FlowCT for the analysis of large immunophenotypic datasets and biomarker discovery in cancer immunology

Efficacy of LCMV-based cancer immunotherapies is unleashed by intratumoral injections of polyI:C

BACKGROUND

Lymphocytic choriomeningitis virus (LCMV) belongs to the Arenavirus family known for inducing strong cytotoxic T-cell responses in both mice and humans. LCMV has been engineered for the development of cancer immunotherapies, currently undergoing evaluation in phase I/II clinical trials. Initial findings have demonstrated safety and an exceptional ability to activate and expand tumor-specific T lymphocytes. Combination strategies to maximize the antitumor effectiveness of LCMV-based immunotherapies are being explored.

METHODS

We assessed the antitumor therapeutic effects of intratumoral administration of polyinosinic:polycytidylic acid (poly(I:C)) and systemic vaccination using an LCMV-vector expressing non-oncogenic versions of the E6 and E7 antigens of human papillomavirus 16 (artLCMV-E7E6) in a bilateral model engrafting TC-1/A9 cells. This cell line, derived from the parental TC-1, exhibits low MHC class I expression and is highly immune-resistant. The mechanisms underlying the combination's efficacy were investigated through bulk RNA-seq, flow cytometry analyses of the tumor microenvironment, selective depletions using antibodies and clodronate liposomes, Batf3 deficient mice, and in vivo bioluminescence experiments. Finally, we assessed the antitumor effectiveness of the combination of artLCMV-E7E6 with BO-112, a GMP-grade poly(I:C) formulated in polyethyleneimine, currently under evaluation in clinical trials.

RESULTS

Intratumoral injection of poly(I:C) enhanced the antitumor efficacy of artLCMV-E7E6 in both injected and non-injected tumor lesions. The combined treatment resulted in a significant delay in tumor growth and often complete eradication of several tumor lesions, leading to significantly improved survival compared with monotherapies. While intratumoral administration of poly(I:C) did not impact LCMV vector biodistribution or transgene expression, it significantly modified leucocyte infiltrates within the tumor microenvironment and amplified systemic efficacy through proinflammatory cytokines/chemokines such as CCL3, CCL5, CXCL10, TNF, IFNα, and IL12p70. Upregulation of MHC on tumor cells and a reconfiguration of the gene expression programs related to tumor vasculature, leucocyte migration, and the activation profile of tumor-infiltrating CD8+ T lymphocytes were observed. Indeed, the antitumor effect relied on the functions of CD8+ T lymphocytes and macrophages. The synergistic efficacy of the combination was further confirmed when BO-112 was included.

CONCLUSION

Intratumoral injection of poly(I:C) sensitizes MHClow tumors to the antitumor effects of artLCMV-E7E6, resulting in a potent therapeutic synergy.

Immune profiles to predict bortezomib-based treatment response for multiple myeloma patients

BACKGROUND

To evaluate the distribution of bone marrow immune cell subsets and their correlation with treatment efficacy in patients with multiple myeloma (MM).

METHODS

We analyzed the bone marrow lymphocyte subsets of 186 newly diagnosed MM patients at diagnosis and their correlation with clinical characteristics. In our study, eight-color flow cytometry, a method commonly used to detect plasma cell phenotypes, was used to analyze seven bone marrow immune cell groups by change gate-strategy.

RESULTS

First, for all the 7 immune cell groups, the percentage of immature B cells was significantly lower in stage III patients than in stage I patients, while the trend was reversed in memory B cells in both the International Staging System(p = 0.004) and Revised International Staging System(p = 0.018). Second, the percentage of naïve B cells were significantly lower in patients with severe anemia, while the percentage of memory B cells had reversed trend. The percentage of immature B cells were lower in patients with Cr ≥ 2 mg/dL than in patients with Cr < 2 mg/dL. Then we followed the treatment efficacy of 152 patients who received four cycles of induction therapy (bortezomib + dexamethasone or bortezomib + lenalidomide + dexamethasone) and analyzed the relationship between bone marrow lymphocyte subsets at the initial stage and treatment response datasets. We found that both the percentage of B cells(p＜0.001) and immature B(p = 0.002) were increased in patients who achieved very good partial remission(VGPR) after four cycles of induction therapy. The ROC results indicated the combination of the multiple immune subgroups had predictive values (AUC = 0.802, p<0.001) in the treatment effect after four cycles of induction therapy.

CONCLUSIONS

Overall, these results suggest that the analysis of lymphocyte subsets along with plasma cell immunophenotyping could be a potential index for determining the prognosis of MM patients.

Large T cell clones expressing immune checkpoints increase during multiple myeloma evolution and predict treatment resistance

Tumor recognition by T cells is essential for antitumor immunity. A comprehensive characterization of T cell diversity may be key to understanding the success of immunomodulatory drugs and failure of PD-1 blockade in tumors such as multiple myeloma (MM). Here, we use single-cell RNA and T cell receptor sequencing to characterize bone marrow T cells from healthy adults (n = 4) and patients with precursor (n = 8) and full-blown MM (n = 10). Large T cell clones from patients with MM expressed multiple immune checkpoints, suggesting a potentially dysfunctional phenotype. Dual targeting of PD-1 + LAG3 or PD-1 + TIGIT partially restored their function in mice with MM. We identify phenotypic hallmarks of large intratumoral T cell clones, and demonstrate that the CD27- and CD27+ T cell ratio, measured by flow cytometry, may serve as a surrogate of clonal T cell expansions and an independent prognostic factor in 543 patients with MM treated with lenalidomide-based treatment combinations.

Understanding high-risk smoldering multiple myeloma

Smoldering multiple myeloma (SMM) is an asymptomatic condition with heterogeneous biology and various risks of progression to symptomatic disease. The best-known risk stratification models are Mayo-2018, and IWWG based on tumor burden. Recently, the personalized risk assessment tool PANGEA was introduced. New markers of SMM progression, including genomic and immune characteristics of plasma cells (PCs) and tumor microenvironment, are under investigation, and some have been incorporated into traditional scoring systems. Only one phase 3 clinical trial demonstrated an overall survival benefit of lenalidomide for high-risk SMM patients. The study has limitations, and most guidelines recommend observation or participation in clinical trials for high-risk SMM. High-intensity time-limited treatment strategies for high-risk SMM demonstrated deep responses in single-arm studies. But these treatments can cause adverse effects in asymptomatic patients.This review aims to understand better the risk of SMM progression from a clinical and biological point of view.

Ferritin Metabolism Reflects Multiple Myeloma Microenvironment and Predicts Patient Outcome

Multiple myeloma (MM) is a hematologic malignancy with a multistep evolutionary pattern, in which the pro-inflammatory and immunosuppressive microenvironment and genomic instability drive tumor evolution. MM microenvironment is rich in iron, released by pro-inflammatory cells from ferritin macromolecules, which contributes to ROS production and cellular damage. In this study, we showed that ferritin increases from indolent to active gammopathies and that patients with low serum ferritin had longer first line PFS (42.6 vs. 20.7 months and, p = 0.047, respectively) and OS (NR vs. 75.1 months and p = 0.029, respectively). Moreover, ferritin levels correlated with systemic inflammation markers and with the presence of a specific bone marrow cell microenvironment (including increased MM cell infiltration). Finally, we verified by bioinformatic approaches in large transcriptomic and single cell datasets that a gene expression signature associated with ferritin biosynthesis correlated with worse outcome, MM cell proliferation, and specific immune cell profiles. Overall, we provide evidence of the role of ferritin as a predictive/prognostic factor in MM, setting the stage for future translational studies investigating ferritin and iron chelation as new targets for improving MM patient outcome.

Definition and Clinical Significance of the Monoclonal Gammopathy of Undetermined Significance-Like Phenotype in Patients With Monoclonal Gammopathies

PURPOSE

The existence of patients with multiple myeloma (MM) and light-chain (AL) amyloidosis who present with a monoclonal gammopathy of undetermined significance (MGUS)-like phenotype has been hypothesized, but methods to identify this subgroup are not standardized and its clinical significance is not properly validated.

PATIENTS AND METHODS

An algorithm to identify patients having MGUS-like phenotype was developed on the basis of the percentages of total bone marrow (BM) plasma cells (PC) and of clonal PC within the BM PC compartment, determined at diagnosis using flow cytometry in 548 patients with MGUS and 2,011 patients with active MM. The clinical significance of the algorithm was tested and validated in 488 patients with smoldering MM, 3,870 patients with active MM and 211 patients with AL amyloidosis.

RESULTS

Patients with smoldering MM with MGUS-like phenotype showed significantly lower rates of disease progression (4.5% and 0% at 2 years in two independent series). There were no statistically significant differences in time to progression between treatment versus observation in these patients. In active newly diagnosed MM, MGUS-like phenotype retained independent prognostic value in multivariate analyses of progression-free survival (PFS; hazard ratio [HR], 0.49; P = .001) and overall survival (OS; HR, 0.56; P = .039), together with International Staging System, lactate dehydrogenase, cytogenetic risk, transplant eligibility, and complete remission status. Transplant-eligible patients with active MM with MGUS-like phenotype showed PFS and OS rates at 5 years of 79% and 96%, respectively. In this subgroup, there were no differences in PFS and OS according to complete remission and measurable residual disease status. Application of the algorithm in two independent series of patients with AL predicted for different survival.

CONCLUSION

We developed an open-access algorithm for the identification of MGUS-like patients with distinct clinical outcomes. This phenotypic classification could become part of the diagnostic workup of MM and AL amyloidosis.

Preclinical models for prediction of immunotherapy outcomes and immune evasion mechanisms in genetically heterogeneous multiple myeloma

The historical lack of preclinical models reflecting the genetic heterogeneity of multiple myeloma (MM) hampers the advance of therapeutic discoveries. To circumvent this limitation, we screened mice engineered to carry eight MM lesions (NF-κB, KRAS, MYC, TP53, BCL2, cyclin D1, MMSET/NSD2 and c-MAF) combinatorially activated in B lymphocytes following T cell-driven immunization. Fifteen genetically diverse models developed bone marrow (BM) tumors fulfilling MM pathogenesis. Integrative analyses of ∼500 mice and ∼1,000 patients revealed a common MAPK-MYC genetic pathway that accelerated time to progression from precursor states across genetically heterogeneous MM. MYC-dependent time to progression conditioned immune evasion mechanisms that remodeled the BM microenvironment differently. Rapid MYC-driven progressors exhibited a high number of activated/exhausted CD8⁺ T cells with reduced immunosuppressive regulatory T (T_reg) cells, while late MYC acquisition in slow progressors was associated with lower CD8⁺ T cell infiltration and more abundant T_reg cells. Single-cell transcriptomics and functional assays defined a high ratio of CD8⁺ T cells versus T_reg cells as a predictor of response to immune checkpoint blockade (ICB). In clinical series, high CD8⁺ T/T_reg cell ratios underlie early progression in untreated smoldering MM, and correlated with early relapse in newly diagnosed patients with MM under Len/Dex therapy. In ICB-refractory MM models, increasing CD8⁺ T cell cytotoxicity or depleting T_reg cells reversed immunotherapy resistance and yielded prolonged MM control. Our experimental models enable the correlation of MM genetic and immunological traits with preclinical therapy responses, which may inform the next-generation immunotherapy trials.

Monoclonal Gammopathies and the Bone Marrow Microenvironment: From Bench to Bedside and Then Back Again

Multiple myeloma (MM) is an incurable hematologic malignancy characterized by a multistep evolutionary pathway, with an initial phase called monoclonal gammopathy of undetermined significance (MGUS), potentially evolving into the symptomatic disease, often preceded by an intermediate phase called "smoldering" MM (sMM). From a biological point of view, genomic alterations (translocations/deletions/mutations) are already present at the MGUS phase, thus rendering their role in disease evolution questionable. On the other hand, we currently know that changes in the bone marrow microenvironment (TME) could play a key role in MM evolution through a progressive shift towards a pro-inflammatory and immunosuppressive shape, which may drive cancer progression as well as clonal plasma cells migration, proliferation, survival, and drug resistance. Along this line, the major advancement in MM patients' survival has been achieved by the introduction of microenvironment-oriented drugs (including immunomodulatory drugs and monoclonal antibodies). In this review, we summarized the role of the different components of the TME in MM evolution from MGUS as well as potential novel therapeutic targets/opportunities.

Detection of early-stage lung cancer in sputum using automated flow cytometry and machine learning

BACKGROUND

Low-dose spiral computed tomography (LDCT) may not lead to a clear treatment path when small to intermediate-sized lung nodules are identified. We have combined flow cytometry and machine learning to develop a sputum-based test (CyPath Lung) that can assist physicians in decision-making in such cases.

METHODS

Single cell suspensions prepared from induced sputum samples collected over three consecutive days were labeled with a viability dye to exclude dead cells, antibodies to distinguish cell types, and a porphyrin to label cancer-associated cells. The labeled cell suspension was run on a flow cytometer and the data collected. An analysis pipeline combining automated flow cytometry data processing with machine learning was developed to distinguish cancer from non-cancer samples from 150 patients at high risk of whom 28 had lung cancer. Flow data and patient features were evaluated to identify predictors of lung cancer. Random training and test sets were chosen to evaluate predictive variables iteratively until a robust model was identified. The final model was tested on a second, independent group of 32 samples, including six samples from patients diagnosed with lung cancer.

RESULTS

Automated analysis combined with machine learning resulted in a predictive model that achieved an area under the ROC curve (AUC) of 0.89 (95% CI 0.83-0.89). The sensitivity and specificity were 82% and 88%, respectively, and the negative and positive predictive values 96% and 61%, respectively. Importantly, the test was 92% sensitive and 87% specific in cases when nodules were < 20 mm (AUC of 0.94; 95% CI 0.89-0.99). Testing of the model on an independent second set of samples showed an AUC of 0.85 (95% CI 0.71-0.98) with an 83% sensitivity, 77% specificity, 95% negative predictive value and 45% positive predictive value. The model is robust to differences in sample processing and disease state.

CONCLUSION

CyPath Lung correctly classifies samples as cancer or non-cancer with high accuracy, including from participants at different disease stages and with nodules < 20 mm in diameter. This test is intended for use after lung cancer screening to improve early-stage lung cancer diagnosis. Trial registration ClinicalTrials.gov ID: NCT03457415; March 7, 2018.

Network meta-analysis of randomized trials in multiple myeloma: Efficacy and safety in frontline therapy for patients not eligible for transplant

The treatment scenario for newly-diagnosed transplant-ineligible multiple myeloma patients (NEMM) is quickly evolving. Currently, combinations of proteasome inhibitors and/or immunomodulatory drugs +/- the monoclonal antibody Daratumumab are used for first-line treatment, even if head-to-head comparisons are lacking. To compare efficacy and safety of these regimens, we performed a network meta-analysis of 27 phase 2/3 randomized trials including a total of 12,935 patients and 23 different schedules. Four efficacy/outcome and one safety indicators were extracted and integrated to obtain (for each treatment) the surface under the cumulative ranking-curve (SUCRA), a metric used to build a ranking chart. With a mean SUCRA of 83.8 and 80.08 respectively, VMP + Daratumumab (DrVMP) and Rd + Daratumumab (DrRd) reached the top of the chart. However, SUCRA is designed to work for single outcomes. To overcome this limitation, we undertook a dimensionality reduction approach through a principal component analysis, that unbiasedly grouped the 23 regimens into three different subgroups. On the bases of our results, we demonstrated that first line treatment for NEMM should be based on DrRd (most active, but continuous treatment), DrVMP (quite "fixed-time" treatment), or, alternatively, VRD and that, surprisingly, melphalan as well as Rd doublets still deserve a role in this setting.

Circulating Tumor and Immune Cells for Minimally Invasive Risk Stratification of Smoldering Multiple Myeloma

PURPOSE

Early intervention in smoldering multiple myeloma (SMM) requires optimal risk stratification to avoid under- and overtreatment. We hypothesized that replacing bone marrow (BM) plasma cells (PC) for circulating tumor cells (CTC), and adding immune biomarkers in peripheral blood (PB) for the identification of patients at risk of progression due to lost immune surveillance, could improve the International Myeloma Working Group 20/2/20 model.

EXPERIMENTAL DESIGN

We report the outcomes of 150 patients with SMM enrolled in the iMMunocell study, in which serial assessment of tumor and immune cells in PB was performed every 6 months for a period of 3 years since enrollment.

RESULTS

Patients with >0.015% versus ≤0.015% CTCs at baseline had a median time-to-progression of 17 months versus not reached (HR, 4.9; P < 0.001). Presence of >20% BM PCs had no prognostic value in a multivariate analysis that included serum free light-chain ratio >20, >2 g/dL M-protein, and >0.015% CTCs. The 20/2/20 and 20/2/0.015 models yielded similar risk stratification (C-index of 0.76 and 0.78). The combination of the 20/2/0.015 model with an immune risk score based on the percentages of SLAN+ and SLAN- nonclassical monocytes, CD69+HLADR+ cytotoxic NK cells, and CD4+CXCR3+ stem central memory T cells, allowed patient' stratification into low, intermediate-low, intermediate-high, and high-risk disease with 0%, 20%, 39%, and 73% rates of progression at 2 years.

CONCLUSIONS

This study showed that CTCs outperform BM PCs for assessing tumor burden. Additional analysis in larger series are needed to define a consensus cutoff of CTCs for minimally invasive stratification of SMM.

Label-Free Enrichment of Circulating Tumor Plasma Cells: Future Potential Applications of Dielectrophoresis in Multiple Myeloma

In multiple myeloma (MM), circulating tumor plasma cells (CTPCs) are an emerging prognostic factor, offering a promising and minimally invasive means for longitudinal patient monitoring. Recent advances highlight the complex biology of plasma cell trafficking, highlighting the phenotypic and genetic signatures of intra- and extra-medullary MM onset, making CTPC enumeration and characterization a new frontier of precision medicine for MM patients, requiring novel technological platforms for their standardized and harmonized detection. Dielectrophoresis (DEP) is an emerging label-free cell manipulation technique to separate cancer cells from healthy cells in peripheral blood samples, based on phenotype and membrane capacitance that could be successfully tested to enumerate and isolate CTPCs. Herein, we summarize preclinical data on DEP development for CTPC detection, as well as their clinical and research potential.

Impact of Mycobacterium tuberculosis Infection on Human B Cell Compartment and Antibody Responses

Tuberculosis (TB) remains one of the most important health challenges worldwide. Control of the TB epidemic has not yet been achieved because of the lack of an effective vaccine and rapid and sensitive diagnostic approaches, as well as the emergence of drug-resistant forms of M. tuberculosis. Cellular immunity has a pivotal role against M. tuberculosis infection, but the role of humoral immunity is still controversial. We analyzed the frequency, absolute counts, and phenotypic and functional subsets of B lymphocytes in the peripheral blood of patients with active TB and subjects with latent infection compared to healthy donors. Moreover, we analyzed serum levels of total Ig and their IgA, IgM, and IgG isotypes and the titers of preexisting antibodies against a pool of common viral pathogens. FlowCT and unsupervised clusterization analysis show that patients with active TB and LTBI subjects have modest non-significant reduction in the numbers of circulating B lymphocytes as compared to healthy donors. Moreover, LTBI subjects had high percentages of atypical B cell population and lower percentages of naive and switched memory B cells. These findings were supported by gene expression and GSEA analysis. Moreover, there were no differences between active TB patients, LTBI subjects and HD, either in serum levels of total Ig isotypes or in preexisting IgG antibody titers, to ten different antigens from eight common pathogenic viruses, clearly demonstrating that either active or latent M. tuberculosis infection preserves the antibody production capacity of long-lived plasma cells. Thus, our results agree with previous studies reporting unaltered B cell frequencies in the blood of active TB patients and LTBI individuals as compared to healthy controls.

PD-1/PD-L1 immune-checkpoint blockade induces immune effector cell modulation in metastatic non-small cell lung cancer patients: A single-cell flow cytometry approach

Peripheral immune-checkpoint blockade with mAbs to programmed cell death receptor-1 (PD-1) (either nivolumab or pembrolizumab) or PD-Ligand-1 (PD-L1) (atezolizumab, durvalumab, or avelumab) alone or in combination with doublet chemotherapy represents an expanding treatment strategy for metastatic non-small cell lung cancer (mNSCLC) patients. This strategy lays on the capability of these mAbs to rescue tumor-specific cytotoxic T lymphocytes (CTLs) inactivated throughout PD-1 binding to PD-L1/2 in the tumor sites. This inhibitory interactive pathway is a physiological mechanism of prevention against dangerous overreactions and autoimmunity in case of prolonged and/or repeated CTL response to the same antigen peptides. Therefore, we have carried out a retrospective bioinformatics analysis by single-cell flow cytometry to evaluate if PD-1/PD-L1-blocking mAbs modulate the expression of specific peripheral immune cell subsets, potentially correlated with autoimmunity triggering in 28 mNSCLC patients. We recorded a treatment-related decline in CD4⁺ T-cell and B-cell subsets and in the neutrophil-to-lymphocyte ratio coupled with an increase in natural killer T (NKT), CD8⁺PD1⁺ T cells, and eosinophils. Treatment-related increase in autoantibodies [mainly antinuclear antibodies (ANAs) and extractable nuclear antigen (ENA) antibodies] as well as the frequency of immune-related adverse events were associated with the deregulation of specific immune subpopulations (e.g., NKT cells). Correlative biological/clinical studies with deep immune monitoring are badly needed for a better characterization of the effects produced by PD-1/PD-L1 immune-checkpoint blockade.

Biological Characterization and Clinical Relevance of Circulating Tumor Cells: Opening the Pandora's Box of Multiple Myeloma

Simple Summary

Bone marrow (BM) aspirates are mandatory for diagnosis and follow-up of patients with multiple myeloma (MM). However, they present two important caveats: Their invasiveness and limited scope to capture the broad tumor heterogeneity. Conversely, circulating tumor cells (CTCs) are detectable in the peripheral blood of patients with precursor and malignant disease states and have strong prognostic value. Moreover, the high genetic and transcriptomic overlap between both plasma cell compartments suggests that CTCs might reflect with notable precision the medullar clone. Furthermore, the study of CTCs could be used as a model to identify mechanisms favoring BM egression and disease spreading. Here, we summarize the state of the art on MM CTCs and provide insights on what they may offer in research and clinical scenarios.

Abstract

Bone marrow (BM) aspirates are the gold standard for patient prognostication and genetic characterization in multiple myeloma (MM). However, they represent an important limitation for periodic disease monitoring because they entail an aggressive procedure. Moreover, recent findings show that a single BM aspirate is unable to reflect the complex MM heterogeneity. Recent advances in flow cytometry, microfluidics, and “omics” technologies have opened Pandora’s box of MM: The detection and isolation of circulating tumor cells (CTCs) offer a promising and minimally invasive alternative for tumor assessment and metastasis study. CTCs are detectable in premalignant and active MM states, and their enumeration has strong prognostic value, to the extent that it is challenging current stratification systems. In addition, CTCs reflect with high precision both intra- and extra-medullary disease at the phenotypic, genomic, and transcriptomic levels. Despite this high resemblance between tumor clones in distinct locations, some subtle (not random) differences might shed some light on the metastatic process. Thus, it has been suggested that a hypoxic and pro-inflammatory microenvironment could induce an arrest in proliferation forcing tumor cells to recirculate. Herein, we summarize data on the characterization of MM CTCs as well as their clinical and research potential.

Immune biomarkers to predict SARS-CoV-2 vaccine effectiveness in patients with hematological malignancies

There is evidence of reduced SARS-CoV-2 vaccine effectiveness in patients with hematological malignancies. We hypothesized that tumor and treatment-related immunosuppression can be depicted in peripheral blood, and that immune profiling prior to vaccination can help predict immunogenicity. We performed a comprehensive immunological characterization of 83 hematological patients before vaccination and measured IgM, IgG, and IgA antibody response to four viral antigens at day +7 after second-dose COVID-19 vaccination using multidimensional and computational flow cytometry. Health care practitioners of similar age were the control group (n = 102). Forty-four out of 59 immune cell types were significantly altered in patients; those with monoclonal gammopathies showed greater immunosuppression than patients with B-cell disorders and Hodgkin lymphoma. Immune dysregulation emerged before treatment, peaked while on-therapy, and did not return to normalcy after stopping treatment. We identified an immunotype that was significantly associated with poor antibody response and uncovered that the frequency of neutrophils, classical monocytes, CD4, and CD8 effector memory CD127low T cells, as well as naive CD21+ and IgM+D+ memory B cells, were independently associated with immunogenicity. Thus, we provide novel immune biomarkers to predict COVID-19 vaccine effectiveness in hematological patients, which are complementary to treatment-related factors and may help tailoring possible vaccine boosters.