PD-L1 immunohistochemistry for non-small cell lung carcinoma: which strategy should be adopted?

Multifaceted roles of PD-1 in tumorigenesis: From immune checkpoint to tumor cell-intrinsic function

Programmed cell death 1 (PD-1), a key immune checkpoint receptor, has been extensively studied for its role in regulating immune responses in cancer. However, recent research has unveiled a complex and dual role for PD-1 in tumorigenesis. While PD-1 is traditionally associated with immune cells, this article explores its expression in various cancer cells and its impact on cancer progression. PD-1's functions extend beyond immune regulation, as it has been found to both promote and suppress tumor growth, depending on the cancer type. These findings have significant implications for the future of cancer treatment and our understanding of the immune response in the context of cancer. This article calls for further research into the multifaceted roles of PD-1 to optimize its therapeutic potential and improve patient outcomes in the fight against cancer.

Automated PD-L1 status prediction in lung cancer with multi-modal PET/CT fusion

Programmed death-ligand 1 (PD-L1) expressions play a crucial role in guiding therapeutic interventions such as the use of tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) in lung cancer. Conventional determination of PD-L1 status includes careful surgical or biopsied tumor specimens. These specimens are gathered through invasive procedures, representing a risk of difficulties and potential challenges in getting reliable and representative tissue samples. Using a single center cohort of 189 patients, our objective was to evaluate various fusion methods that used non-invasive computed tomography (CT) and18 F-FDG positron emission tomography (PET) images as inputs to various deep learning models to automatically predict PD-L1 in non-small cell lung cancer (NSCLC). We compared three different architectures (ResNet, DenseNet, and EfficientNet) and considered different input data (CT only, PET only, PET/CT early fusion, PET/CT late fusion without as well as with partially and fully shared weights to determine the best model performance. Models were assessed utilizing areas under the receiver operating characteristic curves (AUCs) considering their 95% confidence intervals (CI). The fusion of PET and CT images as input yielded better performance for PD-L1 classification. The different data fusion schemes systematically outperformed their individual counterparts when used as input of the various deep models. Furthermore, early fusion consistently outperformed late fusion, probably as a result of its capacity to capture more complicated patterns by merging PET and CT derived content at a lower level. When we looked more closely at the effects of weight sharing in late fusion architectures, we discovered that while it might boost model stability, it did not always result in better results. This suggests that although weight sharing could be beneficial when modality parameters are similar, the anatomical and metabolic information provided by CT and PET scans are too dissimilar to consistently lead to improved PD-L1 status predictions.

Liquid biopsy for human cancer: cancer screening, monitoring, and treatment

Currently, tumor treatment modalities such as immunotherapy and targeted therapy have more stringent requirements for obtaining tumor growth information and require more accurate and easy-to-operate tumor information detection methods. Compared with traditional tissue biopsy, liquid biopsy is a novel, minimally invasive, real-time detection tool for detecting information directly or indirectly released by tumors in human body fluids, which is more suitable for the requirements of new tumor treatment modalities. Liquid biopsy has not been widely used in clinical practice, and there are fewer reviews of related clinical applications. This review summarizes the clinical applications of liquid biopsy components (e.g., circulating tumor cells, circulating tumor DNA, extracellular vesicles, etc.) in tumorigenesis and progression. This includes the development process and detection techniques of liquid biopsies, early screening of tumors, tumor growth detection, and guiding therapeutic strategies (liquid biopsy-based personalized medicine and prediction of treatment response). Finally, the current challenges and future directions for clinical applications of liquid biopsy are proposed. In sum, this review will inspire more researchers to use liquid biopsy technology to promote the realization of individualized therapy, improve the efficacy of tumor therapy, and provide better therapeutic options for tumor patients.

Circulating T cells: a promising biomarker of anti-PD-(L)1 therapy

Anti-PD-(L)1 therapy has shown great efficacy in some patients with cancer. However, a significant proportion of patients with cancer do not respond to it. Another unmet clinical need for anti-PD-(L)1 therapy is the dynamic monitoring of treatment effects. Therefore, identifying biomarkers that can stratify potential responders before PD-(L)1 treatment and timely monitoring of the efficacy of PD-(L)1 treatment are crucial in the clinical setting. The identification of biomarkers by liquid biopsy has attracted considerable attention. Among the identified biomarkers, circulating T cells are one of the most promising because of their indispensable contribution to anti-PD-(L)1 therapy. The present review aimed to thoroughly explore the potential of circulating T cells as biomarkers of anti-PD-(L)1 therapy and its advantages and limitations.

Matched tissue and liquid biopsies for advanced non-small cell lung cancer patients A potentially indispensable complementary approach

The introduction of liquid biopsies (LB) has brought forth a number of therapeutic opportunities into the domain of thoracic oncology. Many of which have been adopted for care of patients presenting with advanced non-squamous non-small cell lung cancer (aNS-NSCLC). For example, one of the most frequent indications to perform a LB in these patients, at least in Europe, is for patients treated with tyrosine kinase inhibitors (TKIs) targeting EGFR and ALK genomic alterations when the tumor progresses. A tissue biopsy (TB) must then be taken, ideally from a site of a tumor that progresses, in particular if the LB does not permit detection of a mechanism of resistance to TKI. A LB from a patient with aNS-NSCLC is recommended before first-line therapy if no tissue and/or cytological material is accessible or if the extracted nucleic acid is insufficient in amount and/or of poor quality. At present a LB and a TB are rarely performed simultaneously before treatment and/or on tumor progression. This complementary/matched testing approach is still controversial but needs to be better evaluated to determine the true benefit to care of patients. This review provides an update on the complementarity of the LB and TB method for care of patients presenting with aNS-NSCLC.

Peripheral and tumor-infiltrating immune cells are correlated with patient outcomes in ovarian cancer

OBJECTIVE

At present, there is still a lack of reliable biomarkers for ovarian cancer (OC) to guide prognosis prediction and accurately evaluate the dominant population of immunotherapy. In recent years, the relationship between peripheral blood markers and tumor-infiltrating immune cells (TICs) with cancer has attracted much attention. However, the relationship between the survival of OC patients and intratumoral- or extratumoral-associated immune cells remains controversial.

METHODS

In this study, four machine-learning algorithms were used to predict overall survival in OC patients based on peripheral blood indicators. To further screen out immune-related gene and molecular targets, we systematically explored the correlation between TICs and OC patient survival based on The Cancer Genome Atlas database. Using the TICs score method, patients were divided into a low immune infiltrating cell group and a high immune infiltrating cell group.

RESULTS

The results showed that there was a significant statistical significance between the peripheral blood indicators and the survival prognosis of OC patients. Survival analysis showed that TICs play a crucial role in the survival of OC patients. Four core genes, CXCL9, CD79A, MS4A1, and MZB1, were identified by cross-PPI and COX regression analysis. Further analysis found that these genes were significantly associated with both TICs and survival in OC patients.

CONCLUSIONS

These results suggest that both peripheral blood markers and TICs can be used as prognostic predictors in patients with OC, and CXCL9, CD79A, MS4A1, and MZB1 may be potential therapeutic targets for OC immunotherapy.

The role of PD-1/PD-L1 and application of immune-checkpoint inhibitors in human cancers

Programmed cell death protein-1 (PD-1) is a checkpoint receptor expressed on the surface of various immune cells. PD-L1, the natural receptor for PD-1, is mainly expressed in tumor cells. Studies have indicated that PD-1 and PD-L1 are closely associated with the progression of human cancers and are promising biomarkers for cancer therapy. Moreover, the interaction of PD-1 and PD-L1 is one of the important mechanism by which human tumors generate immune escape. This article provides a review on the role of PD-L1/PD-1, mechanisms of immune response and resistance, as well as immune-related adverse events in the treatment of anti-PD-1/PD-L1 immunotherapy in human cancers. Moreover, we summarized a large number of clinical trials to successfully reveal that PD-1/PD-L1 Immune-checkpoint inhibitors have manifested promising therapeutic effects, which have been evaluated from different perspectives, including overall survival, objective effective rate and medium progression-free survival. Finally, we pointed out the current problems faced by PD-1/PD-L1 Immune-checkpoint inhibitors and its future prospects. Although PD-1/PD-L1 immune checkpoint inhibitors have been widely used in the treatment of human cancers, tough challenges still remain. Combination therapy and predictive models based on integrated biomarker determination theory may be the future directions for the application of PD-1/PD-L1 Immune-checkpoint inhibitors in treating human cancers.

PD-1/PD-L1 inhibitors in treatment-naïve, advanced non-small cell lung cancer patients with < 1% PD-L1 expression: a meta-analysis of randomized controlled trials

BACKGROUND

PD-1/PD-L1 inhibitors prolong survival in treatment-naïve, locally advanced, and metastatic non-small cell lung cancer (NSCLC) with positive PD-L1 expression (> 1%/ > 50%). Recent evidence has suggested that tumors with < 1% PD-L1 expression may also be predictive of PD-1/PD-L1 inhibiting agents.

METHODS

Systematic review and meta-analysis were conducted of randomized controlled trials (RCTs) evaluating PD-1/PD-L1 inhibitors that have assessed tumors with < 1% PD-L1 expression (negative PD-L1 expression). PD-1/PD-L1 inhibitors-chemotherapy combinations (PC) were compared with histology-selected chemotherapy with respect to overall survival (OS) and progression-free survival (PFS).

RESULTS

Twelve RCTs comprising 5410 participants (PD-1/PD-L1 inhibitors-chemotherapy: 3051; chemotherapy: 2359) met the inclusion criteria. Tumors with PD-L1 expression < 1% were evident in 38.9% of the pooled study population. A significant OS [hazard ratio (HR) 0.71 95% confidence interval (CI) 0.63-0.80, p < 0.00001] and PFS [HR 0.65 95% CI 0.58-0.72, p < 0.00001] benefit of PC was evident in tumors with negative PD-L1 expression. PD-1/PD-L1 inhibitors-chemotherapy combinations were more likely to achieve an objective response than chemotherapy [odds ratio, 1.86; 95% CI, 1.46-2.38, p < 0.00001]. Histologic subtypes and diagnostic assays did not modify the OS and PFS treatment effects for PC compared to chemotherapy.

CONCLUSION

Tumors harboring < 1% PD-L1 expression are likely to benefit from PD-1/PD-L1 inhibitor-chemotherapy regimens in advanced NSCLC.

Predicting programmed death-ligand 1 expression level in non-small cell lung cancer using a combination of peritumoral and intratumoral radiomic features on computed tomography

In this study, we investigated the possibility of predicting expression levels of programmed death-ligand 1 (PD-L1) using radiomic features of intratumoral and peritumoral tumors on computed tomography (CT) images. We retrospectively analyzed 161 patients with non-small cell lung cancer. We extracted radiomics features for intratumoral and peritumoral regions on CT images. The null importance, least absolute shrinkage, and selection operator model were used to select the optimized feature subset to build the prediction models for the PD-L1 expression level. LightGBM with five-fold cross-validation was used to construct the prediction model and evaluate the receiver operating characteristics. The corresponding area under the curve (AUC) was calculated for the training and testing cohorts. The proportion of ambiguously clustered pairs was calculated based on consensus clustering to evaluate the validity of the selected features. In addition, Radscore was calculated for the training and test cohorts. For expression level of PD-L1 above 1%, prediction models that included radiomic features from the intratumoral region and a combination of radiomic features from intratumoral and peritumoral regions yielded an AUC of 0.83 and 0.87 and 0.64 and 0.74 in the training and test cohorts, respectively. In contrast, the models above 50% prediction yielded an AUC of 0.80, 0.97, and 0.74, 0.83, respectively. The selected features were divided into two subgroups based on PD-L1 expression levels ≥ 50% or ≥ 1%. Radscore was statistically higher for subgroup one than subgroup two when radiomic features for intratumoral and peritumoral regions were combined. We constructed a predictive model for PD-L1 expression level using CT images. The model using a combination of intratumoral and peritumoral radiomic features had a higher accuracy than the model with only intratumoral radiomic features.

EGFR Status Assessment for Better Care of Early Stage Non-Small Cell Lung Carcinoma: What Is Changing in the Daily Practice of Pathologists?

The recent emergence of novel neoadjuvant and/or adjuvant therapies for early stage (I-IIIA) non-small cell lung carcinoma (NSCLC), mainly tyrosine kinase inhibitors (TKIs) targeting EGFR mutations and immunotherapy or chemo-immunotherapy, has suddenly required the evaluation of biomarkers predictive of the efficacy of different treatments in these patients. Currently, the choice of one or another of these treatments mainly depends on the results of immunohistochemistry for PD-L1 and of the status of EGFR and ALK. This new development has led to the setup of different analyses for clinical and molecular pathology laboratories, which have had to rapidly integrate a number of new challenges into daily practice and to establish new organization for decision making. This review outlines the impact of the management of biological samples in laboratories and discusses perspectives for pathologists within the framework of EGFR TKIs in early stage NSCLC.

First-in-human evaluation of a PD-L1-binding peptide radiotracer in non-small cell lung cancer patients with PET

⁶⁸Ga-NOTA-WL12 is a peptide-based PET imaging agent. We conducted a first-in-human study of ⁶⁸Ga-NOTA-WL12 for PET to study the in vivo biodistribution, metabolism, radiation dosimetry, safety, and potential for quantifying programmed death ligand-1 (PD-L1) expression levels in patients with advanced non–small cell lung cancer (NSCLC). Methods: In vitro assessment of the PD-L1 expression and cellular uptake of ⁶⁸Ga-NOTA-WL12 was performed, followed by in vivo evaluation of ⁶⁸Ga-NOTA-WL12 uptake in mouse models with tumors. Nine patients with NSCLC with lesions expressing PD-L1 were enrolled and monitored for adverse events during the study. ⁶⁸Ga-NOTA-WL12 and paired ¹⁸F-FDG PET/CT imaging were performed. Uptake (SUV, SUL [SUV_lean], and kBq/mL) values of tumors and normal organs were obtained. Radiopharmaceutical biodistribution, radiation dosimetry, and the relationship of tumor uptake to PD-L1 expression were evaluated. Follow-up ¹⁸F-FDG PET/CT was performed in patients who had undergone treatment with a combination of pembrolizumab with chemotherapy. Results:⁶⁸Ga-NOTA-WL12 exhibited PD-L1–specific uptake in vitro and in PD-L1–positive tumors in vivo. ⁶⁸Ga-NOTA-WL12 PET imaging proved safe with acceptable radiation dosimetry. Physiologic tracer uptake was mainly visible in the liver, spleen, small intestine, and kidney. Tumors were clearly visible, particularly in the lungs, with a tumor-to-lung ratio of 4.45 ± 1.89 at 1 h. One hour was a suitable time point for image acquisition because no significant differences were noted in tumor-to-background ratios between 1 and 2 h. A strong, positive correlation was found between tumor uptake (SUV_peak) and PD-L1 immunohistochemistry results (r = 0.9349; P = 0.002). ⁶⁸Ga-NOTA-WL12 and ¹⁸F-FDG PET studies suggest that PD-L1 PET before therapy may indicate the therapeutic efficacy of pembrolizumab plus chemotherapy combination treatment. Conclusion: Our first-in-human findings demonstrate the safety and feasibility of ⁶⁸Ga-NOTA-WL12 for noninvasive, in vivo detection of tumor PD-L1 expression levels, indicating potential benefits for clinical PD-L1 therapy.

Liquid biopsy in non-small cell lung cancer-current status and future outlook-a narrative review

Lung cancer ranks first as the cause of cancer-associated deaths gobally. The American Cancer Society estimates for 228,820 new cases and 135,720 deaths from lung cancer in the United States for the year 2020. Targeted treatment options have rapidly emerged for non-small cell lung cancer (NSCLC) within the past decade. Screening for molecular aberrations is mainly done by tissue biopsy. However, in some cases a biopsy is not possible, or patients do not consent to it. Hence, liquid biopsy remains the only option. Relevant data about the topic of liquid biopsy, with a special focus on NSCLC, was obtained via a PubMed search. We included mainly literature published from 2010 onwards, omitting older studies whenever possible. With this review of the literature, we give an overview of different liquid biopsy approaches, as well as their respective advantages and disadvantages. We have reviewed the assessment of epidermal growth factor receptor (EGFR) mutation status in particular, and go into detail with current use of liquid biopsy in everyday clinical practice. Today, liquid biopsy is still infrequently used, depending on the treatment center, but popularity is steadily increasing. Various different approaches are already available, but costs and level of sensitivity significantly differ between techniques. By using liquid biopsy more widely in selected patients, complication rates can be reduced, and constant disease monitoring is made considerably easier.

The progress and challenge of anti-PD-1/PD-L1 immunotherapy in treating non-small cell lung cancer

The use of programmed cell-death protein 1 (PD-1)/programmed cell-death ligand 1 (PD-L1) inhibitors is the standard therapy for the first-line or second-line treatment of patients with non-small-cell lung cancer (NSCLC). In contrast to current traditional treatments such as chemotherapy or radiotherapy, anti-PD-1 and anti-PD-L1 treatments can directly attenuate tumour-mediated exhaustion and effectively modulate the host anti-tumour immune response in vivo. In addition, compared with traditional therapy, PD-1/PD-L1 inhibitor monotherapy can significantly prolong survival without obvious side effects in the treatment of advanced NSCLC. Ideally, several biomarkers could be used to monitor the safety and effectiveness of anti-PD-1 and anti-PD-L1 treatments; however, the current lack of optimal prognostic markers remains a widespread limitation and challenge for further clinical applications, as does the possibility of immune-related adverse events and drug resistance. In this review, we aimed to summarise the latest progress in anti-PD-1/anti-PD-L1 treatment of advanced NSCLC, worldwide, including in China. An exploration of underlying biomarker identification and future challenges will be discussed in this article to facilitate translational studies in cancer immunotherapy.

Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images

Rationale: This study aimed to use computed tomography (CT) images to assess PD-L1 expression in non-small cell lung cancer (NSCLC) and predict response to immunotherapy. Methods: We retrospectively analyzed a PD-L1 expression dataset that consisted of 939 consecutive stage IIIB-IV NSCLC patients with pretreatment CT images. A deep convolutional neural network was trained and optimized with CT images from the training cohort (n = 750) and validation cohort (n = 93) to obtain a PD-L1 expression signature (PD-L1ES), which was evaluated using the test cohort (n = 96). Finally, a separate immunotherapy cohort (n = 94) was used to assess the prognostic value of PD-L1ES with respect to clinical outcome. Results: PD-L1ES was able to predict high PD-L1 expression (PD-L1 ≥ 50%) with areas under the receiver operating characteristic curve (AUC) of 0.78 (95% confidence interval (CI): 0.75~0.80), 0.71 (95% CI: 0.59~0.81), and 0.76 (95% CI: 0.66~0.85) in the training, validation, and test cohorts, respectively. In patients treated with anti-PD-1 antibody, low PD-L1ES was associated with improved progression-free survival (PFS) (median PFS 363 days in low score group vs 183 days in high score group; hazard ratio [HR]: 2.57, 95% CI: 1.22~5.44; P = 0.010). Additionally, when PD-L1ES was combined with a clinical model that was trained using age, sex, smoking history and family history of malignancy, the response to immunotherapy could be better predicted compared to either PD-L1ES or the clinical model alone. Conclusions: The deep learning model provides a noninvasive method to predict high PD-L1 expression of NSCLC and to infer clinical outcomes in response to immunotherapy. Additionally, this deep learning model combined with clinical models demonstrated improved stratification capabilities.

From biomarkers to therapeutic targets: the promise of PD-L1 in thyroid autoimmunity and cancer

The programmed cell death-1/programmed cell death ligand-1 (PD-1/PD-L1) immune checkpoint proteins hold promise as diagnostic, prognostic, and therapeutic targets for precision oncology. By restoring antitumor T cell surveillance, the high degree of effectiveness of the immune checkpoint inhibitors (ICIs) has revolutionized cancer treatment. However, the majority of patients (65-80 %) treated with ICIs experience significant side effects, called immune-related adverse events (irAEs), resulting in autoimmune damage to various organs. Therefore, broadening the clinical applicability of these treatments to all cancer types requires an improved understanding of the mechanisms linking cancer immune evasion and autoimmunity. The thyroid is the endocrine gland the most frequently involved in autoimmunity and cancer, the growing incidence of which is raising serious public health issues worldwide. In addition, the risk of developing thyroid cancer is increased in patients with autoimmune thyroid disease and thyroid dysfunction is one of the most common irAEs, especially with PD‑1/PD-L1 blockade. Therefore, we chose the thyroid as a model for the study of the link between autoimmunity, irAEs, and cancer. We provide an update into the current knowledge of the PD‑1/PD-L1 axis and discuss the growing interest of this axis in the diagnosis, prognosis, and management of thyroid diseases within the context of autoimmunity and cancer, while embracing personalized medicine.

PD-1/PD-L1 Blockade Therapy in Advanced Non-Small-Cell Lung Cancer: Current Status and Future Directions

This article summarizes the latest clinical applications of PD‐1/PD‐L1 blockade therapy in advanced non‐small cell lung cancer (NSCLC) worldwide and in China, reporting the bottlenecks related to the use of this therapy in clinic. An exploration of the underlying mechanism of PD‐1/PD‐L1 blockade therapy and biomarker identification will maximize the application of immune checkpoint inhibitors in advanced NSCLC and facilitate bedside‐to‐bench studies in cancer immunotherapy.

The use of immune checkpoint inhibitors (ICIs) has become one of the most promising approaches in the field of cancer therapy. Unlike the current therapies that target tumor cells, such as chemotherapy, radiotherapy, or targeted therapy, ICIs directly restore the exhausted host antitumor immune responses mediated by the tumors. Among multiple immune modulators identified, the programmed cell death protein 1 (PD‐1)/programmed cell death protein ligand 1 (PD‐L1) axis leading to the exhaustion of T‐cell immunity in chronic infections and tumors has been widely investigated. Therefore, blocking antibodies targeting PD‐1 or PD‐L1 have been developed and approved for the treatment of various advanced cancers, including non‐small‐cell lung cancer (NSCLC), making them the most successful ICIs. Compared with chemotherapy or radiotherapy, PD‐1/PD‐L1 blockade therapy significantly improves the durable response rate and prolongs long‐term survival with limited adverse effects in both monotherapy and combination therapy for advanced NSCLC. However, extensive challenges exist for further clinical applications, such as a small fraction of benefit population, primary and acquired resistance, the lack of predictive and prognostic biomarkers, and treatment‐related adverse effects. In this article, we summarize the latest clinical applications of PD‐1/PD‐L1 blockade therapy in advanced NSCLC worldwide, as well as in China, and discuss the bottlenecks related to the use of this therapy in clinical practice. An exploration of the underlying mechanism of PD‐1/PD‐L1 blockade therapy and biomarker identification will maximize the application of ICIs in advanced NSCLC and facilitate bedside‐to‐bench studies in cancer immunotherapy as well.

Implications for Practice.

Immune checkpoint inhibitors (ICIs) targeting programmed cell death protein 1 (PD‐1) and programmed cell death protein ligand 1 (PD‐L1) display apparent benefits for the treatment of advanced non‐small‐cell lung cancer (NSCLC). However, the clinical applications of these therapies are challenged by the limited benefit population with additional high economic burden and adverse events. This review discusses the bottlenecks of ICI therapy in clinical practice and provides appropriate guidance in the development of predictive biomarkers, the establishment of the criteria for combining PD‐1/PD‐L1 blockade therapy with the existing therapies, and the management of adverse events observed both in monotherapy and combination therapy, which will help maximize the applications of ICIs in advanced NSCLC.

Peripheral blood immune cell-based biomarkers in anti-PD-1/PD-L1 therapy

Immune checkpoint blockade targeting PD-1 and PD-L1 has resulted in unprecedented clinical benefit for cancer patients. Anti-PD-1/PD-L1 therapy has become the standard treatment for diverse cancer types as monotherapy or in combination with other anti-cancer therapies, and its indications are expanding. However, many patients do not benefit from anti-PD-1/PD-L1 therapy due to primary and/or acquired resistance, which is a major obstacle to broadening the clinical applicability of anti-PD-1/PD-L1 therapy. In addition, hyperprogressive disease, an acceleration of tumor growth following anti-PD-1/PD-L1 therapy, has been proposed as a new response pattern associated with deleterious prognosis. Anti-PD-1/PD-L1 therapy can also cause a unique pattern of adverse events termed immune-related adverse events, sometimes leading to treatment discontinuation and fatal outcomes. Investigations have been carried out to predict and monitor treatment outcomes using peripheral blood as an alternative to tissue biopsy. This review summarizes recent studies utilizing peripheral blood immune cells to predict various outcomes in cancer patients treated with anti-PD-1/PD-L1 therapy.

Liquid biopsy in the era of immuno-oncology: is it ready for prime-time use for cancer patients?

The emergence of immunotherapy in oncology requires the discovery, validation and subsequent adoption of robust, sensitive and specific predictive and prognostic biomarkers for daily practice. Until now, anti-PD-L1 immunohistochemistry (IHC) on tissue sections has been the only validated companion diagnostic test for first-line immunotherapy for advanced and metastatic cancer, notably non-small-cell lung cancer (NSCLC). However, detection of this biomarker presents limitations that have stimulated the development of other biomarkers and other approaches. Within this context, the use of a liquid biopsy (LB) could provide an important complementary or alternative added value to PD-L1 IHC. In this review, we discuss how LBs have been used in the field of immuno-oncology (I-O) to predict response, relapse or adverse advents for patients undergoing immune-checkpoint inhibitor (ICI) therapy (anti-PD-1/PD-L1 and CTLA-4) and we highlight recent developments. Circulating tumor cells (CTCs), cell-free DNA (cfDNA), proteins and cytokines detected in plasma as well as circulating T-lymphocytes are discussed as potential sources for developing new I-O biomarkers. The quantification of cfDNA as a predictive biomarker, as well as its sequencing for the determination of tumor mutational burden, is already well advanced. Additionally, the quantification of PD-L1 from CTCs, bound on exosomes or free in plasma, as well as the determination of cytokines, are also being actively investigated with promising results having recently been published. Lastly, analysis of T-lymphocytes, especially by analyzing the T-cell receptor, has recently emerged as a valuable biomarker that might become relevant for the prediction of response to ICIs. While LBs have not yet been implemented in routine I-O clinical practice, recent promising data and rapidly advancing technologies indicate that this approach has the potential to soon personalize the clinical management of cancer patients receiving ICIs.

[Thoracic oncology and tumor mutational burden: Towards new challenges for the pathologist?]

Among the different promising predictive biomarkers in immuno-oncology, the tumor mutational burden (TMB) may soon impose itself in clinical routine practice, in association with PD-L1 immunohistochemistry testing. However, the TMB is used currently in clinical trials only, in particular in the thoracic oncology field. If this biomarker becomes mandatory in the near future, the pathologist will have to respond to new challenges in tight collaboration with the activity of molecular pathology platforms. Given the high incidence of lung cancer in France, this new development could have a strong impact on the daily life of the laboratories. This review addresses the different challenges which could be soon proposed to the laboratories and the pathologists due to the use of TMB assays on a daily practice.

Deciphering Microenvironment of NSCLC based on CD8+ TIL Density and PD-1/PD-L1 Expression

Purpose: To determine whether distinct tissue immune microenvironments differentially impact on clinical outcome in non-small cell lung cancer (NSCLC), an extended analysis of PD-1/PD-L1 and Tumor Infiltrating Lymphocytes (TILs) was performed.

Materials and Methods: 1016 NSCLC mRNA-sequence samples from The Genome Data Analysis Center (TCGA) and 275 NSCLC mRNA-microarray samples from Gene Expression Omnibus (GEO) were included as testing cohort and validation cohort respectively. Enrichment scores of CD8+ T cells' metagene were used for quantifying its infiltrating density. Based on the median values of CD8+ T cell density and PD-1/PD-L1 mRNA expression, the samples were classified into four Tumor Immune Microenvironment types (TIMTs). Overall survival, as well as clinicopathological features, mutational profiles, mismatch repair score etc. were compared across the four types.

Results: Neither PD-1 expression nor PD-L1 expression was associated with outcome in the overall NSCLC. Classification of TIMT based on PD-1/PD-L1 and CD8+ TIL could efficiently classify patients of different survival in ADC but not SCC, with the best overall survival achieved in TIMT3 (high CD8+ TIL and low PD-1/PD-L1), whereas TIMT2 (low CD8+ TIL and high PD-1/PD-L1) manifested the worst outcome. TIMT classification based on PD-1/ CD8+ TIL could better stratify patient of different prognosis than PD-L1/ CD8+ TIL based classification. EGFR wide type and IFNγ overexpression were associated with TIMT4 (high PD-1/PD-L1 and high CD8+ TIL), whereas tumor mutational burden (TMB) manifested no significant difference across four TIMTs.

Conclusion: The classification of tumors into four microenvironment subtypes based on PD-1/PD-L1 status and CD8+ TIL is an appropriate approach to stratify patients of different clinical outcome and better guide the practical use of immunotherapy.

Tumor mutational burden assessment as a predictive biomarker for immunotherapy in lung cancer patients: getting ready for prime-time or not?

The emergence of immunotherapy as a first- or second-line of treatment has revolutionized the therapeutic management of lung cancer patients. However, not all lung cancer patients receive the same benefit from this treatment, leading to limitations in the number of patients who can receive anti-PD-1/PD-L1 checkpoint inhibitors because some secondary toxicity has been associated with immunotherapy, and because some patients would benefit more from chemotherapy. In this context, the selection of patients is currently based on PD-L1 immunohistochemistry (IHC), specifically on the percentage of PD-L1 positive tumor cells. To date, this is the only validated biomarker that is used as a companion diagnostic test for immunotherapy in non-small cell carcinoma lung (NSCLC) patients. However, this biomarker is not sufficiently robust and demonstrates many challenges. For example, some patients with more than 50% PD-L1 positive tumor cells are non-responders to anti-PD-1/PD-L1 treatment, while conversely, other patients with no PD-L1 positive tumor cells are good responders. The tumor mutation burden (TMB) or tumor mutation load (TML) emerged recently as a new predictive biomarker for immunotherapy response in NSCLC. However, this biomarker needs to be validated for routine clinical use and shares similar constraints with the PD-L1 IHC biomarker. PD-L1 IHC and TMB are currently the two best predictive biomarkers that could soon be used to systematically inform treatment decisions in advanced or metastatic NSCLC patients. The aim of this review is to consider the possible integration of TMB testing in daily practice through a pros- and cons-debate, and to establish sample quality-dependent algorithms and the main current constraints for laboratories considering TMB assessments.

Update on Immunohistochemistry for the Diagnosis of Lung Cancer

Immunohistochemistry is a widely available technique that is less challenging and can provide clinically meaningful results quickly and cost-efficiently in comparison with other techniques. In addition, immunohistochemistry allows for the evaluation of cellular localization of proteins in the context of tumor structure. In an era of precision medicine, pathologists are required to classify lung cancer into specific subtypes and assess biomarkers relevant to molecular-targeted therapies. This review summarizes the hot topics of immunohistochemistry in lung cancer, including (i) adenocarcinoma vs squamous cell carcinoma; (ii) neuroendocrine markers; (iii) ALK, ROS1, and EGFR; (iv) PD-L1 (CD274); (v) lung carcinoma vs malignant mesothelioma; and (vi) NUT carcinoma. Major pitfalls in evaluating immunohistochemical results are also described.

Any Place for Immunohistochemistry within the Predictive Biomarkers of Treatment in Lung Cancer Patients?

The identification of certain genomic alterations (EGFR, ALK, ROS1, BRAF) or immunological markers (PD-L1) in tissues or cells has led to targeted treatment for patients presenting with late stage or metastatic lung cancer. These biomarkers can be detected by immunohistochemistry (IHC) and/or by molecular biology (MB) techniques. These approaches are often complementary but depending on, the quantity and quality of the biological material, the urgency to get the results, the access to technological platforms, the financial resources and the expertise of the team, the choice of the approach can be questioned. The possibility of detecting simultaneously several molecular targets, and of analyzing the degree of tumor mutation burden and of the micro-satellite instability, as well as the recent requirement to quantify the expression of PD-L1 in tumor cells, has led to case by case development of algorithms and international recommendations, which depend on the quality and quantity of biological samples. This review will highlight the different predictive biomarkers detected by IHC for treatment of lung cancer as well as the present advantages and limitations of this approach. A number of perspectives will be considered.