Differential Immune-Related Microenvironment Determines Programmed Cell Death Protein-1/Programmed Death-Ligand 1 Blockade Efficacy in Patients With Advanced NSCLC

Predictive biomarkers for immune checkpoint inhibitors therapy in lung cancer

Immune checkpoint inhibitors (ICIs) have changed the treatment mode of lung cancer, extending the survival time of patients unprecedentedly. Once patients respond to ICIs, the median duration of response is usually longer than that achieved with cytotoxic or targeted drugs. Unfortunately, there is still a large proportion of lung cancer patients do not respond to ICI. Effective biomarkers are crucial for identifying lung cancer patients who can benefit from them. The first predictive biomarker is programmed death-ligand 1 (PD-L1), but its predictive value is limited to specific populations. With the development of single-cell sequencing and spatial imaging technologies, as well as the use of deep learning and artificial intelligence, the identification of predictive biomarkers has been greatly expanded. In this review, we will dissect the biomarkers used to predict ICIs efficacy in lung cancer from the tumor-immune microenvironment and host perspectives, and describe cutting-edge technologies to further identify biomarkers.

Spatial heterogeneity of infiltrating immune cells in the tumor microenvironment of non-small cell lung cancer

Tumor-infiltrating lymphocytes (TILs) are essential components of the tumor microenvironment (TME) of non-small cell lung cancer (NSCLC). Still, it is difficult to describe due to their heterogeneity. In this study, five cell markers from NSCLC patients were analyzed. We segmented tumor cells (TCs) and TILs using Efficientnet-B3 and explored their quantitative information and spatial distribution. After that, we simulated multiplex immunohistochemistry (mIHC) by overlapping continuous single chromogenic IHCs slices. As a result, the proportion and the density of programmed cell death-ligand 1 (PD-L1)-positive TCs were the highest in the core. CD8+ T cells were the closest to the tumor (median distance: 41.71 μm), while PD-1+T cells were the most distant (median distance: 62.2μm), and our study found that most lymphocytes clustered together within the peritumoral range of 10-30 μm where cross-talk with TCs could be achieved. We also found that the classification of TME could be achieved using CD8+ T-cell density, which is correlated with the prognosis of patients. In addition, we achieved single chromogenic IHC slices overlap based on CD4-stained IHC slices. We explored the number and spatial distribution of cells in heterogeneous TME of NSCLC patients and achieved TME classification. We also found a way to show the co-expression of multiple molecules economically.

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

AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Efficacy and safety of anlotinib as maintenance therapy in patients with advanced non-small cell lung cancer achieving SD post first-line chemotherapy combined with immunotherapy

Advanced non-small cell lung cancer (NSCLC) remains a significant clinical challenge, particularly in patients who exhibit stable disease (SD) following first-line chemotherapy combined with immunotherapy. This study aims to evaluate the efficacy and safety of Anlotinib, a novel multitarget tyrosine kinase inhibitor, as maintenance therapy in this patient cohort. This retrospective, single-center study enrolled patients with advanced NSCLC who showed SD after receiving a combination of first-line chemo-immunotherapy for 4 cycles, then add anlotinib to subsequent standard maintenance therapy, continuing treatment until disease progression or the occurrence of intolerable toxic side effects. The primary endpoint was progression-free survival (P FS), overall survival (OS), objective response rate (ORR), disease control rate (DCR) and safety profile. A total of 52 patients were enrolled, the median P FS and OS was 5.0m and 10.0m, respectively. The ORR and DCR was 28.85% and 67.31%. subgroup analysis indicated that its efficacy correlate with certain Adverse Effects (AEs, such as hypertension, proteinuria, and hand-foot syndrome). Further mechanistic analysis suggests that this regimen may likely reduce immune suppression by depleting Tregs, thereby further activating the immune system to exert synergistic anti-tumor effects. Besides promising efficacy, the toxicity can be tolerated. Anlotinib demonstrates promising efficacy as a maintenance therapy in patients with advanced NSCLC who have achieved SD following first-line chemotherapy combined with immunotherapy. The manageable safety profile and the observed extension in P FS and OS suggest that Anlotinib could be a valuable therapeutic option for this challenging patient population. Further large-scale randomized controlled trials are warranted to confirm these findings and to optimize patient selection and management strategies.

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.

Impacts of tumor microenvironment during neoadjuvant chemotherapy in patients with esophageal squamous cell carcinoma

With the advent of immune checkpoint inhibitors (ICIs), a better understanding of tumor microenvironment (TME) is becoming crucial in managing esophageal squamous cell carcinoma (ESCC) patients. We investigated the survival impact of TME status and changes in patients with ESCC who underwent neoadjuvant chemotherapy (NAC) followed by surgery (n = 264). We examined immunohistochemical status (CD4+, CD8+, CD20+, Foxp3+, HLA class-1+, CD204+, and programmed death ligand-1 [PD-L1+]) on 264 pre-NAC and 204 paired post-NAC specimens. Patients were classified by their pre- and post-NAC immune cell status and their changes following NAC. Our findings showed that pre-NAC TME status was not significantly associated with survival outcomes. In contrast, post-NAC TME status, such as low level of T cells, CD4+ T cells, and high PD-L1 combined positive score (CPS), were significantly associated with poor overall survival (OS). Notably, TME changes through NAC exerted significant survival impacts; patients with consistently low levels of T cells, low levels of CD4+ T cells, or high levels of PD-L1 (CPS) had very poor OS (3-year OS: 35.5%, 40.2%, and 33.3%, respectively). Tumor microenvironment changes of consistently low T cells, low CD4+ T cells, and high PD-L1 were independent predictors of poor OS in multivariate Cox hazards analyses, while factors indicating post-NAC status (T cells, CD4+, and PD-L1 [CPS]) alone were not. Therefore, we suggest that the consistently low T/high PD-L1 group could benefit from additional therapies, such as ICIs, and the importance of stratification by the TME, which has recently been recognized.

Comparison of the efficacy of first‑/second‑generation EGFR‑tyrosine kinase inhibitors and osimertinib for EGFR‑mutant lung cancer with negative or low PD‑L1 expression

In epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) with negative or low programmed death ligand-1 (PD-L1) expression, the acquisition rate of the T790M mutation is higher after treatment with first-/second-generation EGFR-tyrosine kinase inhibitors (TKIs) and the progression-free survival (PFS) is longer in patients treated with osimertinib. The present study compared the clinical course after the initiation of each EGFR-TKI monotherapy in patients with EGFR-mutant NSCLC with negative or low PD-L1 expression. Data of patients with EGFR-mutant NSCLC with negative or low PD-L1 expression who were treated with EGFR-TKI monotherapy were retrieved and retrospectively analyzed. Between June 2013 and November 2023, 26 and 29 patients were treated with first-/second-generation EGFR-TKIs and osimertinib, respectively. The PFS time was longer in patients treated with osimertinib (median, 22.5 months) than in those treated with first-/second-generation EGFR-TKIs (median, 12.9 months). However, the EGFR-TKI treatment duration, defined as the PFS for osimertinib, or the sum of the PFS for first-/second-generation EGFR-TKIs and sequential osimertinib therapy after the acquisition of the T790M mutation, was similar between patients treated with first-/second-generation EGFR-TKIs (median, 23.0 months) and osimertinib (median, 22.5 months). The Cox proportional hazard model suggested that there was no significant difference in the EGFR-TKI treatment duration between patients treated with first-/second-generation EGFR-TKIs and patients treated with osimertinib (hazard ratio, 1.31, 95% CI, 0.55-3.13). In conclusion, first-/second-generation EGFR-TKIs and osimertinib were associated with a similar EGFR-TKI treatment duration in patients with EGFR-mutant NSCLC with negative or low PD-L1 expression. The findings suggested that both treatments are promising for this population.

Soluble immune checkpoint factors reflect exhaustion of antitumor immunity and response to PD-1 blockade

BACKGROUNDPrecise stratification of patients with non-small cell lung cancer (NSCLC) is needed for appropriate application of PD-1/PD-L1 blockade therapy.METHODSWe measured soluble forms of the immune-checkpoint molecules PD-L1, PD-1, and CTLA-4 in plasma of patients with advanced NSCLC before PD-1/PD-L1 blockade. A prospective biomarker-finding trial (cohort A) included 50 previously treated patients who received nivolumab. A retrospective observational study was performed for patients treated with any PD-1/PD-L1 blockade therapy (cohorts B and C), cytotoxic chemotherapy (cohort D), or targeted therapy (cohort E). Plasma samples from all patients were assayed for soluble immune-checkpoint molecules with a highly sensitive chemiluminescence-based assay.RESULTSNonresponsiveness to PD-1/PD-L1 blockade therapy was associated with higher concentrations of these soluble immune factors among patients with immune-reactive (hot) tumors. Such an association was not apparent for patients treated with cytotoxic chemotherapy or targeted therapy. Integrative analysis of tumor size, PD-L1 expression in tumor tissue (tPD-L1), and gene expression in tumor tissue and peripheral CD8+ T cells revealed that high concentrations of the 3 soluble immune factors were associated with hyper or terminal exhaustion of antitumor immunity. The combination of soluble PD-L1 (sPD-L1) and sCTLA-4 efficiently discriminated responsiveness to PD-1/PD-L1 blockade among patients with immune-reactive tumors.CONCLUSIONCombinations of soluble immune factors might be able to identify patients unlikely to respond to PD-1/PD-L1 blockade as a result of terminal exhaustion of antitumor immunity. Our data suggest that such a combination better predicts, along with tPD-L1, for the response of patients with NSCLC.TRIAL REGISTRATIONUMIN000019674.FUNDINGThis study was funded by Ono Pharmaceutical Co. Ltd. and Sysmex Corporation.

Cancer biomarkers: Emerging trends and clinical implications for personalized treatment

The integration of cancer biomarkers into oncology has revolutionized cancer treatment, yielding remarkable advancements in cancer therapeutics and the prognosis of cancer patients. The development of personalized medicine represents a turning point and a new paradigm in cancer management, as biomarkers enable oncologists to tailor treatments based on the unique molecular profile of each patient's tumor. In this review, we discuss the scientific milestones of cancer biomarkers and explore future possibilities to improve the management of patients with solid tumors. This progress is primarily attributed to the biological characterization of cancers, advancements in testing methodologies, elucidation of the immune microenvironment, and the ability to profile circulating tumor fractions. Integrating these insights promises to continually advance the precision oncology field, fostering better patient outcomes.

HOXC9 characterizes a suppressive tumor immune microenvironment and integration with multiple immune biomarkers predicts response to PD-1 blockade plus chemotherapy in lung adenocarcinoma

BACKGROUND

The quest for dependable biomarkers to predict responses to immune checkpoint inhibitors (ICIs) combined with chemotherapy in advanced non-small cell lung cancer remains unfulfilled. HOXC9, known for its role in oncogenesis and creating a suppressive tumor microenvironment (TME), shows promise in enhancing predictive precision when included as a TME biomarker. This study explores the predictive significance of HOXC9 for ICI plus chemotherapy efficacy in lung adenocarcinoma (LUAD).

METHODS

Following the bioinformatic findings, assays were performed to ascertain the effects of Hoxc9 on oncogenesis and response to programmed death 1 (PD-1) blockade. Furthermore, a cohort of LUAD patients were prospectively enrolled to receive anti-PD-1 plus chemotherapy. Based on the expression levels, baseline characteristics, and clinical outcomes, the predictive potential of HOXC9, PD-L1, CD4, CD8, CD68, and FOXP3 was integrally analyzed. HOXC9 not only mediated oncogenesis, but also corelated with suppressive TME. CMT167 and LLC cell lines unveiled the impacts of Hoxc9 on proliferation, invasion, and migration. Subsequently, tumor-bearing murine models were established to validate the inverse relationship between Hoxc9 expression and effective CD8+ T cells.

RESULTS

Inhibition of Hoxc9 significantly curtailed tumor growth (P<0.05), independent of PD-1 blockade. In patient studies, while individual markers fell short in prognosticating survival, a notable elevation in CD8-positive expression was observed in responders (P=0.042). Yet, the amalgamation of HOXC9 with other markers provided a more distinct differentiation between responders and non-responders. Notably, patients displaying PD-L1+/HOXC9- and CD8+/HOXC9- phenotypes exhibited significantly prolonged progression-free survival.

CONCLUSIONS

The expression of HOXC9 may serve as a biomarker to amplifying predictive efficacy for ICIs plus chemotherapy, which is also a viable oncogene and therapeutic target for immunotherapy in LUAD.

New clinical trial design in precision medicine: discovery, development and direction

In the era of precision medicine, it has been increasingly recognized that individuals with a certain disease are complex and different from each other. Due to the underestimation of the significant heterogeneity across participants in traditional "one-size-fits-all" trials, patient-centered trials that could provide optimal therapy customization to individuals with specific biomarkers were developed including the basket, umbrella, and platform trial designs under the master protocol framework. In recent years, the successive FDA approval of indications based on biomarker-guided master protocol designs has demonstrated that these new clinical trials are ushering in tremendous opportunities. Despite the rapid increase in the number of basket, umbrella, and platform trials, the current clinical and research understanding of these new trial designs, as compared with traditional trial designs, remains limited. The majority of the research focuses on methodologies, and there is a lack of in-depth insight concerning the underlying biological logic of these new clinical trial designs. Therefore, we provide this comprehensive review of the discovery and development of basket, umbrella, and platform trials and their underlying logic from the perspective of precision medicine. Meanwhile, we discuss future directions on the potential development of these new clinical design in view of the "Precision Pro", "Dynamic Precision", and "Intelligent Precision". This review would assist trial-related researchers to enhance the innovation and feasibility of clinical trial designs by expounding the underlying logic, which be essential to accelerate the progression of precision medicine.

CD57-positive CD8 + T cells define the response to anti-programmed cell death protein-1 immunotherapy in patients with advanced non-small cell lung cancer

Immune checkpoint inhibitors have transformed the treatment landscape of non-small cell lung cancer (NSCLC). However, accurately identifying patients who will benefit from immunotherapy remains a challenge. This study aimed to discover potential biomarkers for predicting immunotherapy response in NSCLC patients. Single-cell mass cytometry (CyTOF) was utilized to analyze immune cell subsets in peripheral blood mononuclear cells (PBMCs) obtained from NSCLC patients before and 12 weeks after single-agent immunotherapy. The CyTOF findings were subsequently validated using flow cytometry and multiplex immunohistochemistry/immunofluorescence in PBMCs and tumor tissues, respectively. RNA sequencing (RNA-seq) was performed to elucidate the underlying mechanisms. In the CyTOF cohort (n = 20), a high frequency of CD57+CD8+ T cells in PBMCs was associated with durable clinical benefit from immunotherapy in NSCLC patients (p = 0.034). This association was further confirmed in an independent cohort using flow cytometry (n = 27; p < 0.001), with a determined cutoff value of 12.85%. The cutoff value was subsequently validated in another independent cohort (AUC = 0.733). We also confirmed the CyTOF findings in pre-treatment formalin-fixed and paraffin-embedded tissues (n = 90; p < 0.001). RNA-seq analysis revealed 475 differentially expressed genes (DEGs) between CD57+CD8+ T cells and CD57-CD8+ T cells, with functional analysis identifying DEGs significantly enriched in immune-related signaling pathways. This study highlights CD57+CD8+ T cells as a promising biomarker for predicting immunotherapy success in NSCLC patients.

Biomarkers of immunotherapy for non-small cell lung cancer

Immunotherapy is revolutionizing the treatment of non-small cell lung cancer by targeting immune checkpoint proteins, including programmed death-1, programmed death ligand 1 and cytotoxic T-lymphocyte-associated antigen 4. Several immune checkpoint inhibitors, including programmed death ligand 1 inhibitors, programmed death-1 inhibitors and cytotoxic T-lymphocyte-associated antigen 4 inhibitors, were approved for the treatment of patients with advanced non-small cell lung cancer. Programmed death ligand 1 expression is currently the only predictive biomarker for immune checkpoint inhibitors to guide the treatment strategy in these patients. However, programmed death ligand 1 expression is not a perfect biomarker for predicting the efficacy of immunotherapy. Therefore, various biomarkers such as tumour mutation burden, tumour microenvironment, gut microbiome and T-cell receptor repertoire have been proposed to predict the efficacy of immunotherapy more accurately. Additionally, combining different biomarkers may provide a more accurate prediction of response to immunotherapy. This article reports the review of the latest evidence of the predictive marker of immunotherapy in patients with advanced non-small cell lung cancer.

First-line immunotherapy in non-small cell lung cancer: how to select and where to go

INTRODUCTION

Immunotherapy (IO) has established a new milestone in lung cancer treatment. Several registrational studies have approved immune checkpoint inhibitors (ICIs) in different settings, including the metastatic nonsmall cell lung cancer (NSCLC). As well known, responders are just a certain proportion of patients; therefore, their selection by using predictive factors has stood out as a crucial issue to address in tailoring a patient-centered care.

AREAS COVERED

In our review we propose a detailed yet handy cross section on ICIs as first-line treatment in metastatic NSCLC, regarding indications, histological, clinical, and blood-based biomarkers, other than their mechanisms of resistance and new immunological actionable targets. We performed a literature search through PubMed entering keywords complying with crucial features of immunotherapy.

EXPERT OPINION

IO represents the backbone of lung cancer treatment. Trials are currently testing novel immune blockade agents assessing combinatorial approaches with standard ICIs, or antibody drug conjugates (ADC), harboring immunological targets. Perfecting patients' selection is an ongoing challenge and a more and more urgent need in order to best predict responders who will consistently benefit from it.

Hot and cold tumors: Immunological features and the therapeutic strategies

The "hotness" or "coldness" of the tumors are determined by the information of the cancer cells themselves, tumor immune characteristics, tumor microenvironment, and signaling mechanisms, which are key factors affecting cancer patients' clinical efficacy. The switch mechanism of "hotness" and "coldness" and its corresponding pathological characteristics and treatment strategies are the frontier and hot spot of tumor treatment. How to distinguish the "hotness" or "coldness" effectively and clarify the causes, microenvironment state, and characteristics are very important for the tumor response and efficacy treatments. Starting from the concept of hot and cold tumor, this review systematically summarized the molecular characteristics, influencing factors, and therapeutic strategies of "hot and cold tumors," and analyzed the immunophenotypes, the tumor microenvironment, the signaling pathways, and the molecular markers that contribute to "hot and cold tumors" in details. Different therapeutic strategies for "cold and hot tumors" based on clinical efficacy were analyzed with drug targets and proteins for "cold and hot tumors." Furthermore, this review combines the therapeutic strategies of different "hot and cold tumors" with traditional medicine and modern medicine, to provide a basis and guidance for clinical decision-making of cancer treatment.

Tumor Microenvironment Landscape of NSCLC Reveals Resistance Mechanisms for Programmed Death-Ligand 1 Blockade After Chemoradiotherapy: A Multicenter Prospective Biomarker Study (WJOG11518L:SUBMARINE)

INTRODUCTION

The PACIFIC regimen of consolidation therapy with the programmed cell death-ligand 1 inhibitor durvalumab after definitive concurrent chemoradiation therapy has become a standard of care for individuals with unresectable stage III NSCLC. Nevertheless, approximately half of the treated patients experience disease progression within 1 year, with the mechanisms of treatment resistance being poorly understood. We here performed a nationwide prospective biomarker study to explore the resistance mechanisms (WJOG11518L:SUBMARINE).

METHODS

A total of 135 patients with unresectable stage III NSCLC who received the PACIFIC regimen were included for comprehensive profiling of the tumor microenvironment by immunohistochemistry, transcriptome analysis, and genomic sequencing of pretreatment tumor tissue and flow cytometric analysis of circulating immune cells. Progression-free survival was compared on the basis of these biomarkers.

RESULTS

The importance of preexisting effective adaptive immunity in tumors was revealed for treatment benefit regardless of genomic features. We also identified CD73 expression by cancer cells as a mechanism of resistance to the PACIFIC regimen. Multivariable analysis of immunohistochemistry data with key clinical factors as covariables indicated that low CD8+ tumor-infiltrating lymphocyte density and the high CD73+ cancer cells were independently associated with poor durvalumab outcome (hazard ratios = 4.05 [95% confidence interval: 1.17-14.04] for CD8+ tumor-infiltrating lymphocytes; 4.79 [95% confidence interval: 1.12-20.58] for CD73). In addition, whole-exome sequencing of paired tumor samples suggested that cancer cells eventually escaped immune pressure as a result of neoantigen plasticity.

CONCLUSIONS

Our study emphasizes the importance of functional adaptive immunity in stage III NSCLC and implicates CD73 as a promising treatment target, thus providing insight forming a basis for development of a new treatment approach in NSCLC.

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

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

Classification of Tumor Immune Microenvironment According to Programmed Death-Ligand 1 Expression and Immune Infiltration Predicts Response to Immunotherapy Plus Chemotherapy in Advanced Patients With NSCLC

INTRODUCTION

According to mechanisms of adaptive immune resistance, tumor immune microenvironment (TIME) is classified into four types: (1) programmed death-ligand 1 (PD-L1)-negative and tumor-infiltrating lymphocyte (TIL)-negative (type I); (2) PD-L1-positive and TIL-positive (type II); (3) PD-L1-negative and TIL-positive (type III); and (4) PD-L1-positive and TIL-negative (type IV). However, the relationship between the TIME classification model and immunotherapy efficacy has not been validated by any large-scale randomized controlled clinical trial among patients with advanced NSCLC.

METHODS

On the basis of RNA-sequencing and immunohistochemistry data from the ORIENT-11 study, we optimized the TIME classification model and evaluated its predictive value for the efficacy of immunotherapy plus chemotherapy.

RESULTS

PD-L1 mRNA expression and immune score calculated by the ESTIMATE method were the strongest predictors for the efficacy of immunotherapy plus chemotherapy. Therefore, they were determined as the optimized definition of the TIME classification system. When compared between combination therapy and chemotherapy alone, only the type II subpopulation with high immune score and high PD-L1 mRNA expression was significantly associated with improved progression-free survival (PFS) (hazard ratio = 0.12, 95% confidence interval: 0.06-0.25, p < 0.001) and overall survival (hazard ratio = 0.27, 95% confidence interval: 0.13-0.55, p < 0.001). In the combination group, the type II subpopulation had a much longer survival time, not even reaching the median PFS or overall survival, but the other three subpopulations were susceptible to having similar PFS. In the chemotherapy group, there was no marked association between survival outcomes and TIME subtypes.

CONCLUSIONS

Only patients with both high PD-L1 expression and high immune infiltration could benefit from chemotherapy plus immunotherapy in first-line treatment of advanced NSCLC. For patients lacking either PD-L1 expression or immune infiltration, chemotherapy alone might be a better treatment option to avoid unnecessary toxicities and financial burdens.

Mechanistic rationales for combining immunotherapy with radiotherapy

Immunotherapy consisted mainly of immune checkpoint inhibitors (ICIs) has led to significantly improved antitumor response. However, such response has been observed only in tumors possessing an overall responsive tumor immune micro-environment (TIME), in which the presence of functional tumor-infiltrating lymphocytes (TILs) is critical. Various mechanisms of immune escape from immunosurveillance exist, leading to different TIME phenotypes in correlation with primary or acquired resistance to ICIs. Radiotherapy has been shown to induce antitumor immunity not only in the irradiated primary tumor, but also at unirradiated distant sites of metastases. Such antitumor immunity is mainly elicited by radiation's stimulatory effects on antigenicity and adjuvanticity. Furthermore, it may be significantly augmented when irradiation is combined with immunotherapy, such as ICIs. Therefore, radiotherapy represents one potential therapeutic strategy to restore anti-tumor immunity in tumors presenting with an unresponsive TIME. In this review, the generation of anti-tumor immunity, its impairment, radiation's immunogenic properties, and the antitumor effects of combining radiation with immunotherapy will be comprehensively discussed.

Identification of inflamed-phenotype of small cell lung cancer leading to the efficacy of anti-PD-L1 antibody and chemotherapy

BACKGROUND

Platinum etoposide plus anti-programmed cell death ligand-1 (PD-L1) antibody therapy is the standard of care for extensive-stage small cell lung cancer (ES-SCLC). However, patient characteristics associated with the efficacy of the combination therapy in SCLC are unclear.

METHODS

We retrospectively reviewed post-surgical limited-stage (LS)-SCLC and ES-SCLC patients treated with atezolizumab plus carboplatin and etoposide (ACE). The association between SCLC subtypes based on transcriptomic data and pathological findings, including CD8-positive tumor-infiltrating lymphocyte (TIL) status, was investigated in the LS-SCLC cohort. The association between the efficacy of ACE therapy, pathological subtypes, and TIL status was evaluated in the ES-SCLC cohort.

RESULTS

The LS-SCLC cohort (N = 48) was classified into four SCLC subtypes (ASCL1 + NEUROD1 [SCLC-A + N, N = 17], POU2F3 [SCLC-P, N = 15], YAP1 [SCLC-Y, N = 10], and inflamed [SCLC-I, N = 6]) based on transcriptomic data. SCLC-I showed enriched immune-related pathways, the highest immune score (CD8A expression and T-cell-inflamed gene expression profiles), and epithelial-mesenchymal transition (EMT), in transcriptional subtypes. Immunohistochemical staining (IHC) showed that SCLC-I had the highest density of CD8-positive TILs in transcriptional subtypes. In the ES-SCLC cohort, the efficacy of ACE therapy did not differ according to pathological subtypes. The progression-free survival (PFS) of TIL_High patients was significantly longer than that of TIL_Low patients (PFS: 7.3 months vs. 4.0 months, p < 0.001).

CONCLUSION

Tumors with a high density of TILs, which represent the most immunogenic SCLC subtype (SCLC-I), based on transcriptomic data could benefit from ACE therapy.

Characterization of Infiltrating Immune Cells and Secretory or Membrane-Associated Proteins in KRAS Lung Adenocarcinoma

Background

This study identified the expression and prognosis significance of secretory or membrane-associated proteins in KRAS lung adenocarcinoma (LUAD) and depicted the characteristics between the immune cell infiltration and the expression of these genes.

Methods

Gene expression data of LUAD samples (n = 563) were accessed from The Cancer Genome Atlas (TCGA). The expression of secretory or membrane-associated proteins was compared among the KRAS-mutant, wild-type, and normal groups, as well as the subgroup of the KRAS-mutant group. We identified the survival-related differentially expressed secretory or membrane-associated proteins and conducted the functional enrichment analysis. Then, the characterization and association between their expression and the 24 immune cell subsets were investigated. We also constructed a scoring model to predict KRAS mutation by LASSO and logistic regression analysis.

Results

Secretory or membrane-associated genes with differential expression (n = 74) across three groups (137 KRAS LUAD, 368 wild-type LUAD, and 58 normal groups) were identified, and the results of GO and KEGG indicated that they were strongly associated with immune cell infiltrations. Among them, ten genes were significantly related to the survival of patients with KRAS LUAD. The expression of IL37, KIF2, INSR, and AQP3 had the most significant correlations with immune cell infiltration. In addition, eight DEGs from the KRAS subgroups were highly correlated with immune infiltrations, especially TNFSF13B. Using LASSO-logistic regression, a KRAS mutation prediction model based on the 74 differentially expressed secretory or membrane-associated genes was built, and the accuracy was 0.79.

Conclusion

The research investigated the relationship between the expression of KRAS-related secretory or membrane-associated proteins in LUAD patients with prognostic prediction and immune infiltration characterization. Our study demonstrated that secretory or membrane-associated genes were closely associated with the survival of KRAS LUAD patients and were strongly correlated to immune cell infiltration.

High post-chemotherapy TIL and increased CD4+TIL are independent prognostic factors of surgically resected NSCLC following neoadjuvant chemotherapy

Neoadjuvant chemotherapy (NCT) has significantly improved the overall survival of patients with operable non-small cell lung cancer (NSCLC). Chemotherapy can remodel the tumor immune microenvironment (TIME) and has an important influence on antitumor immunity. For patients who underwent surgery for resected NSCLC following NCT (NCT-NSCLC), a prognostic value comparison between naïve and post-chemotherapy TIME is absent. We enrolled 89 patients with NCT-NSCLC in this study; the tumor-infiltrating lymphocyte (TIL), CD4+TIL, and CD8+TIL levels in naïve and post-chemotherapy tumor tissues were detected using immunohistochemistry staining and divided into high and low groups. Kaplan-Meier analysis revealed that major pathology response, pathological tumor, node, and metastasis stage post-NCT (ypTNM), high post-chemotherapy TIL, high post-chemotherapy CD8+TIL, low naïve CD4+TIL, low naïve CD4+/CD8+TIL ratio, and increased CD4+TIL levels post-chemotherapy were favorable prognostic factors in patients with NCT-NSCLC. Multivariate Cox analysis found that ypTNM, high post-chemotherapy TIL, and increased CD4+TIL levels post-chemotherapy were independent prognostic factors in patients with NCT-NSCLC. These results indicate that a TIME remodeled by chemotherapy plays an important role in antitumor immunity and has a better prognostic value than the naïve TIME.

Nanoparticles overcome adaptive immune resistance and enhance immunotherapy via targeting tumor microenvironment in lung cancer

Lung cancer is one of the common malignant cancers worldwide. Immune checkpoint inhibitor (ICI) therapy has improved survival of lung cancer patients. However, ICI therapy leads to adaptive immune resistance and displays resistance to PD-1/PD-L1 blockade in lung cancer, leading to less immune response of lung cancer patients. Tumor microenvironment (TME) is an integral tumor microenvironment, which is involved in immunotherapy resistance. Nanomedicine has been used to enhance the immunotherapy in lung cancer. In this review article, we described the association between TME and immunotherapy in lung cancer. We also highlighted the importance of TME in immunotherapy in lung cancer. Moreover, we discussed how nanoparticles are involved in regulation of TME to improve the efficacy of immunotherapy, including Nanomedicine SGT-53, AZD1080, Nanomodulator NRF2, Cisplatin nanoparticles, Au@PG, DPAICP@ME, SPIO NP@M-P, NBTXR3 nanoparticles, ARAC nanoparticles, Nano-DOX, MS NPs, Nab-paclitaxel, GNPs-hPD-L1 siRNA. Furthermore, we concluded that targeting TME by nanoparticles could be helpful to overcome resistance to PD-1/PD-L1 blockade in lung cancer.

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

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

Multiplexed imaging of tumor immune microenvironmental markers in locally advanced or metastatic non-small-cell lung cancer characterizes the features of response to PD-1 blockade plus chemotherapy

BACKGROUND

Although programmed cell death 1 (PD-1) blockade plus chemotherapy can significantly prolong the progression-free survival (PFS) and overall survival (OS) in first-line settings in patients with driver-negative advanced non-small-cell lung cancer (NSCLC), the predictive biomarkers remain undetermined. Here, we investigated the predictive value of tumor immune microenvironmental marker expression to characterize the response features to PD-1 blockade plus chemotherapy.

METHODS

Tumor tissue samples at baseline were prospectively collected from 144 locally advanced or metastatic NSCLC patients without driver gene alterations who received camrelizumab plus chemotherapy or chemotherapy alone. Tumor immune microenvironmental markers, including PD-1 ligand (PD-L1), CD8, CD68, CD4 and forkhead box P3, were assessed using multiplex immunofluorescence (mIF) assays. Kaplan-Meier curves were used to determine treatment outcome differences according to their expression status. Mutational profiles were compared between tumors with distinct expression levels of these markers and their combinations.

RESULTS

Responders had significantly higher CD8/PD-L1 (P = 0.015) or CD68/PD-L1 co-expression levels (P = 0.021) than non-responders in the camrelizumab plus chemotherapy group, while no difference was observed in the chemotherapy group. Patients with high CD8/PD-L1 or CD68/PD-L1 co-expression level was associated with significantly longer PFS (P = 0.002, P = 0.024; respectively) and OS (P = 0.006, P = 0.026; respectively) than those with low co-expression in camrelizumab plus chemotherapy group. When comparing survival in the camrelizumab plus chemotherapy with chemotherapy by CD8/PD-L1 co-expression stratification, significantly better PFS (P = 0.003) and OS (P = 0.032) were observed in high co-expression subgroups. The predictive value of CD8/PD-L1 and CD68/PD-L1 co-expression remained statistically significant for PFS and OS when adjusting clinicopathological features. Although the prevalence of TP53 or KRAS mutations was similar between patients with and without CD8/PD-L1 or CD68/PD-L1 co-expression, the positive groups had a significantly higher proportion of TP53/KRAS co-mutations than the negative groups (both 13.0% vs. 0.0%, P = 0.023). Notably, enriched PI3K (P = 0.012) and cell cycle pathway (P = 0.021) were found in the CD8/PD-L1 co-expression group.

CONCLUSION

Tumor immune microenvironmental marker expression, especially CD8/PD-L1 or CD68/PD-L1 co-expression, was associated with the efficacy of PD-1 blockade plus chemotherapy as first-line treatment in patients with advanced NSCLC.

The efficacy and safety analysis of first-line immune checkpoint inhibitors in pulmonary sarcomatoid carcinoma

Background

Pulmonary sarcomatoid carcinoma (PSC) is a rare and aggressive disease without standardized treatment strategies. The efficacy of second-line or beyond immune checkpoint inhibitors (ICIs) has been proven in recent studies, whereas the evidence for first-line immunotherapy for PSC is still limited to case reports and remains poorly understood.

Materials and methods

This was a multicenter, retrospective analysis of 21 patients with a histological diagnosis of PSC who received ICI as first-line therapy from January 2019 to March 2022. The expression of PD-L1 was evaluated by immunohistochemistry (IHC) using the monoclonal antibody 22C3. Low and high PD-L1 expressions were defined using the tumor proportion score (TPS), with cutoffs of 1 and 50%, respectively.

Results

All eight patients had PD-L1 positivity who underwent PD-L1 expression assessment, and six patients (6/8, 75.0%) had high PD-L1 expression. Among the 21 PSC patients, seven received tislelizumab, six received camrelizumab, four received sintilimab, three received pembrolizumab, and one received durvalumab. Among them, 18 PSCs received combination therapy, whereas another three PSCs received immunotherapy alone. Out of the 21 PSC patients, 12 (57.1%) achieved a partial response (PR), and five patients had stable disease (SD) as the best response, whereas four PSCs experienced dramatic progressive disease (PD). The median progression-free survival (PFS) was 9.2 (95% CI [4.3, 14.1]) months, and the median OS was 22.8 (95% CI [4.0, 41.5]) months. Among the three treatment groups (immunotherapy alone, immunotherapy combined with anlotinib, and chemoimmunotherapy), the median PFS was 8.0, 9.4, and 9.6 months, and the median OS was 19.0, 22.8, and 30.6 months, respectively. There was no difference in PFS and OS between the three treatment regimen groups (P = 0.86 and P = 0.34, respectively) and different immunotherapies (P = 0.10 and P = 0.23, respectively). No serious adverse events (grade ≥ 3) were noted.

Conclusion

First-line immunotherapy has promising therapeutic potential in the treatment of PSC. More studies are warranted to confirm these findings.

Liquid Biopsy and the Translational Bridge from the TIME to the Clinic

Research and advancing understanding of the tumor immune microenvironment (TIME) is vital to optimize and direct more effective cancer immune therapy. Pre-clinical bench research is vital to better understand the genomic interplay of the TIME and immune therapy responsiveness. However, a vital key to effective translational cancer research is having a bridge of translation to bring that understanding from the bench to the bedside. Without that bridge, research into the TIME will lack an efficient and effective translation into the clinic and cancer treatment decision making. As a clinical oncologist, the purpose of this commentary is to emphasize the importance of researching and improving clinical utility of the bridge, as well as the TIME research itself.

PMS2 Expression With Combination of PD-L1 and TILs for Predicting Survival of Esophageal Squamous Cell Carcinoma

Background

DNA mismatch repair (MMR) deficiency (dMMR) has been recognized as an important biomarker for immunotherapy in esophageal squamous cell carcinoma (ESCC), along with programmed death ligand 1 (PD-L1) expression and/or tumor-infiltrated lymphocytes (TILs). However, in ESCC, MMR protein assessment has not been well studied at present.

Methods

A total of 484 ESCC tissues treated between 2007 and 2010, in our hospital, were enrolled. Immunohistochemical expression of MLH1, MSH2, MSH6, PMS2, and PD-L1 on tissue microarray specimens and clinicopathological features, including TILs, were analyzed retrospectively.

Results

Out of the 484 studied cases, loss of MLH1, MSH2, MSH6, and PMS2 expression were found in 6.8%, 2.1%, 8.7%, and 4.8% patients, respectively. dMMR was found in 65 patients, 37 cases involved in one MMR protein, 17 cases involved in two proteins, 7 cases involved in three proteins, and 4 cases involved in four proteins. There was no significant survival difference between pMMR (MMR-proficient) and dMMR patients (P>0.05). However, 224 patients with low PMS2 expression had better DFS and OS than 260 patients with high PMS2 expression (P=0.006 for DFS and 0.008 for OS), which was identified as an independent prognostic factor in multivariate analyses. Positive PD-L1 expression was detected in 341 (70.5%) samples. In stage I-II disease, patients with PD-L1 expression had better DFS and OS than those without PD-L1 expression(P<0.05), which was not found in stage III-IV disease. With the ITWG system, 40.1% of cases were classified as high TILs. Patients in the high-TILs group tended to have better DFS (P=0.055) and OS (P=0.070) than those in the low-TILs group and the differences were statistically significant in pMMR, high MSH6, or PMS2 expression cases (P<0.05). Also, high PMS2 expression patients with both PD-L1 expression and high TILs, had similar DFS and OS compared with low PMS2 expression patients (P>0.05), which were much better than other high PMS2 expression patients.

Conclusion

The expression level of MMR proteins could also be used as a prognostic factor in ESCC and PMS2 expression outperformed other MMR proteins for predicting survival. The combination of PD-L1 expression and TILs may lead to more efficient risk stratification of ESCC.

Predictive Markers for Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer

Immune checkpoint inhibitors (ICIs) have dramatically improved the outcomes of non-small cell lung cancer patients and have increased the possibility of long-term survival. However, few patients benefit from ICIs, and no predictive biomarkers other than tumor programmed cell death ligand 1 (PD-L1) expression have been established. Hence, the identification of biomarkers is an urgent issue. This review outlines the current understanding of predictive markers for the efficacy of ICIs, including PD-L1, tumor mutation burden, DNA mismatch repair deficiency, microsatellite instability, CD8+ tumor-infiltrating lymphocytes, human leukocyte antigen class I, tumor/specific genotype, and blood biomarkers such as peripheral T-cell phenotype, neutrophil-to-lymphocyte ratio, interferon-gamma, and interleukin-8. A tremendous number of biomarkers are in development, but individual biomarkers are insufficient. Tissue biomarkers have issues in reproducibility and accuracy because of intratumoral heterogeneity and biopsy invasiveness. Furthermore, blood biomarkers have difficulty in reflecting the tumor microenvironment and therefore tend to be less predictive for the efficacy of ICIs than tissue samples. In addition to individual biomarkers, the development of composite markers, including novel technologies such as machine learning and high-throughput analysis, may make it easier to comprehensively analyze multiple biomarkers.

Daily Practice Assessment of KRAS Status in NSCLC Patients: A New Challenge for the Thoracic Pathologist Is Right around the Corner

Simple Summary

RAS mutation is the most frequent oncogenic alteration in human cancers and KRAS is the most frequently mutated, notably in non-small cell lung carcinomas (NSCLC). Various attempts to inhibit KRAS in the past were unsuccessful in these latter tumors. However, recently, several small molecules (AMG510, MRTX849, JNJ-74699157, and LY3499446) have been developed to specifically target KRAS G12C-mutated tumors, which seems promising for patient treatment and should soon be administered in daily practice for non-squamous (NS)-NSCLC. In this context, it will be mandatory to systematically assess the KRAS status in routine clinical practice, at least in advanced NS-NSCLC, leading to new challenges for thoracic oncologists.

Abstract

KRAS mutations are among the most frequent genomic alterations identified in non-squamous non-small cell lung carcinomas (NS-NSCLC), notably in lung adenocarcinomas. In most cases, these mutations are mutually exclusive, with different genomic alterations currently known to be sensitive to therapies targeting EGFR, ALK, BRAF, ROS1, and NTRK. Recently, several promising clinical trials targeting KRAS mutations, particularly for KRAS G12C-mutated NSCLC, have established new hope for better treatment of patients. In parallel, other studies have shown that NSCLC harboring co-mutations in KRAS and STK11 or KEAP1 have demonstrated primary resistance to immune checkpoint inhibitors. Thus, the assessment of the KRAS status in advanced-stage NS-NSCLC has become essential to setting up an optimal therapeutic strategy in these patients. This stimulated the development of new algorithms for the management of NSCLC samples in pathology laboratories and conditioned reorganization of optimal health care of lung cancer patients by the thoracic pathologists. This review addresses the recent data concerning the detection of KRAS mutations in NSCLC and focuses on the new challenges facing pathologists in daily practice for KRAS status assessment.

The key to immunotherapy: how to choose better therapeutic biomarkers for patients with non-small cell lung cancer

Immunotherapy has become the standard of care for non-small cell lung cancer (NSCLC), either in combination or monotherapy. However, there are still some patients who cannot benefit from it. Immunization strategies for NSCLC are based on the expression of PD-L1 on tumor cells and TMB, and although these indicators have a certain predictive effect, their predictive performance is not good. Therefore, clinicians must make adjustments to recognize markers. This is a review article that summarized immunotherapeutic biomarkers according to the "seed-soil-environment", generalizes primary resistance to immunotherapy, and summarizes the integration of markers.

High farnesoid X receptor expression predicts favorable clinical outcomes in PD‑L1low/negative non‑small cell lung cancer patients receiving anti‑PD‑1‑based chemo‑immunotherapy

Anti-programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1)-directed immunotherapy has revolutionized the treatment of advanced non-small cell lung cancer (NSCLC). However, predictive biomarkers are still lacking, particularly in identifying PD-L1^low/negative patients who will benefit from immunotherapy. It was previously reported that farnesoid X receptor (FXR) downregulated PD-L1 expression in NSCLC, and that FXR^highPD-L1^low mouse Lewis lung carcinoma tumors showed an increased susceptibility to PD-1 blockade compared with mock tumors. At present, whether the FXR^highPD-L1^low phenotype predicts clinical response to immunotherapy in patients with NSCLC remains unclear. Herein, a retrospective study was conducted to examine the expression levels of FXR, PD-L1 and CD8⁺ T cells by immunohistochemistry in a cohort of 149 patients with NSCLC receiving anti-PD-1-based chemo-immunotherapy. The results revealed that high FXR and PD-L1 expression levels were associated with higher objective response rates (ORR) in all patients. High PD-L1 expression also indicated superior progression-free survival (PFS). Interestingly, an inverse correlation was identified between FXR and PD-L1 expression in specimens with NSCLC. Subgroup analysis revealed that high FXR expression was associated with a higher ORR, as well as longer PFS and overall survival (OS) in PD-L1^low patients. Cox multivariate analysis revealed that high FXR expression was an independent predictor for PFS and OS in PD-L1^low patients. Tumor microenvironment evaluation revealed a statistically significant decrease of infiltrating CD8⁺ T cells in FXR^high specimens with NSCLC. Overall, the present study proposed an FXR^highPD-L1^low signature as a candidate predictor of response to anti-PD-1-based chemo-immunotherapy in PD-L1^low/negative patients with NSCLC, providing evidence that could be used to broaden the patients benefitting from immunotherapy.