Cytidine deaminase status as a marker of response to azacytidine treatment in MDS and AML patients.

Azacitidine (Aza) is a mainstay of treatment for patients with acute myeloid leukaemia (AML) ineligible for induction chemotherapy and other high-risk myelodysplastic syndromes (MDS). Only half of patients respond, and almost all will eventually relapse. There are no predictive markers of response to Aza. Aza is detoxified in the liver by cytidine deaminase (CDA). Here, we investigated the association between CDA phenotype, toxicity and efficacy of Aza in real-world adult patients. Median overall survival (OS) was 15 months and 13 months in AML and high-risk MDS patients respectively. In addition, our data suggest that delaying Aza treatment was not associated with lack of efficacy and should not be considered a signal to switch to an alternative treatment. Half of the patients had deficient CDA activity (i.e. <2 UA/mg), with a lower proportion of deficient patients in MDS patients (34%) compared to AML patients (67%). In MDS patients, CDA deficiency correlated with longer landmark OS (14 vs. 8 months; p = 0.03), but not in AML patients. Taken together, our data suggest that CDA is an independent covariate and may therefore be a marker for predicting clinical outcome in MDS patients treated with Aza.

A non-inferiority randomized phase III trial of standard immunotherapy by checkpoint inhibitors vs. reduced dose intensity in responding patients with metastatic cancer: the MOIO protocol study.

BACKGROUND: Immunotherapy (IO) has become a standard of care for treating various types of metastatic cancers and has significantly improved clinical outcome. With the exception of metastatic melanoma in complete response for which treatment can be stopped at 6 months, these treatments are currently administered until either disease progression for some IO, 2 years for others, or unacceptable toxicity. However, a growing number of studies are reporting maintenance of response despite discontinuation of therapy. There is currently no evidence of a dose effect of IO in pharmacokinetic studies. Maintaining efficacy despite a reduction in treatment intensity by decreasing the frequency of administration in patients with highly selected metastatic cancer, is the hypothesis evaluated in the MOIO study. METHOD/DESIGN: This non-inferiority, randomized phase III study aims to compare the standard regimen to a 3 monthly regimen of variousIO drugs in adult patients with metastatic cancer in partial (PR) or complete response (CR) after 6 months of standard IO dosing (except melanoma in CR). This is a French national study conducted in 36 centers. The main objective is to demonstrate that the efficacy of a three-monthly administration is not unacceptably less efficacious than a standard administration. Secondary objectives are cost-effectiveness, quality of life (QOL), anxiety, fear of relapse, response rate, overall survival and toxicity. After 6 months of standard IO, patients with partial or complete response will be randomized 1:1 between standard IO or a reduced intensity dose of IO, administered every 3 months. The randomization will be stratified on therapy line,, tumor type, IO type and response status. The primary endpoint is the hazard ratio of progression-free survival. With a planned study duration of 6 years, including 36 months enrolment time, 646 patients are planned to demonstrate with a statistical level of evidence of 5% that the reduced IO regimen is non-inferior to the standard IO regimen, with a relative non-inferiority margin set at 1.3. DISCUSSION: Should the hypothesis of non-inferiority with an IO reduced dose intensity be validated, alternate scheduling could preserve efficacy while being cost-effective and allowing a reduction of the toxicity, with an increase in patient's QOL. TRIAL REGISTRATION: NCT05078047.

Quantitative impact of pre-analytical process on plasma uracil when testing for dihydropyrimidine dehydrogenase deficiency.

AIMS: Determining dihydropyrimidine dehydrogenase (DPD) activity by measuring patient's uracil (U) plasma concentration is mandatory before fluoropyrimidine (FP) administration in France. In this study, we aimed to refine the pre-analytical recommendations for determining U and dihydrouracil (UH2 ) concentrations, as they are essential in reliable DPD-deficiency testing. METHODS: U and UH2 concentrations were collected from 14 hospital laboratories. Stability in whole blood and plasma after centrifugation, the type of anticoagulant and long-term plasma storage were evaluated. The variation induced by time and temperature was calculated and compared to an acceptability range of ±20%. Inter-occasion variability (IOV) of U and UH2 was assessed in 573 patients double sampled for DPD-deficiency testing. RESULTS: Storage of blood samples before centrifugation at room temperature (RT) should not exceed 1 h, whereas cold (+4°C) storage maintains the stability of uracil after 5 hours. For patients correctly double sampled, IOV of U reached 22.4% for U (SD = 17.9%, range = 0-99%). Notably, 17% of them were assigned with a different phenotype (normal or DPD-deficient) based on the analysis of their two samples. For those having at least one non-compliant sample, this percentage increased up to 33.8%. The moment of blood collection did not affect the DPD phenotyping result. CONCLUSION: Caution should be taken when interpreting U concentrations if the time before centrifugation exceeds 1 hour at RT, since it rises significantly afterwards. Not respecting the pre-analytical conditions for DPD phenotyping increases the risk of DPD status misclassification.

Renal impairment and DPD testing: Watch out for false-positive results!

Measuring uracil (U) levels in plasma is a convenient surrogate to establish dihydropyrimidine dehydrogenase (DPD) status in patients scheduled with 5-fluorouracil (5-FU) or capecitabine. To what extent renal impairment could impact on U levels and thus be a confounding factor is a rising concern. Here, we report the case of a cancer patient with severe renal impairment scheduled for 5-FU-based regimen. Determination of his DPD status was complicated because of his condition and the influence of intermittent haemodialysis when monitoring U levels. The patient was initially identified as markedly DPD-deficient upon U measurement (i.e., U = 40 ng/mL), but further monitoring between and immediately after dialysis showed mild deficiency only (i.e., U = 34 and U = 19 ng/mL, respectively). Despite this discrepancy, a starting dose of 5-FU was cut by 50% upon treatment initiation. Tolerance was good and 5-FU dosing was next shifted to 25% reduction, then further shifted to normal dosing at the 5th course, with still no sign for drug-related toxicities. Further DPYD genotyping showed none of the four allelic variants usually associated with loss of DPD activity. Of note, the excellent tolerance upon standard dosing strongly suggests that this patient was actually not DPD-deficient, despite U values always above normal concentrations. This case report highlights how critical is the information regarding the renal function of patients with cancer when phenotyping DPD using U plasma as a surrogate, and that U accumulation in patients with such condition is likely to yield false-positive results.

COVID-19 vaccine race: watch your step for cancer patients.

Patients with cancer should benefit from COVID-19 vaccination. Some of the most advanced vaccine candidates are mRNAs encapsulated into lipid carriers, and small liposomes are expected to accumulate in tumour tissues through the enhanced and permeation retention effect. However, to what extent solid tumours could take up a significant part of the vaccine dose as well remains unknown. This calls for a careful evaluation of the efficacy of these promising mRNA COVID-19 vaccines administered as lipid carriers for patients with solid tumours, including a possible re-appraisal of the dosing for optimal protection of this specific and frail population.

Population modeling of tumor growth curves and the reduced Gompertz model improve prediction of the age of experimental tumors.

Tumor growth curves are classically modeled by means of ordinary differential equations. In analyzing the Gompertz model several studies have reported a striking correlation between the two parameters of the model, which could be used to reduce the dimensionality and improve predictive power. We analyzed tumor growth kinetics within the statistical framework of nonlinear mixed-effects (population approach). This allowed the simultaneous modeling of tumor dynamics and inter-animal variability. Experimental data comprised three animal models of breast and lung cancers, with 833 measurements in 94 animals. Candidate models of tumor growth included the exponential, logistic and Gompertz models. The exponential and-more notably-logistic models failed to describe the experimental data whereas the Gompertz model generated very good fits. The previously reported population-level correlation between the Gompertz parameters was further confirmed in our analysis (R2 > 0.92 in all groups). Combining this structural correlation with rigorous population parameter estimation, we propose a reduced Gompertz function consisting of a single individual parameter (and one population parameter). Leveraging the population approach using Bayesian inference, we estimated times of tumor initiation using three late measurement timepoints. The reduced Gompertz model was found to exhibit the best results, with drastic improvements when using Bayesian inference as compared to likelihood maximization alone, for both accuracy and precision. Specifically, mean accuracy (prediction error) was 12.2% versus 78% and mean precision (width of the 95% prediction interval) was 15.6 days versus 210 days, for the breast cancer cell line. These results demonstrate the superior predictive power of the reduced Gompertz model, especially when combined with Bayesian estimation. They offer possible clinical perspectives for personalized prediction of the age of a tumor from limited data at diagnosis. The code and data used in our analysis are publicly available at https://github.com/cristinavaghi/plumky.

Deciphering the response and resistance to immune-checkpoint inhibitors in lung cancer with artificial intelligence-based analysis: when PIONeeR meets QUANTIC.

This project aims to generate dense longitudinal data in lung cancer patients undergoing anti-PD1/PDL1 therapy. Mathematical modelling with mechanistic learning algorithms will help decipher the mechanisms underlying the response or resistance to immunotherapy. A better understanding of these mechanisms should help identifying actionable items to increase the efficacy of immune-checkpoint inhibitors.

Tumor uptake and associated greater efficacy of anti-Her2 immunoliposome does not rely on Her2 expression status: study of a docetaxel-trastuzumab immunoliposome on Her2+ breast cancer model (SKBR3).

Nanoparticles have been used for decades in breast cancer. More recently, anti-human epidermal receptor 2 (Her2) immunoliposomes are of rising interest. However, recent studies have questioned the actual relevance of using anti-Her2 antibodies to improve liposome distribution and efficacy. Using standard thin-film method and maleimide linker, we have synthesized a 140-nm docetaxel-trastuzumab immunoliposome. This nanoparticle was then tested on a canonical Her2-overexpressing breast cancer model (i.e., SKBR3), using 3D spheroids and xenografted mice. Its efficacy was compared with free docetaxel + trastuzumab, liposomal docetaxel + free trastuzumab and to reference antibody-drug conjugate trastuzumab-emtansine (T-DM1). Immunoliposomes resulted in better efficacy as compared with all other treatments, both in vitro and in vivo. To explain such an improvement, immunoliposome biodistribution was investigated using live imaging in xenografted mice. Surprisingly, no difference in tumor uptake was found between anti-Her2 immunoliposomes and standard docetaxel liposomes (i.e., 1.9 ± 1.2 vs. 1.7 ± 0.5% at the end of treatment and 1.4 ± 0.6 vs. 1.6 ± 0.4% at the end of the study, respectively, P > 0.05). We hypothesized that passive targeting (i.e., enhanced permeation and retention effect) contributed more to tumor distribution than active targeting and that the observed differences in efficacy could come from a better internalization of immunoliposomes into Her2+ cells as compared with standard liposomes, and not from a higher specificity towards tumor tissue.

Pharmacodynamic Therapeutic Drug Monitoring for Cancer: Challenges, Advances, and Future Opportunities.

In the modern era of cancer treatment, with targeted agents superseding more traditional cytotoxic chemotherapeutics, it is becoming increasingly important to use stratified medicine approaches to ensure that patients receive the most appropriate drugs and treatment schedules. In this context, there is significant potential for the use of pharmacodynamic biomarkers to provide pharmacological information, which could be used in a therapeutic drug monitoring setting. This review focuses on discussing some of the challenges faced to date in translating preclinical pharmacodynamic biomarker approaches to a clinical setting. Recent advances in important areas including circulating biomarkers and pharmacokinetic/pharmacodynamic modeling approaches are discussed, and selected examples of anticancer drugs where there is existing evidence to potentially advance pharmacodynamic therapeutic drug monitoring approaches to deliver more effective treatment are discussed. Although we may not yet be in a position to systematically implement therapeutic drug monitoring approaches based on pharmacodynamic information in a cancer patient setting, such approaches are likely to become more commonplace in the coming years. Based on ever-increasing levels of pharmacodynamic information being generated on newer anticancer drugs, facilitated by increasingly advanced and accessible experimental approaches available to researchers to collect these data, we can now look forward optimistically to significant advances being made in this area.

Estimation of Unbound Carboplatin Clearance From Total Plasma Concentrations as a Means of Facilitating Therapeutic Drug Monitoring.

BACKGROUND: Therapeutic drug monitoring of carboplatin is based on its unbound clearance (CLU) determined by Bayesian analysis on unbound (U) concentrations. However, the ultrafiltration of plasma samples presents technical and time constraints. Therefore, this study aims to estimate CLU using total plasma (P) concentrations. METHODS: U and P concentration data of 407 patients were obtained from 2 clinical studies in which actual CLU had been determined for each patient. The patients were then split into development (277 patients) and prospective data sets (130 patients). Two approaches were evaluated. PK-model-only approach: a 3-compartment pharmacokinetic (PK) model based on U and P concentrations and taking into account the protein binding process was developed. The model with patient covariates was also evaluated. Linear regression approach: an equation (CLU = aCLP + b) was obtained by linear regression analysis between actual CLU and CLP, which is the total plasma clearance obtained by analyzing P concentrations according to a 2-compartment PK model. Predictive performance was then assessed within the prospective data set by estimating CLU from P concentrations using each approach and computing the relative percentage error (PE) between estimated CLU and actual CLU. RESULTS: The linear regression equation was CLU (L/h) = 1.15 CLP (L/h) + 0.13. The mean PE (MPE) between CLU (estimated using the equation) and the actual CLU was +1.2% (ranging from -31% to +33%) and the mean absolute PE (MAPE) was 9.7%. With the 3-compartment PK model, the MPE was +2.3% (ranging from -41% to +31%) and the MAPE was 11.1%. Inclusion of covariates in the 3-compartment model did not improve the estimation of CLU [MPE = +6.3% (from -33% to +37%); MAPE = 11.4%]. CONCLUSIONS: The linear equation gives a relatively good estimation of CLU based on P concentrations, making PK-based carboplatin dose adaptation possible for centers without ultrafiltration facilities.

Population Pharmacokinetics of Gemcitabine and dFdU in Pancreatic Cancer Patients Using an Optimal Design, Sparse Sampling Approach.

BACKGROUND: Gemcitabine remains a pillar in pancreatic cancer treatment. However, toxicities are frequently observed. Dose adjustment based on therapeutic drug monitoring might help decrease the occurrence of toxicities. In this context, this work aims at describing the pharmacokinetics (PK) of gemcitabine and its metabolite dFdU in pancreatic cancer patients and at identifying the main sources of their PK variability using a population PK approach, despite a sparse sampled-population and heterogeneous administration and sampling protocols. METHODS: Data from 38 patients were included in the analysis. The 3 optimal sampling times were determined using KineticPro and the population PK analysis was performed on Monolix. Available patient characteristics, including cytidine deaminase (CDA) status, were tested as covariates. Correlation between PK parameters and occurrence of severe hematological toxicities was also investigated. RESULTS: A two-compartment model best fitted the gemcitabine and dFdU PK data (volume of distribution and clearance for gemcitabine: V1 = 45 L and CL1 = 4.03 L/min; for dFdU: V2 = 36 L and CL2 = 0.226 L/min). Renal function was found to influence gemcitabine clearance, and body surface area to impact the volume of distribution of dFdU. However, neither CDA status nor the occurrence of toxicities was correlated to PK parameters. CONCLUSIONS: Despite sparse sampling and heterogeneous administration and sampling protocols, population and individual PK parameters of gemcitabine and dFdU were successfully estimated using Monolix population PK software. The estimated parameters were consistent with previously published results. Surprisingly, CDA activity did not influence gemcitabine PK, which was explained by the absence of CDA-deficient patients enrolled in the study. This work suggests that even sparse data are valuable to estimate population and individual PK parameters in patients, which will be usable to individualize the dose for an optimized benefit to risk ratio.

Metronomic reloaded: Theoretical models bringing chemotherapy into the era of precision medicine.

Oncology has benefited from an increasingly growing number of groundbreaking innovations over the last decade. Targeted therapies, biotherapies, and the most recent immunotherapies all contribute to increase the number of therapeutic options for cancer patients. Consequently, substantial improvements in clinical outcomes for some disease with dismal prognosis such as lung carcinoma or melanoma have been achieved. Of note, the latest innovations in targeted therapies or biotherapies do not preclude the use of standard cytotoxic agents, mostly used in combination. Importantly, and despite the rise of bioguided (a.k.a. precision) medicine, the administration of chemotherapeutic agents still relies on the maximum tolerated drug (MTD) paradigm, a concept inherited from theories conceptualized nearly half a century ago. Alternative dosing schedules such as metronomic regimens, based upon the repeated and regular administration of low doses of chemotherapeutic drugs, and adaptive therapy (i.e. modulating the dose and frequency of cytotoxics administration to control disease progression rather than eradicate it at all cost) have emerged as possible strategies to improve response rates while reducing toxicities. The recent changes in paradigm in the way we theorize cancer biology and evolution, metastatic spreading and tumor ecology, alongside the recent advances in the field of immunotherapy, have considerably strengthened the interest for these alternative approaches. This paper aims at reviewing the recent evolutions in the field of theoretical biology of cancer and computational oncology, with a focus on the consequences these changes have on the way we administer chemotherapy. Here, we advocate for the development of model-guided strategies to refine doses and schedules of chemotherapy administration in order to achieve precision medicine in oncology.

A phase Ia/Ib clinical trial of metronomic chemotherapy based on a mathematical model of oral vinorelbine in metastatic non-small cell lung cancer and malignant pleural mesothelioma: rationale and study protocol.

BACKGROUND: Metronomic oral vinorelbine is effective in metastatic NSCLC and malignant pleural mesothelioma, but all the studies published thus far were based upon a variety of empirical and possibly suboptimal schedules, with inconsistent results. Mathematical modelling showed by simulation that a new metronomic protocol could lead to a better safety and efficacy profile. DESIGN: This phase Ia/Ib trial was designed to confirm safety (phase Ia) and evaluate efficacy (phase Ib) of a new metronomic oral vinorelbine schedule. Patients with metastatic NSCLC or malignant pleural mesothelioma in whom standard treatments failed and who exhibited ECOG performance status 0-2 and adequate organ function will be eligible. Our mathematical PK-PD model suggested an alternative weekly D1, D2 and D4 schedule (named Vinorelbine Theoretical Protocol) with a respective dose of 60, 30 and 60 mg. Trial recruitment will be two-staged, as 12 patients are planned to participate in phase Ia to confirm safety and consolidate the calibration of the model parameters. Depending on the phase Ia results and after a favourable decision from a consultative committee, the extension phase (phase Ib) will be an efficacy study including 20 patients who will receive the Optimal Vinorelbine Theoretical Protocol. The primary endpoint is the tolerance (assessed by CTC v4.0) for the phase Ia and the objective response according to RECIST 1.1 for phase Ib. An ancillary study on circulating angiogenesis biomarkers will be a subproject of the trial. DISCUSSION: This ongoing trial is the first to prospectively test a mathematically optimized schedule in metronomic chemotherapy. As such, this trial can be considered as a proof-of-concept study demonstrating the feasibility to run a computational-driven protocol to ensure an optimal efficacy/toxicity balance in patients with cancer. TRIAL REGISTRATION: EudraCT N°: 2015-000138-31.

Beating the odds: efficacy and toxicity of dihydropyrimidine dehydrogenase-driven adaptive dosing of 5-FU in patients with digestive cancer.

AIMS: 5-FU is the backbone of most regimens in digestive oncology. Administration of standard 5-FU leads to 15-30% of severe side effects, and lethal toxicities are regularly reported with fluoropyrimidine drugs. Dihydropyrimidine dehydrogenase (DPD) deficiency is a pharmacogenetic syndrome responsible for most cases of life-threatening toxicities upon 5-FU intake, and pre-treatment checking for DPD status should help to reduce both incidence and severity of side effects through adaptive dosing strategies. METHODS: We have used a simple method for rapidly establishing the DPD phenotype of patients with cancer and used it prospectively in 59 routine patients treated with 5-FU-based therapy for digestive cancers. No patient with total DPD deficiency was found but 23% of patients exhibited poor metabolizer phenotype, and one patient was phenotyped as profoundly deficient. Consequently, 5-FU doses in poor metabolizer patients were cut by an average 35% as compared with non deficient patients (2390 ± 1225 mg vs. 3653 ± 1371 mg, P < 0.003, t-test). RESULTS: Despite this marked reduction in 5-FU dosing, similar efficacy was achieved in the two subsets (clinical benefit: 40 vs. 43%, stable disease: 40 vs. 37%, progressive disease: 20% in both subsets, P = 0.893, Pearson's chi-square). No difference in toxicities was observed (P = 0.104, Fisher's exact test). Overall, only 3% of early severe toxicities were recorded, a value markedly lower than the 15-30% ones usually reported with 5-FU. CONCLUSIONS: This feasibility study shows how simplified DPD-based adaptive dosing of 5-FU can reduce sharply the incidence of treatment-related severe toxicities while maintaining efficacy as part of routine clinical practice in digestive oncology.

Lethal toxicity after administration of azacytidine: implication of the cytidine deaminase-deficiency syndrome.

Azacytidine, an antimetabolite with an original epigenetic mechanism of action, increases survival in patients diagnosed with high-risk myelodysplasic syndromes or acute myeloid leukemia with less than 30% medullar blasts. Azacytidine is a pyrimidine derivative that undergoes metabolic detoxification driven by cytidine deaminase (CDA), a liver enzyme whose gene is prone to genetic polymorphism, leading to erratic activity among patients. Clinical reports have shown that patients with the poor metabolizer (PM) phenotype are likely to experience early severe or lethal toxicities when treated with nucleosidic analogs such as gemcitabine or cytarabine. No clinical data have been available thus far on the relationships between CDA PM status and toxicities in azacytidine-treated patients. Here, we measured CDA activity in a case of severe toxicities with fatal outcome in a patient undergoing standard azacytidine treatment. Results showed that the patient was PM (i.e. residual activity reduced by 63%), thus suggesting that an impaired detoxification step could have given rise to the lethal toxicities observed. This case report calls for further prospective studies investigating the exact role that CDA status plays in the clinical outcome of patients treated with azacytidine.

Recipient/donor contradictory genotypes with impact on drug pharmacogenetics after liver transplant: a deadly gift?

A 5-year-old girl who had undergone liver transplantation was scheduled for treatment with high-dose cytarabine for a Burkitt lymphoma. Because of impaired transplantation, a study of cytidine deaminase (CDA), the liver enzyme responsible for cytarabine detoxification, was conducted before initiating treatment to evaluate the risk for toxicity in this patient. The CDA genotype and phenotype were both studied and showed none of the polymorphisms usually associated with impaired CDA, but surprisingly functional deficiency was observed. Despite a subsequent 30% reduction in cytarabine dosing, life-threatening toxicities appeared quickly and treatment was discontinued. Further genetic investigations performed on liver biopsy showed that the donor was actually homozygous for CDA*2, a genotype associated with severe CDA deficiency. On the basis of the liver genotype, treatment was resumed with further dose reduction, which led to a better tolerance. This case report highlights the limits of searching germline polymorphisms in patients with liver transplant when the story plays in the liver.

Biodistribution, tumor uptake and efficacy of 5-FU-loaded liposomes: why size matters.

PURPOSE: We have investigated the impact of particle size on the biodistribution, tumor uptake and antiproliferative efficacy of 5-FU-loaded liposomes. METHODS: Three different batches of pegylated liposomes varying in size (i.e., 70, 120 and 250 nm respectively) were tested. The active compounds encapsulated were an equimolar mix of 5-FU, 2'-deoxyinosine and folinic acid. Liposomes were subsequently tested on the human breast cancer model MDA231 cells, a model previously found to be resistant to 5-FU. In vitro, antiproliferative efficacy and microscopy studies of liposomes uptake were carried out. In vivo, comparative biodistribution and efficacy studies were performed in tumor-bearing mice. RESULTS: Difference in size did not change in vitro antiproliferative activity. Fluorescence-Microscopy studies showed that liposomes were mainly uptaken by tumor cells through a direct internalization process, regardless of their size. Biodistribution profiles in tumor-bearing mice revealed higher accumulation of small liposomes in tumors throughout time as compared with normal and large liposomes (p < 0.05). Additionally, we observed that the bigger were the tumors, the more vascularised they were and the greater was the difference in accumulation between small and large liposomes. Consequently, in vivo efficacy studies showed at study conclusion that a 68% reduction in tumor size was achieved with small liposomes (p < 0.05), whereas larger liposomes failed to reduce significantly tumor growth. Similarly, at study conclusion a trend towards higher survival-rate in animals treated with smaller liposomes was observed. CONCLUSION: This study suggests that particle size is critical to achieve higher selectivity and efficacy in experimental oncology, including in resistant tumors.

Overcoming immuno-resistance by rescheduling anti-VEGF/cytotoxics/anti-PD-1 combination in lung cancer model.

Background: Many tumors are refractory to immune checkpoint inhibitors, but their combination with cytotoxics is expected to improve sensitivity. Understanding how and when cytotoxics best re-stimulate tumor immunity could help overcome resistance to immune checkpoint inhibitors. Methods: In vivo studies were performed in C57BL/6 mice grafted with immune-refractory LL/2 lung cancer model. A longitudinal immunomonitoring study on tumor, spleen, and blood after multiple treatments including Cisplatin, Pemetrexed, and anti-VEGF, either alone or in combination, was performed, spanning a period of up to 21 days, to determine the optimal time window during which immune checkpoint inhibitors should be added. Finally, an efficacy study was conducted comparing the antiproliferative performance of various schedules of anti-VEGF, Pemetrexed-Cisplatin doublet, plus anti-PD-1 (i.e., immunomonitoring-guided scheduling, concurrent dosing or a random sequence), as well as single agent anti-PD1. Results: Immunomonitoring showed marked differences between treatments, organs, and time points. However, harnessing tumor immunity (i.e., promoting CD8 T cells or increasing the T CD8/Treg ratio) started on D7 and peaked on D14 with the anti-VEGF followed by cytotoxics combination. Therefore, a 14-day delay between anti-VEGF/cytotoxic and anti-PD1 administration was considered the best sequence to test. Efficacy studies then confirmed that this sequence achieved higher antiproliferative efficacy compared to other treatment modalities (i.e., -71% in tumor volume compared to control). Conclusions: Anti-VEGF and cytotoxic agents show time-dependent immunomodulatory effects, suggesting that sequencing is a critical feature when combining these agents with immune checkpoint inhibitors. An efficacy study confirmed that sequencing treatments further enhance antiproliferative effects in lung cancer models compared to concurrent dosing and partly reverse the resistance to cytotoxics and anti-PD1.