Translational Biomarkers and Rationale Strategies to Overcome Resistance to Immune Checkpoint Inhibitors in Solid Tumors

Harnessing Spatiotemporal-Specific Tumorous Exosome Dynamics: Ultra-Sensitive Lanthanide Luminescence Detection Strategy Enabled by Exosomal Membrane Engineering for Melanoma Immunotherapy Monitoring

Focused on the newly secreted tumorous exosomes during melanoma immunotherapy, this work has pioneered an ultra-sensitive spatiotemporal-specific exosome detection strategy, leveraging advanced exosomal membrane engineering techniques. The proposed strategy harnesses the power of amplified lanthanide luminescence signals on these exosomes, enabling precise and real-time monitoring of the efficacy of melanoma immunotherapy. The methodology comprises two pivotal steps. Initially, Ac4ManNAz-associated metabolic labeling is employed to evolve azide groups onto the membranes of newly secreted exosomes with remarkable selectivity. These azide groups serve as versatile clickable artificial tags, enabling the precise identification of melanoma exosomes emerging during immunotherapy. Subsequently, lanthanide-nanoparticle-functionalized polymer chains are controllably grafted onto the exosome surfaces through click chemistry and in situ Fenton-RAFT polymerization, serving as robust signal amplifiers. When integrated with time-resolved fluorescence detection, this strategy yields detection signals with an exceptionally high signal-to-noise ratio, enabling ultra-sensitive detection of PD-L1 antigen expression levels on the spatiotemporal-specific exosomes. The detection strategy boasts a wide linear concentration range spanning from 1.7 × 104 to 1.7 × 109 particles/mL, with a remarkable theoretical detection limit of 1.28 × 103 particles/mL. The remarkable enhancements in detection sensitivity and accuracy facilitate the evaluation of the efficacy of immunotherapeutic interventions in the mouse B16 melanoma model, notably revealing a substantial disparity in PD-L1 levels between immunotherapy-treated and untreated groups (P < 0.01) and further emphasizing the cumulative therapeutic effect that intensifies with repeated treatments (P < 0.001).

Immune-Cell-Derived Exosomes as a Potential Novel Tool to Investigate Immune Responsiveness in SCLC Patients: A Proof-of-Concept Study

Small cell lung cancer (SCLC) is a highly invasive and rapidly proliferating lung tumor subtype. Most patients respond well to a combination of platinum-based chemotherapy and PD-1/PDL-1 inhibitors. Unfortunately, not all patients benefit from this treatment regimen, and few alternative therapies are available. In this scenario, the identification of new biomarkers and differential therapeutic strategies to improve tumor response becomes urgent. Here, we investigated the role of exosomes (EXs) released from the peripheral blood mononuclear cells (PBMCs) of SCLC patients in mediating the functional crosstalk between the immune system and tumors in response to treatments. In this study, we showed that PBMC-EXs from SCLC patients with different responses to chemoimmunotherapy showed different levels of immune (STING and MAVS) and EMT (Snail and c-Myc) markers. We demonstrated that PBMC-EXs derived from best responder (BR) patients were able to induce a significant increase in apoptosis in SCLC cell lines in vitro compared to PBMC-EXs derived from non-responder (NR) SCLC patients. PBMC-EXs were able to affect cell viability and modulate apoptotic markers, DNA damage and the replication stress pathway, as well as the occurrence of EMT. Our work provides proof of concept that PBMC-EXs can be used as a tool to study the crosstalk between cancer cells and immune cells and that PBMC-EXs exhibit an in vitro ability to promote cancer cell death and reduce tumor aggressiveness.

Defining intra-tumoral and systemic immune biomarkers for locally advanced head-and-neck cancer - detailed protocol of a prospective, observatory multicenter trial (ImmunBioKHT) and first results of the immunophenotyping of the patients' peripheral blood

The approval and effectiveness of immune checkpoint inhibitors in head-and-neck squamous cell carcinoma (HNSCC) highlights the role of the immune system in this tumor entity. HNSCCs not only interacts with the immune system in the tumor tissue, but also induce systemic effects that may be additionally influenced by further factors such as the microbiome. Nonetheless, reliable immunological biomarkers that predict treatment response and outcome in HNSCC patients are lacking. The currently available biomarkers are mainly limited to analyses from tumor biopsies, while biomarkers from liquid biopsies, such as peripheral blood are not well-established. Thus, the here presented trial aims to identify interactions of intra-tumoral and systemic immune responses and to define prognostic immune signatures. Consequently, not only samples from the tumor tissue, but also from peripheral blood and the microbiome will be studied/are being evaluated and correlated with the clinical outcome. In this prospective, multi-center trial, 1000 HNSCC patients and 100 patients in the control cohort with non-tumor head-and-neck surgery will be enrolled. The local immune status from of the tumor and the microbiome will be sampled before treatment. In addition, the systemic immune status from peripheral blood will be analyzed before and after surgery and after the adjuvant and definitive radio-chemotherapy (RCT). Clinical baseline characteristics and outcome will additionally be collected. Data mining and modelling approaches will finally be applied to identify interactions of local and systemic immune parameters and to define prognostic immune signatures based on the evaluated immune markers. Approval from the institutional review board of the Friedrich-Alexander-Universität Erlangen-Nürnberg was granted in December 2021 (application number 21-440-B). By now, 150 patients have been enrolled in the intervention cohort. The results will be disseminated to the scientific audience and the general public via presentations at conferences and publication in peer-reviewed journals.

Blood Immune Cells as Biomarkers in Long-Term Surviving Patients with Advanced Non-Small-Cell Lung Cancer Undergoing a Combined Immune/Chemotherapy

An important challenge remains in identifying the baseline characteristics of cancer patients who will mostly benefit from immune checkpoint inhibitor (ICI) therapies. Furthermore, biomarkers could help in the choice of an optimal therapy duration after a primary therapy response. In this pilot study, the time courses of four different immune cell parameters were followed in 12 patients with advanced non-small-cell lung cancer (NSCLC) undergoing ICI therapy combined with chemotherapy and surviving at least 12 months. Blood was collected at the time point of the first and third antibody administration, as well as after 12 months of patients' survival. Using multi-color flow cytometry, two suppressive markers (neutrophil/lymphocyte ratio (NLR) and the frequency of circulating HLA-DRlow monocytes), as well as two markers of an ongoing immune response (6-Sulfo LacNAc (slan)+ non-classical monocytes and dendritic cell (DC) subtypes), were determined. In most of those who survived > 12 months, a low NLR and a low number of HLA-DRlow monocytes combined with clearly detectable numbers of slan+ non-classical monocytes and of DC subtypes were seen. Two of the patients had an increase in the suppressive markers paired with a decrease in slan+ non-classical monocytes and in DC subtypes, which, in at least one patient, was the correlate of an ongoing clinical progression. Our results implicate that the NLR, specific subtypes of monocytes, and the number of blood DCs might be useful predictive biomarkers for cancer patients during long-term treatment with ICI/chemotherapy.

Dynamic evaluation of blood immune cells predictive of response to immune checkpoint inhibitors in NSCLC by multicolor spectrum flow cytometry

Introduction

Immune checkpoint inhibitors (ICIs) only benefit a subset of cancer patients, underlining the need for predictive biomarkers for patient selection. Given the limitations of tumor tissue availability, flow cytometry of peripheral blood mononuclear cells (PBMCs) is considered a noninvasive method for immune monitoring. This study explores the use of spectrum flow cytometry, which allows a more comprehensive analysis of a greater number of markers using fewer immune cells, to identify potential blood immune biomarkers and monitor ICI treatment in non-small-cell lung cancer (NSCLC) patients.

Methods

PBMCs were collected from 14 non-small-cell lung cancer (NSCLC) patients before and after ICI treatment and 4 healthy human donors. Using spectrum flow cytometry, 24 immune cell markers were simultaneously monitored using only 1 million PBMCs. The results were also compared with those from clinical flow cytometry and bulk RNA sequencing analysis.

Results

Our findings showed that the measurement of CD4+ and CD8+ T cells by spectrum flow cytometry matched well with those by clinical flow cytometry (Pearson R ranging from 0.75 to 0.95) and bulk RNA sequencing analysis (R=0.80, P=1.3 x 10-4). A lower frequency of CD4+ central memory cells before treatment was associated with a longer median progression-free survival (PFS) [Not reached (NR) vs. 5 months; hazard ratio (HR)=8.1, 95% confidence interval (CI) 1.5-42, P=0.01]. A higher frequency of CD4-CD8- double-negative (DN) T cells was associated with a longer PFS (NR vs. 4.45 months; HR=11.1, 95% CI 2.2-55.0, P=0.003). ICIs significantly changed the frequency of cytotoxic CD8+PD1+ T cells, DN T cells, CD16+CD56dim and CD16+CD56- natural killer (NK) cells, and CD14+HLDRhigh and CD11c+HLADR + monocytes. Of these immune cell subtypes, an increase in the frequency of CD16+CD56dim NK cells and CD14+HLADRhigh monocytes after treatment compared to before treatment were associated with a longer PFS (NR vs. 5 months, HR=5.4, 95% CI 1.1-25.7, P=0.03; 7.8 vs. 3.8 months, HR=5.7, 95% CI 169 1.0-31.7, P=0.04), respectively.

Conclusion

Our preliminary findings suggest that the use of multicolor spectrum flow cytometry helps identify potential blood immune biomarkers for ICI treatment, which warrants further validation.

Emerging precision neoadjuvant systemic therapy for patients with resectable non-small cell lung cancer: current status and perspectives

Over the past decade, targeted therapy for oncogene-driven NSCLC and immune checkpoint inhibitors for non-oncogene-driven NSCLC, respectively, have greatly improved the survival and quality of life for patients with unresectable NSCLC. Increasingly, these biomarker-guided systemic therapies given before or after surgery have been used in patients with early-stage NSCLC. In March 2022, the US FDA granted the approval of neoadjuvant nivolumab and chemotherapy for patients with stage IB-IIIA NSCLC. Several phase II/III trials are evaluating the clinical efficacy of various neoadjuvant immune checkpoint inhibitor combinations for non-oncogene-driven NSCLC and neoadjuvant molecular targeted therapies for oncogene-driven NSCLC, respectively. However, clinical application of precision neoadjuvant treatment requires a paradigm shift in the biomarker testing and multidisciplinary collaboration at the diagnosis of early-stage NSCLC. In this comprehensive review, we summarize the current diagnosis and treatment landscape, recent advances, new challenges in biomarker testing and endpoint selections, practical considerations for a timely multidisciplinary collaboration at diagnosis, and perspectives in emerging neoadjuvant precision systemic therapy for patients with resectable, early-stage NSCLC. These biomarker-guided neoadjuvant therapies hold the promise to improve surgical and pathological outcomes, reduce systemic recurrences, guide postoperative therapy, and improve cure rates in patients with resectable NSCLC.

Monitoring Blood Immune Cells in Patients with Advanced Small Cell Lung Cancer Undergoing a Combined Immune Checkpoint Inhibitor/Chemotherapy

In this exploratory prospective observational study on 40 small cell lung cancer (SCLC) patients treated with a combination of chemotherapy and immune checkpoint inhibitors, blood immune cells were characterized by multi-color flow cytometry at the baseline and at the third therapy cycle. The numbers of neutrophils and of T-, B-, and NK cells, as well as the frequency of HLA-DR^low monocytes, 6-SulfoLacNAc (slan)+ non-classical monocytes and circulating dendritic cell (DC) subtypes were determined. The prognostic value of the parameters was evaluated by the patient's survival analysis with overall survival (OS) as the primary endpoint. In addition, blood cell parameters from SCLC patients were compared to those from non-SCLC (NSCLC). The global median OS of patients was 10.4 ± 1.1 months. Disease progression (15% of patients) correlated with a higher baseline neutrophil/lymphocyte ratio (NLR), more HLA-DR^low monocytes, and lower NK cell and DC numbers. The risk factors for poor OS were the presence of brain/liver metastases, a baseline NLR ≥ 6.1, HLA-DR^low monocytes ≥ 21% of monocytes, slan+ non-classical monocytes < 0.12%, and/or CD1c+ myeloid DC < 0.05% of leukocytes. Lymphocytic subpopulations did not correlate with OS. When comparing biomarkers in SCLC versus NSCLC, SCLC had a higher frequency of brain/liver metastases, a higher NLR, the lowest DC frequencies, and lower NK cell numbers. Brain/liver metastases had a substantial impact on the survival of SCLC patients. At the baseline, 45% of SCLC patients, but only 24% of NSCLC patients, had between three and five risk factors. A high basal NLR, a high frequency of HLA-DR^low monocytes, and low levels of slan+ non-classical monocytes were associated with poor survival in all lung cancer histotypes. Thus, the blood immune cell signature might contribute to a better prediction of SCLC patient outcomes and may uncover the pathophysiological peculiarities of this tumor entity.

Hospitalized cancer patients with comorbidities and low lymphocyte counts had poor clinical outcomes to immune checkpoint inhibitors

Background

Immune checkpoint inhibitor (ICI) therapy has improved survivals with a favorable toxicity profile in a variety of cancer patients. We hypothesized that hospitalized cancer patients who have acute or chronic comorbidities may have suppressed immune systems and poor clinical outcomes to ICIs. The objective of this study was to explore clinical outcomes and predictive factors of hospitalized cancer patients who received ICI therapy at an NCI-designated Comprehensive Cancer Center.

Methods

A retrospective review of electronic medical records was conducted for adult cancer patients who received an FDA-approved ICI during admission from 08/2016 to 01/2022. For each patient we extracted demographics, cancer histology, comorbidities, reasons for hospitalization, ICI administered, time from treatment to discharge, time from treatment to progression or death, and complete blood counts. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared using the log-rank test. The 95% confidence interval for survival was calculated using the exact binomial distribution. Statistical significance was defined as 2-sided p<0.05.

Results

Of 37 patients identified, 2 were excluded due to lack of complete blood counts on admission. Average hospital stay was 24.2 (95% CI 16.5, 31.9) days. Ten (27.0%) patients died during the same hospitalization as treatment. Of those who followed up, 22 (59.5%) died within 90 days of inpatient therapy. The median PFS was 0.86 (95% CI 0.43, 1.74) months and median OS was 1.55 (95% CI 0.76, 3.72) months. Patients with ≥3 comorbidities had poorer PFS (2.4 vs. 0.4 months; p=0.0029) and OS (5.5 vs. 0.6 months; p=0.0006). Pre-treatment absolute lymphocyte counts (ALC) <600 cells/µL were associated with poor PFS (0.33 vs. 1.35 months; p=0.0053) and poor OS (0.33 vs. 2.34 months; p=0.0236). Pre-treatment derived neutrophil to lymphocyte ratio (dNLR) <4 was associated with good median PFS (1.6 vs. 0.4 months; p=0.0157) and OS (2.8 vs. 0.9 months; p=0.0375).

Conclusions

Administration of ICI therapy was associated with poor clinical outcomes and high rates of both inpatient mortality and 90-day mortality after inpatient ICI therapy. The presence of ≥3 comorbidities, ALC <600/μL, or dNLR >4 in hospitalized patients was associated with poor survival outcomes.

Development of a Simple and Objective Prognostication Model for Patients with Advanced Solid Malignant Tumors Treated with Immune Checkpoint Inhibitors: A Pan-Cancer Analysis

BACKGROUND

Systemic therapy using immune checkpoint inhibitors (ICIs) has recently become prevalent in the treatment of patients with various types of advanced cancers; however, difficulties are still associated with predicting the outcomes of patients receiving ICIs due to heterogenous responses to these agents.

OBJECTIVE

To develop a prognostic model for advanced cancer patients treated with ICIs.

PATIENTS AND METHODS

This study retrospectively analyzed the impact of clinical parameters on overall survival (OS) in 329 patients with several advanced solid malignant tumors who received systemic therapy using ICIs.

RESULTS

The primary tumors of 329 patients were as follows: lung (n = 89), kidney (n = 70), urinary tract (n = 52), skin (n = 50), stomach (n = 30), esophagus (n = 21), and head and neck (n = 17). Median OS after the introduction of ICIs was 17.3 months. Among the factors that correlated with OS in a univariate analysis, body mass index, C-reactive protein, hemoglobin, lymphocytes, and platelets were identified as independent predictors of OS in a multivariate analysis. Following the classification of patients into 3 groups based on positive numbers of these independent risk factors, median OS was not reached in the favorable risk group with 0 or 1 risk factor (n = 76), 19.5 months in the intermediate-risk group with 2 or 3 risk factors (n = 182), and 7.2 months in the poor risk group (n = 71) with 4 or 5 risk factors.

CONCLUSIONS

Although this is a simple and objective model, it may be used as a reliable tool to predict the outcomes of advanced cancer patients receiving ICIs across multiple tumor types.

Blood Immune Cell Biomarkers in Lung Cancer Patients Undergoing Treatment with a Combination of Chemotherapy and Immune Checkpoint Blockade

Although immune checkpoint inhibitor (ICI) therapies have improved the treatment of patients with advanced non-small cell lung cancer (NSCLC), several patients do not achieve durable clinical responses. Biomarkers for the prediction of therapy responses are urgently needed. To identify blood cell parameters correlating with patients’ survival, immune cells from 90 patients with NSCLC undergoing a combination of ICI and chemotherapy were prospectively monitored. At the time point of the first and third antibody administration, complete leukocyte blood count, the percentage of HLA-DRlow monocytes, the percentage of 6-Sulfo LacNAc (slan)+CD16+ non-classical monocytes, and the number of circulating dendritic cell (DC) subtypes, as well as T-, B-, and NK cells were determined by multi-color flow cytometry in peripheral blood. The prognostic value of the immune cell parameters investigated was evaluated by patients’ survival analysis, with progression-free survival (PFS) as the main criterion. A total of 67 patients (74.4%) showed a partial remission or a stable disease, and 35% of patients even survived 12 months and longer. Patients with a neutrophil-to-lymphocyte ratio (NLR) ≥6.1, a frequency of HLA-DRlow monocytes ≥22%, of slan+ non-classical monocytes <0.25% of leukocytes, and/or a sum of myeloid DC (MDC) and plasmacytoid DC (PDC) ≤0.14% of leukocytes had a poorer prognosis. The hazard ratio for PFS was 2.097 (1.208−3.640) for the NLR, 1.964 (1.046−3.688) for HLA-DRlow monocytes, 3.202 (1.712−5.99) for slan+ non-classical monocytes, and 2.596 (1.478−4.56) for the MDC/PDC sum. Patients without any of the four risk factors showed the best PFS. Furthermore, low NK cell counts correlated with shorter PFS (cutoff 200 cells/µL). Female patients had lower baseline NK cell counts and a shorter PFS. Our study confirms the usefulness of blood immune cells as biomarkers for clinical response and survival in NSCLC patients undergoing a combined ICI/chemotherapy.

Small molecule tyrosine kinase inhibitors modulated blood immune cell counts in patients with oncogene-driven NSCLC

BACKGROUND

Lack of biomarkers and in vitro models has contributed to inadequate understanding of the mechanisms underlying the inferior clinical response to immune checkpoint inhibitors (ICIs) in patients with oncogene-driven non-small cell lung cancer (NSCLC).

METHODS

The effect of small molecule tyrosine kinase inhibitors (TKIs) on peripheral blood mononuclear cells (PBMCs) in 34 patients with oncogene-driven NSCLC (cohort A) was compared with those from 35 NSCLC patients without oncogene-driven mutations received ICI (cohort B) or from 22 treatment-naïve NSCLC patients (cohort C). Data for each blood biomarker were summarized by mean and standard deviation and compared by Wilcoxon rank sum tests or Kruskal-Wallis tests with significance at 2-sided p value < 0.05. Co-culture of PBMCs and pleural effusion-derived tumor cells from individual patients with oncogene-driven NSCLC was used to determine the in vitro cytotoxicity of TKI and ICI.

RESULTS

Except for low CD3% in cohort A, there were no significant differences in other 12 blood biomarkers among the 3 cohorts at baseline. TKI treatment in cohort A was associated with significant increase in CD3% and decrease in total and absolute neutrophils (p < 0.05). In cohort B, patients with good clinical response to ICI treatment (N = 18) had significant increases in absolute lymphocyte counts (ALCs), CD4 and/or CD8 cell counts. Conversely, those patients with poor clinical response to ICI (N = 17) had significant decreases in these cell counts. Of the 27 patients with pre- and post-treatment blood samples in cohort A, 11 had poor clinical response to TKIs and decreased lymphocyte counts. Of the remaining 16 patients who had good clinical response to TKI therapy, 10 (62.5%) patients had decreased, and 6 (37.5%) patients had increased lymphocyte counts. Multicolor immunophenotyping of PBMCs revealed ICI treatment activated additional immune cell types that need further validation. We confirmed that TKI treatment could either antagonize or enhance the effect of ICIs in the co-culture assay using patient's tumor cells and PBMCs.

CONCLUSIONS

To the best of our knowledge, this is the first study showing that TKIs can have various effects on blood immune cells, which may affect their response to ICIs. Further validation of the blood biomarker and in vitro assay is warranted.

Durable clinical response to the multidisciplinary management of neurosurgery, radiation and chemoimmunotherapy in a patient with PD-L1/PD-L2/JAK2 (PDJ)-amplified, refractory triple-negative breast cancer

Patients with refractory metastatic triple-negative breast cancer (mTNBC) and symptomatic brain metastases have poor prognosis and are challenging to treat. The addition of an programmed cell death-1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitor (pembrolizumab or atezolizumab) to first line chemotherapy has prolonged survivals in mTNBC patients with PD-L1-positive tumor and/or tumor-infiltrating immune cells. The clinical efficacy of the chemoimmunotherapy combination in patients with refractory mTNBC, especially brain metastasis, is unknown. Co-amplification of PD-L1, PD-L2, and Janus kinase 2 (PD-L1/PD-L2/JAK2) genes (PDJ amplification) is associated with high PD-L1 protein expression and a 65-87% response rate to PD-1/PD-L1 inhibitors in patients with lymphomas. But the utility of PDJ amplification as a biomarker predictive of response to PD-1/PD-L1 inhibitors is unknown for mTNBC patients. Here, we report a 46-year-old woman who had rapid tumor progression in the brain and lung within 3 months after chemotherapy, neurosurgery, and gamma knife stereotactic radiosurgery for brain metastasis. Next-generation sequencing of her brain metastasis specimen revealed 9 copies of PDJ amplification and a tumor mutational burden of 5 mutations per megabase. Although high PDJ mRNA expression levels were detected, PD-L1 protein expression was negative on tumor cells and 10% on tumor-associated immune cells. After the debulking brain tumor resection, she received pembrolizumab monotherapy, whole brain radiation, and then atezolizumab and nab-paclitaxel with good intracranial and extracranial responses for >16 months. To the best of our knowledge, this is the first report that PDJ amplification is associated with durable clinical response to the PD-1/PD-L1 inhibitor-containing, multidisciplinary management in a patient with refractory, PD-L1 protein-negative, PDJ-amplified mTNBC. Further study is warranted to understand the underlying mechanism and validate PDJ amplification as a biomarker for clinical response to PD-1/PD-L1 inhibitor-containing therapy in patients with mTNBC.

Cancer neoantigens as potential targets for immunotherapy

Immune checkpoint inhibitors (ICIs) targeting the cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) and programed cell death protein 1 (PD-1) or its ligand PD-L1 have increased the survival and cure rates for patients with many cancer types in various disease settings. However, only 10–40% of cancer patients benefited from these ICIs, of whom ~ 20% have treatment interruption or discontinuation due to immune-related adverse events that can be severe and even fatal. Current efforts in precision immunotherapy are focused on improving biomarker-based patient selection for currently available ICIs and exploring rationale combination and novel strategies to expand the benefit of immunotherapy to more cancer patients. Neoantigens arise from ~ 10% of the non-synonymous somatic mutations in cancer cells, are important targets of T cell-mediated anti-tumor immunity for individual patients. Advances in next generation sequencing technology and computational bioinformatics have enable the identification of genomic alterations, putative neoantigens, and gene expression profiling in individual tumors for personal oncology in a rapid and cost-effective way. Among the genomic biomarkers, defective mismatch DNA repair (dMMR), microsatellite instability high (MSI-H) and high tumor mutational burden (H-TMB) have received FDA approvals for selecting patients for ICI treatment. All these biomarkers measure high neoantigen load and tumor antigenicity, supporting the current development of neoantigen-based personalized cancer vaccines for patients with high TMB tumor. Several studies have shown neoantigen vaccines are feasible, safe and have promising clinical activity in patients with high TMB tumors in both metastatic and adjuvant settings. This review summarizes the emerging data and technologies for neoantigen-based personalized immunotherapy.

DNA damage response and PD-1/PD-L1 pathway in ovarian cancer

Ovarian cancer has a poor prognosis due to drug resistance, relapse and metastasis. In recent years, immunotherapy has been applied in numerous cancers clinically. However, the effect of immunotherapy monotherapy in ovarian cancer is limited. DNA damage response (DDR) is an essential factor affecting the efficacy of tumor immunotherapy. Defective DNA repair may lead to carcinogenesis and tumor genomic instability, but on the other hand, it may also portend particular vulnerability of tumors and can be used as biomarkers for immunotherapy patient selection. Programmed cell death 1 (PD-1)/programmed death-ligand 1 (PD-L1) pathway mediates tumor immune escape, which may be a promising target for immunotherapy. Therefore, further understanding of the mechanism of PD-L1 expression after DDR may help guide the development of immunotherapy in ovarian cancer. In this review, we present the DNA damage repair pathway and summarize how DNA damage repair affects the PD-1/PD-L1 pathway in cancer cells. And then we look for biomarkers that affect efficacy or prognosis. Finally, we review the progress of PD-1/PD-L1-based immunotherapy in combination with other therapies that may affect the DDR pathway in ovarian cancer.

Prospective development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with recurrent/metastatic cancer to immune checkpoint inhibitors

Background

The predictive power of novel biological markers for treatment response to immune checkpoint inhibitors (ICI) is still not satisfactory for the majority of patients with cancer. One should identify valid predictive markers in the peripheral blood, as this is easily available before and during treatment. The current interim analysis of patients of the ST-ICI cohort therefore focuses on the development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with metastatic cancer to ICI targeting the programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) axis.

Methods

A total of 104 patients were prospectively enrolled. 54 immune cell subsets were prospectively analyzed in patients’ peripheral blood by multicolor flow cytometry before treatment with ICI (pre-ICI; n=89), and after the first application of ICI (n=65). Pre-ICI, patients were randomly allocated to a training (n=56) and a validation cohort (n=33). Univariate Cox proportional hazards regression analysis and least absolute shrinkage and selection operator Cox model were used to create a predictive immune signature, which was also checked after the first ICI, to consider the dynamics of changes in the immune status.

Results

Whole blood samples were provided by 89 patients pre-ICI and by 65 patients after the first ICI. We identified a LIPS which is based on five immune cell subtypes: CD14^high monocytes, CD8+/PD-1⁺ T cells, plasmacytoid dendritic cells, neutrophils, and CD3⁺/CD56⁺/CD16⁺ natural killer (NK)T cells. The signature achieved a high accuracy (C-index 0.74 vs 0.71) for predicting overall survival (OS) benefit in both the training and the validation cohort. In both cohorts, the low-risk group had significantly longer OS than the high-risk group (HR 0.26, 95% CI 0.12 to 0.56, p=0.00025; HR 0.30, 95% CI 0.10 to 0.91, p=0.024, respectively). Regarding the whole cohort, LIPS also predicted progression-free survival (PFS). The identified LIPS was not affected by clinicopathological features with the exception of brain metastases. NKT cells and neutrophils of the LIPS can be used as dynamic predictive biomarkers for OS and PFS after first administration of the ICI.

Conclusion

Our study identified a predictive LIPS for survival of patients with cancer treated with PD-1/PD-L1 ICI, which is based on immune cell subsets in the peripheral whole blood.

Trial registration number

NCT03453892.

Towards a Systems Immunology Approach to Unravel Responses to Cancer Immunotherapy

Immunotherapy, particularly immune checkpoint blockade and chimeric antigen receptor (CAR)-T cells, holds a great promise against cancer. These treatments have markedly improved survival in solid as well as in hematologic tumors previously considered incurable. However, durable responses occur in a fraction of patients, and existing biomarkers (e.g. PD-L1) have shown limited prediction power. This scenario highlights the need to dissect the complex interplay between immune and tumor cells to identify reliable biomarkers of response to be used for patients’ selection. In this context, systems immunology represents indeed the new frontier to address important clinical challenges in biomarker discovery. Through the integration of multiple layers of data obtained with several high-throughput approaches, systems immunology may give insights on the vast range of inter-individual differences and on the influences of genes and factors that cooperatively shape the individual immune response to a given treatment. In this Mini Review, we give an overview of the current high-throughput methodologies, including genomics, epigenomics, transcriptomics, metabolomics, proteomics, and multi-parametric phenotyping suitable for systems immunology as well as on the key steps of data integration and biological interpretation. Additionally, we review recent studies in which multi-omics technologies have been used to characterize mechanisms of response and to identify powerful biomarkers of response to checkpoint inhibitors, CAR-T cell therapy, dendritic cell-based and peptide-based cancer vaccines. We also highlight the need of favoring the collaboration of researchers with complementary expertise and of integrating multi-omics data into biological networks with the final goal of developing accurate markers of therapeutic response.