Dataset Information

Tumor growth rate determines the timing of optimal chronomodulated treatment schedules.

ABSTRACT: In host and cancer tissues, drug metabolism and susceptibility to drugs vary in a circadian (24 h) manner. In particular, the efficacy of a cell cycle specific (CCS) cytotoxic agent is affected by the daily modulation of cell cycle activity in the target tissues. Anti-cancer chronotherapy, in which treatments are administered at a particular time each day, aims at exploiting these biological rhythms to reduce toxicity and improve efficacy of the treatment. The circadian status, which is the timing of physiological and behavioral activity relative to daily environmental cues, largely determines the best timing of treatments. However, the influence of variations in tumor kinetics has not been considered in determining appropriate treatment schedules. We used a simple model for cell populations under chronomodulated treatment to identify which biological parameters are important for the successful design of a chronotherapy strategy. We show that the duration of the phase of the cell cycle targeted by the treatment and the cell proliferation rate are crucial in determining the best times to administer CCS drugs. Thus, optimal treatment times depend not only on the circadian status of the patient but also on the cell cycle kinetics of the tumor. Then, we developed a theoretical analysis of treatment outcome (TATO) to relate the circadian status and cell cycle kinetic parameters to the treatment outcomes. We show that the best and the worst CCS drug administration schedules are those with 24 h intervals, implying that 24 h chronomodulated treatments can be ineffective or even harmful if administered at wrong circadian times. We show that for certain tumors, administration times at intervals different from 24 h may reduce these risks without compromising overall efficacy.

SUBMITTER: Bernard S

PROVIDER: S-EPMC2841621 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Tumor growth rate determines the timing of optimal chronomodulated treatment schedules.

Bernard Samuel S Cajavec Bernard Branka B Lévi Francis F Herzel Hanspeter H

PLoS computational biology 20100319 3

In host and cancer tissues, drug metabolism and susceptibility to drugs vary in a circadian (24 h) manner. In particular, the efficacy of a cell cycle specific (CCS) cytotoxic agent is affected by the daily modulation of cell cycle activity in the target tissues. Anti-cancer chronotherapy, in which treatments are administered at a particular time each day, aims at exploiting these biological rhythms to reduce toxicity and improve efficacy of the treatment. The circadian status, which is the timi ...[more]

PMID: 20333244

Similar Datasets

Project description:BACKGROUND:For pancreatic adenocarcinoma (PDAC), no studies have established any association between earlier treatment initiation and long-term outcomes. In addition, an optimal type of initial treatment for the localized disease remains ill-defined. METHODS:Patients in the National Cancer Database (2004-2015) with clinical stage I (CS-I) and II (CS-II) PDAC who underwent curative-intent resection were included. Optimal time from diagnosis-to-treatment including neoadjuvant chemotherapy, neoadjuvant chemoradiation, or upfront surgery was assessed. An optimal type of treatment was evaluated. The primary outcome was overall survival (OS). RESULTS:Among 29 167 patients, starting any treatment within 0 to 6 weeks was associated with improved median OS compared with 7 to 12 weeks (21.0 vs 20.1 months; P = .004). This persisted when accounting for sex, race, and Charlson-Deyo score (hazard ratio [HR], 0.94; P = 0.02) and on subset analysis for CS-I (23.5 vs 21.8 months; P = .04) and CS-II (19.4 vs 18.3 months; P = .03). Neoadjuvant chemotherapy was associated with improved OS compared with neoadjuvant chemoradiation (25.6 vs 22.7 months; P < .0001) or US (25.6 vs 20.1 months; P < .0001) even when accounting for sex, race, and Charlson-Deyo score (neoadjuvant chemoradiation: HR, 0.86; P < .001; US: HR, 0.79; P < .001). This improvement persisted in subset analysis with NC compared with neoadjuvant chemoradiation (CS-I: 28.6 vs 25.0 months; CS-II: 25.0 vs 22.9 months; both P < .0001) and to US (CS-I: 28.6 vs 22.9 months; CS-II: 24.7 vs 18.4 months; both P < .0001). On multivariable analysis for each CS-I/CS-II, NC remained associated with 20% improved survival compared with neoadjuvant chemoradiation or upfront surgery. CONCLUSIONS:For PDAC, initiation of therapy within 6 weeks from diagnosis is associated with improved survival, with neoadjuvant chemotherapy associated with the best survival compared with neoadjuvant chemoradiation or upfront surgery.

Project description:BackgroundTumor growth rate (TGR), denoted as percentage change in tumor size per month, is a well-established indicator of tumor growth kinetics. The predictive value of early on-treatment TGR (EOT-TGR) for immunotherapy remains unclear. We sought to establish and validate the association of EOT-TGR with treatment outcomes in patients with advanced non-small-cell lung cancer (aNSCLC) undergoing anti-PD-1/PD-L1 (programmed cell death protein 1/programmed death-ligand 1) therapy.Patients and methodsThis bicenter retrospective cohort study included a training cohort, a contemporaneously treated internal validation cohort, and an external validation cohort. Computed tomography images were retrieved to calculate EOT-TGR, denoted as tumor burden change per month during a period between baseline and the first imaging evaluation after immunotherapy. Kaplan-Meier methodology and Cox regression analysis were conducted for survival analyses.ResultsIn the pooled cohort (n = 172), 125 patients (72.7%) were males; median age at diagnosis was 58 (range 28-79) years. Based on the training cohort, we determined the optimal cut-off value for EOT-TGR as 10.4%/month. Higher EOT-TGR was significantly associated with inferior overall survival [OS; hazard ratio (HR) 2.93, 95% confidence interval (CI) 1.47-5.83; P = 0.002], worse progression-free survival (PFS; HR 2.44, 95% CI 1.46-4.08; P = 0.001), and lower objective response rate (3.3% versus 20.9%; P = 0.040) and durable clinical benefit rate (6.7% versus 41.9%; P = 0.001). Results were reproducible in the two validation cohorts for OS and PFS. Among 43 patients who had a best response of progressive disease in the training cohort, those with high EOT-TGR had worse OS (HR 2.64; P = 0.041) and were more likely to progress due to target lesions at the first tumor evaluation (85.2% versus 0.0%; P <0.001).ConclusionsHigher EOT-TGR was associated with inferior OS and immunotherapeutic response in patients with aNSCLC undergoing anti-PD-1/PD-L1 therapy. This easy-to-calculate radiologic biomarker may help evaluate the abilities of immunotherapy to prolong survival and assist in tailoring patients' management.Trial registrationClinicalTrials.govNCT04722406; https://clinicaltrials.gov/ct2/show/NCT04722406.

Dataset Information

Tumor growth rate determines the timing of optimal chronomodulated treatment schedules.

Publications

Tumor growth rate determines the timing of optimal chronomodulated treatment schedules.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets