs, triggering a series of responses on the drug market. Limited research has outlined the nature of the original new drugs in China to understand the dynamic response of the market. METHODS: The objective of this article was to map the clinical development of approved new oncology drugs in China from 2015 to 2021 and differed from previous studies by focusing on original new drugs, using the United States as a benchmark, and elaborating the endogenous features of clinical trials. RESULTS: Clinical trials conducted in China have risen to a level similar to that of the United States in many aspects of trial design, but there is still distance between the implementation and operational details of clinical trials. In the meantime, China has made significant breakthroughs in drug approval. Greater than 60% of novel anticancer drugs in China received accelerated approved for their first listing. Approximately 90% of the pivotal clinical trials supporting initial drug approval used surrogate measures as end points, and one half were nonrandomized or did not have a control group. However, duplicate development without evidence of a clinical advantage compared with current therapies was widely observed. CONCLUSIONS: By presenting a multidimensional landscape of clinical trials and approvals in the real world, this review allows interested researchers, developers, and even regulators to understand what has been done and what should be done next in anticancer drug development in China.

PD-L1 and nectin-4 expression and genomic characterization of bladder cancer with divergent differentiation.

BACKGROUND: Bladder cancer with divergent differentiation (BCDD) comprises a heterogenous group of tumors with a poor prognosis, and differential expression of nectin-4 and programmed death ligand-1 (PD-L1) has been reported in BCDD. Importantly, nectin-4 expression in bladder cancer is associated with response to enfortumab vedotin, and PD-L1 expression is associated with responses to immune checkpoint inhibitors (ICIs). METHODS: The authors conducted a retrospective review identifying 117 patients with advanced or metastatic BCDD who were treated at Winship Cancer Institute from 2011 to 2021. They performed immunohistochemistry staining for nectin-4 and PD-L1 expression by histologic subtype as well as genomic analysis of these patients, including RNA sequencing, whole-exome sequencing, and fusion detection analysis as well as a subgroup genomic analysis of patients with BCDD who received ICIs. RESULTS: The results indicated that nectin-4 expression was highest in the groups who had the squamous and plasmacytoid subtypes, whereas the group that had the sarcomatoid subtype (70.8%) had the highest proportion of PD-L1-positive patients. Genomic analysis yielded several key findings, including a 50% RB1 mutation rate in patients who had small cell BCDD, targetable PIK3CA mutations across multiple subtypes of BCDD, and significantly higher expression of TEC in responders to ICIs. CONCLUSIONS: In this study, the authors identified clinically relevant data on nectin-4 and PD-L1 expression in patients with rare bladder tumors. They also identified several novel findings in the genomic analysis that highlight the role of precision medicine in this population of patients. Larger, prospective studies are needed to validate these hypothesis-generating data.

Cumulative incidence and risk factors of brain metastases in metastatic non-small cell lung cancer without baseline brain metastasis: Pooled analysis of individualized patient data from IMpower130, IMpower131, and IMpower150.

BACKGROUND: The objective of this study was to explore the abilities of atezolizumab plus chemotherapy in preventing brain metastases (BMs) among metastatic non-small cell lung cancer (NSCLC) without initial BMs, as well as the risk factors of BMs. METHODS: Individual patient data from three trials involving first-line atezolizumab for metastatic NSCLC (IMpower130, IMpower131, and IMpower150) were pooled. Among patients without baseline BMs and without epidermal growth factor receptor (EGFR) and/or anaplastic lymphoma kinase (ALK) mutations, those receiving atezolizumab + chemotherapy ± bevacizumab were classified as the atezolizumab plus chemotherapy group and those receiving placebo + chemotherapy ± bevacizumab were classified as the chemotherapy group. The cumulative incidences of BM (CI-BMs) between the two groups were compared. Other factors associated with the CI-BM were analyzed by Cox regression analyses. RESULTS: With a median follow-up of 17.6 months (range, 0.03-33.64 months), 74 (3.1%) of the 2380 enrolled patients developed BMs, including 50 (3.1%) and 24 (3.0%) in the atezolizumab plus chemotherapy group (n = 1589) and the chemotherapy group (n = 791), respectively. The CI-BMs at 6, 12, and 24 months were 1.7%, 2.8%, and 3.3%, respectively. After taking competing risk events into account, there was no significant difference in the CI-BMs between the two groups (p = .888). Nevertheless, the use of bevacizumab and the histology of nonsquamous NSCLC were found to be independently associated with the risk of BMs. CONCLUSIONS: In patients with metastatic EGFR/ALK wild-type NSCLC without baseline BMs, adding atezolizumab in the first-line treatment might not reduce the CI-BM. However, the administration of bevacizumab may reduce the risk of BMs.

Antiprogrammed death ligand 1 therapy failed to reduce the risk of developing brain metastases in patients with extensive-stage small cell lung cancer: A retrospective analysis.

BACKGROUND: Immunotherapy (IO) has demonstrated promising results in treating extensive-stage small cell lung cancer (ES-SCLC), and the management of ES-SCLC brain metastases (BMs) is now receiving significant clinical attention. The objective of this study was to evaluate the role of IO in the clinical management of BMs. METHODS: Between January 2020 and December 2021, the study included the records of 250 patients who were diagnosed with ES-SCLC. Overall survival (OS), progression-free survival, intracranial progression-free survival, and the cumulative incidence of BMs were calculated using the Kaplan-Meier method and were compared using the log-rank test. In addition, the Cox regression model was used to analyze prognostic factors. RESULTS: In the entire group, 85 patients had baseline BMs (IO plus chemotherapy [IO + ChT], n = 38; ChT alone, n = 47), and 165 patients (IO + ChT, n = 86; ChT alone, n = 79) did not have BMs at the time of initial diagnosis. The median follow-up was 22.4 months. The OS benefit with first-line antiprogrammed death ligand 1 therapy was maintained regardless of whether patients had BMs (with BMs, 17.97 vs. 13.14 months [p = .03]; without BMs, 18.46 vs. 15.05 months [p = .047]). However, in patients without BMs, IO did not delay the median time to developing brain progression (10.84 vs. 10.74 months; p = .84), and it did not significantly reduce the risk of developing intracranial metastases (the 2-year actuarial risk of developing BMs was 57.0% vs. 50.6%, respectively). CONCLUSIONS: Antiprogrammed death ligand 1 therapy improved OS regardless of the presence of BMs. However, IO did not delay the median time to brain progression or reduce the risk of intracranial metastasis in patients without baseline BMs. The findings of this study have important clinical implications for the future management of BMs from ES-SCLC.

Anti-PD-1 antibody in combination with radiotherapy as first-line therapy for unresectable intrahepatic cholangiocarcinoma.

BACKGROUND: Unresectable intrahepatic cholangiocarcinoma (iCCA) has a poor prognosis despite treatment with standard combination chemotherapy. We aimed to evaluate the efficacy and safety of radiotherapy in combination with an anti-PD-1 antibody in unresectable iCCA without distant metastases. METHODS: In this phase II study, patients with histopathologically confirmed unresectable primary or postoperative recurrent iCCA without distant metastases were enrolled. Patients received external radiotherapy with a dose of ≥45 Gy (2-2.5 Gy per fraction), followed by anti-PD-1 immunotherapy (camrelizumab 200 mg once, every 3 weeks) initiated within 7 days after completion of radiotherapy as first-line therapy. The primary endpoint was 1-year progression-free survival (PFS) rate. The secondary end points included safety, objective response rate (ORR), disease control rate (DCR), and overall survival (OS). RESULTS: From December 2019 to March 2021, 36 patients completed radiotherapy and at least one cycle of immunotherapy and were included in efficacy and safety analyses. The median follow-up was 19.0 months (IQR 12.0-24.0), and the one-year PFS rate was 44.4% (95% CI, 30.8-64.0). The median PFS was 12.0 months (95% CI, 7.5-not estimable); the median OS was 22.0 months (95% CI, 15.0-not estimable). The ORR was 61.1% and the DCR was 86.1%. Seventeen of 36 (47.2%) patients experienced treatment-related adverse effects (AEs) of any grade. The most common AE was reactive cutaneous capillary endothelial proliferation (25.0%). Five (13.9%) patients experienced grade ≥3 treatment-related AEs, including decreased lymphocyte (5.6%), bullous dermatitis (2.8%), decreased platelet count (2.8%), and deep-vein thrombosis (2.8%). CONCLUSIONS: External radiotherapy plus camrelizumab, as first-line therapy, met its primary endpoint and showed antitumor activity and low toxicity levels in patients with unresectable iCCA without distant metastases, warranting further investigation. TRIAL REGISTRATION: NCT03898895. Registered 2 April 2019.

A community challenge to predict clinical outcomes after immune checkpoint blockade in non-small cell lung cancer.

BACKGROUND: Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. METHODS: Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. RESULTS: A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1. CONCLUSIONS: This DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICI clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICI efficacy. TRIAL REGISTRATION: CheckMate 026; NCT02041533, registered January 22, 2014. CheckMate 227; NCT02477826, registered June 23, 2015.

sPD-L1 and sPD-L2 in plasma of patients with lung cancer and their clinical significance.

INTRODUCTION: Lung cancer is the leading cause of cancer death worldwide. We aim here to determine the soluble programmed death ligand-1 (sPD-L1) and soluble programmed death ligand-2 (sPD-L2) levels in the plasma of patients with lung cancer and evaluate the clinical significance. METHODS: Plasma samples from 95 lung cancer patients and 55 healthy donors were collected, and the sPD-L1 and sPD-L2 levels were measured using the enzyme-linked immunosorbent assay. The correlations of the plasma sPD-L1 and sPD-L2 levels with clinicopathological status and survival of the patients were analyzed. RESULTS: The sPD-L1 and sPD-L2 levels in plasma of lung cancer patients were 713.8 (240.6-3815) pg/ mL and 3233(1122-13955) pg/ mL, respectively, which were significantly higher than those of the health donors 618.6 (189.1-1149) pg/ mL and 2182 (1133-3471) pg/ mL, and the plasma levels of sPD-L1 are correlated with sPD-L2. ROC results showed that both sPD-L1 and sPD-L2 were potential biomarker for lung cancer, and with a higher accuracy level when combined with CEA. Patients with Higher plasma sPD-L1 level (>713.75 pg/ mL) are associated with poor overall survival in advanced lung cancer patients (197 days vs 643 days). CONCLUSIONS: The combination of sPD-L1 and sPD-L2 could be used as adjunctive diagnostic, High level of plasma sPD-L1 rather than sPD-L2 is associated with poor prognosis in lung cancer patients.

An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability.

AIMS: Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising clinical outcomes in urothelial carcinoma (UC). The combined positive score (CPS) quantifies PD-L1 22C3 expression in UC, but it can vary between pathologists due to the consideration of both immune and tumour cell positivity. METHODS AND RESULTS: An artificial intelligence (AI)-powered PD-L1 CPS analyser was developed using 1,275,907 cells and 6175.42 mm2 of tissue annotated by pathologists, extracted from 400 PD-L1 22C3-stained whole slide images of UC. We validated the AI model on 543 UC PD-L1 22C3 cases collected from three institutions. There were 446 cases (82.1%) where the CPS results (CPS ≥10 or <10) were in complete agreement between three pathologists, and 486 cases (89.5%) where the AI-powered CPS results matched the consensus of two or more pathologists. In the pathologist's assessment of the CPS, statistically significant differences were noted depending on the source hospital (P = 0.003). Three pathologists reevaluated discrepancy cases with AI-powered CPS results. After using the AI as a guide and revising, the complete agreement increased to 93.9%. The AI model contributed to improving the concordance between pathologists across various factors including hospital, specimen type, pathologic T stage, histologic subtypes, and dominant PD-L1-positive cell type. In the revised results, the evaluation discordance among slides from different hospitals was mitigated. CONCLUSION: This study suggests that AI models can help pathologists to reduce discrepancies between pathologists in quantifying immunohistochemistry including PD-L1 22C3 CPS, especially when evaluating data from different institutions, such as in a telepathology setting.

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.

DNA mismatch repair system regulates the expression of PD-L1 through DNMTs in cervical cancer.

BACKGROUND: Cervical cancer (CC) is a potential clinical application of PD-1/PD-L1 inhibitor. We aimed to study the mechanism of DNA mismatch repair (MMR) system regulating the expression of PD-L1 in CC through DNA methyltransferase (DNMTs). METHODS: We collected pathological specimens from 118 cases of CC to analyze the relationship between PD-L1 expression and DNMTs in different MMR states. RNA interference (RNAi) technique was used to simulate the formation of CC cell line with MMR deficiency (dMMR) state, and subcutaneous tumor formation experiment was carried out in nude mice to verify the relationship between PD-L1 expression and DNMTs in MMR state. RESULTS: The PD-L1 positive rate in 118 cases of CC was 58.47%, while the microsatellite instability (MSI) status accounted for 5.93%. There was a significant difference in the expression of PD-L1 between patients within the dMMR and MMR proficient (pMMR) groups (χ2 = 21.405, P < 0.001). Subcutaneous inoculation after infection of Siha cells led to successful tumorigenesis in nude mice, accompanied by a significant increase in the level of PD-L1 expression in the mouse tumors, while the expression level of MLH1 and MSH2 protein decreased significantly. We also found that PD-L1 expression was closely related to the expression of DNMTs. CONCLUSION: PD-L1 is universal expressed on the surface of CC cells, dMMR status enhances the expression of PD-L1 on the surface of CC cells, dMMR states of CC are related to the demethylation status of the PD-L1 gene promoter region.

Targeted protein degradation combined with PET imaging reveals the role of host PD-L1 in determining anti-PD-1 therapy efficacy.

PURPOSE: Immunohistochemical staining of programmed death-ligand 1 (PD-L1) in tumor biopsies acquired through invasive procedures is routinely employed in clinical practice to identify patients who are most likely to benefit from anti-programmed cell death protein 1 (PD-1) therapy. Nevertheless, PD-L1 expression is observed in various cellular subsets within tumors and their microenvironments, including tumor cells, dendritic cells, and macrophages. The impact of PD-L1 expression across these different cell types on the responsiveness to anti-PD-1 treatment is yet to be fully understood. METHODS: We synthesized polymer-based lysosome-targeting chimeras (LYTACs) that incorporate both PD-L1-targeting motifs and liver cell-specific asialoglycoprotein receptor (ASGPR) recognition elements. Small-animal positron emission tomography (PET) imaging of PD-L1 expression was also conducted using a PD-L1-specific radiotracer 89Zr-αPD-L1/Fab. RESULTS: The PD-L1 LYTAC platform was capable of specifically degrading PD-L1 expressed on liver cancer cells through the lysosomal degradation pathway via ASGPR without impacting the PD-L1 expression on host cells. When coupled with whole-body PD-L1 PET imaging, our studies revealed that host cell PD-L1, rather than tumor cell PD-L1, is pivotal in the antitumor response to anti-PD-1 therapy in a mouse model of liver cancer. CONCLUSION: The LYTAC strategy, enhanced by PET imaging, has the potential to surmount the limitations of knockout mouse models and to provide a versatile approach for the selective degradation of target proteins in vivo. This could significantly aid in the investigation of the roles and mechanisms of protein functions associated with specific cell subsets in living subjects.

Time-dependent efficacy analysis of first-line immunotherapies for advanced non-small cell lung cancer.

BACKGROUND: Many randomized controlled trials (RCTs) and network meta-analyses have demonstrated that the progression-free survival (PFS) and overall survival (OS) of advanced non-small cell lung cancer (NSCLC) patients can be improved through combination immunotherapy or monotherapies. However, time-dependent analysis of the treatment effect is currently lacking. Thus, we aimed to evaluate the efficacy of first-line immunotherapy, and establish a hazard ratio function to reflect the time-varying progression or mortality risk of patients with NSCLC. METHODS: Seventeen clinical trials were selected based on search strategy. Baseline characteristics, including the age, sex, smoking status, geographical region, and Eastern Cooperative Oncology Group (ECOG) performance status of patients, were balanced, resulting in ten immunotherapies from nine appropriate clinical trials to conduct treatment effect comparison. RESULTS: We found that nivolumab plus ipilimumab (nivo + ipi) improved the PFS and OS over time. The hazard ratio of nivo + ipi, relative to that of pembrolizumab, decreased from 1.11 to 0.36 for PFS, and from 0.93 to 0.49 for OS over a 10-year period. In terms of the response to immunotherapy in patients with different PD-L1 expression levels, patients with PD-L1 > = 50% experienced lower rates of progression and a reduced mortality risk over time. The hazard ratio of patients with PD-L1 > = 50% relative to all of the patients decreased from 0.73 to 0.69 for PFS, and from 0.78 to 0.67 for OS. CONCLUSIONS: Based on the fact that time-dependent progression and mortality risk existed during the treatment duration, physicians should select a suitable treatment regimen for patients based on the hazard ratio.

A novel computer-assisted tool for 3D imaging of programmed death-ligand 1 expression in immunofluorescence-stained and optically cleared breast cancer specimens.

BACKGROUND: Programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) are the two most common immune checkpoints targeted in triple-negative breast cancer (BC). Refining patient selection for immunotherapy is non-trivial and finding an appropriate digital pathology framework for spatial analysis of theranostic biomarkers for PD-1/PD-L1 inhibitors remains an unmet clinical need. METHODS: We describe a novel computer-assisted tool for three-dimensional (3D) imaging of PD-L1 expression in immunofluorescence-stained and optically cleared BC specimens (n = 20). The proposed 3D framework appeared to be feasible and showed a high overall agreement with traditional, clinical-grade two-dimensional (2D) staining techniques. Additionally, the results obtained for automated immune cell detection and analysis of PD-L1 expression were satisfactory. RESULTS: The spatial distribution of PD-L1 expression was heterogeneous across various BC tissue layers in the 3D space. Notably, there were six cases (30%) wherein PD-L1 expression levels along different layers crossed the 1% threshold for admitting patients to PD-1/PD-L1 inhibitors. The average PD-L1 expression in 3D space was different from that of traditional immunohistochemistry (IHC) in eight cases (40%). Pending further standardization and optimization, we expect that our technology will become a valuable addition for assessing PD-L1 expression in patients with BC. CONCLUSION: Via a single round of immunofluorescence imaging, our approach may provide a considerable improvement in patient stratification for cancer immunotherapy as compared with standard techniques.