Analysis of data from the PALOMA-3 trial confirms the efficacy of palbociclib and offers alternatives for novel assessment of clinical trials.

PURPOSE: There remains a need for novel therapies for patients with metastatic breast cancer (MBC). We explore the use of a novel biomarker of survival that could potentially expedite the testing of novel therapies. METHODS: We applied a tumor regression-growth model to radiographic measurement data from 393 women with MBC enrolled in PALOMA-3 examining efficacy of palbociclib in disease that had progressed on previous endocrine therapy. 261 and 132 women were randomized to fulvestrant plus palbociclib or placebo, respectively. We estimated rates of regression (d) and growth (g) of the sensitive and resistant fractions of tumors, respectively. We compared the median g of both arms. We examined the relationship between g and progression-free and overall survival (OS). RESULTS: As in other tumors, g is a biomarker of OS. In PALOMA-3, we found significant differences in g among patients with tumors sensitive to endocrine therapy but not amongst resistant tumors, emulating clinical trial results. Subgroup analysis found favorable g values in visceral metastases treated with palbociclib. Palbociclib efficacy demonstrated by slower g values was evident early in the trial, twelve weeks after the first 28 patients had been enrolled. CONCLUSION: Values of g, estimated using data collected while a patient is enrolled in a clinical trial is an excellent biomarker of OS. Our results correlate with the survival outcomes of PALOMA-3 and argue strongly for using g as a clinical trial endpoint to help inform go/no-go decisions, improve trial efficiency, and deliver novel therapies to patients sooner.

PARP inhibitors: A review of the pharmacology, pharmacokinetics, and pharmacogenetics.

PARP inhibitors have emerged as a promising class of anticancer agents approved for the treatment of ovarian, breast, prostate, and pancreatic cancer. These inhibitors target PARP enzymes involved in DNA repair pathways and exhibit remarkable efficacy in cancers with genetic deficiencies in the homologous recombination pathway responsible for mending DNA double-strand breaks. While all PARP inhibitors demonstrate potent and selective inhibition of PARP1 and PARP2, the key enzymes involved in DNA repair, each agent within the class possesses unique pharmacological profiles distinguishing them from one another. This review aims to comprehensively examine the properties of the entire PARP inhibitor class while emphasizing individual pharmacologic and pharmacokinetic distinctions that inform clinical recommendations. Currently, four agents, namely olaparib, rucaparib, niraparib, and talazoparib, have obtained approval in the United States and Europe. Olaparib, the first approved PARP inhibitor, has been extensively studied and is indicated for a wider range of cancer types. Niraparib and talazoparib, the more recent additions to the PARP inhibitor class, possess the longest half-lives and are formulated for convenient once-daily dosing, alleviating the pill burden for patients when compared to older agents. Moreover, talazoparib undergoes minimal hepatic metabolism, reducing the potential for drug-drug interactions. Notably, niraparib is the sole PARP inhibitor recommended for dose reduction in hepatically impaired populations, whereas talazoparib and olaparib should be dose reduced in renally impaired populations. The mechanisms underlying these dose adjustment recommendations are further explored in this review. Additionally, this review briefly covers veliparib, a PARP inhibitor under development, and two recently approved PARP inhibitors in China, fuzuloparib and pamiparib. Although significant progress has been made in understanding PARP inhibitors, there are several unanswered questions that remain, necessitating further research across a broader spectrum of cancer types within this evolving class of anticancer agents.

Modeling Tumor Growth Using Partly Conditional Survival Models: A Case Study in Colorectal Cancer.

PURPOSE: There are multiple approaches to modeling the relationship between longitudinal tumor measurements obtained from serial imaging and overall survival. Many require strong assumptions that are untestable and debatable. We illustrate how to apply a novel, more flexible approach, the partly conditional (PC) survival model, using images acquired during a phase III, randomized clinical trial in colorectal cancer as an example. METHODS: PC survival approaches were used to model longitudinal volumetric computed tomography data of 1,025 patients in the completed VELOUR trial, which evaluated adding aflibercept to infusional fluorouracil, leucovorin, and irinotecan for treating metastatic colorectal cancer. PC survival modeling is a semiparametric approach to estimating associations of longitudinal measurements with time-to-event outcomes. Overall survival was our outcome. Covariates included baseline tumor burden, change in tumor burden from baseline to each follow-up time, and treatment. Both unstratified and time-stratified models were investigated. RESULTS: Without making assumptions about the distribution of the tumor growth process, we characterized associations between the change in tumor burden and survival. This change was significantly associated with survival (hazard ratio [HR], 1.04; 95% CI, 1.02 to 1.05; P < .001), suggesting that aflibercept works at least in part by altering the tumor growth trajectory. We also found baseline tumor size prognostic for survival even when accounting for the change in tumor burden over time (HR, 1.02; 95% CI, 1.01 to 1.02; P < .001). CONCLUSION: The PC modeling approach offers flexible characterization of associations between longitudinal covariates, such as serially assessed tumor burden, and survival time. It can be applied to a variety of data of this nature and used as clinical trials are ongoing to incorporate new disease assessment information as it is accumulated, as indicated by an example from colorectal cancer.

Requirements for Meaningful Progress in the Therapy of Neuroendocrine Cancers.

This Viewpoint discusses the role of data interpretation and clinical trial design in improving therapy of neuroendocrine cancers.

Cancer medicines on the WHO Model List of Essential Medicines: processes, challenges, and a way forward.

The selection of cancer medicines for national procurement requires deliberate evaluation of population benefit, budget impact, sustainability, and health system capacity. However, this process is complicated by numerous challenges, including the large volume and rapid pace of newly developed therapies offering marginal gains at prohibitively high prices. The WHO Model List of Essential Medicines (EML) and Model List of Essential Medicines for Children (EMLc) have undergone a series of evidence-based updates to ensure recommended cancer medicines offer meaningful clinical benefit. This Health Policy paper describes how cancer medicines are listed on the EML and EMLc, including two updated WHO processes: (1) the formation of the Cancer Medicines Working Group, and (2) additional selection principles for recommending cancer medicines, including a minimum overall survival benefit of 4-6 months with improvement to quality of life compared with standard treatment. These updates, along with proposals to include formal price considerations, additional selection criteria, and multisectoral collaboration (eg, voluntary licensing) promote procurement of high-value essential cancer medicines on national formularies in the context of supporting sustainable health systems to achieve universal health coverage.

Long-term follow-up experience with adjuvant therapy after irreversible electroporation of locally advanced pancreatic cancer.

BACKGROUND: Irreversible electroporation (IRE) expands the surgical options for patients with unresectable pancreatic cancer. This study evaluated for differences in survival stratified by type of IRE and receipt of adjuvant chemotherapy. METHODS: Patients with locally advanced pancreatic cancer treated by IRE (2012-2020) were retrospectively included. Overall survival (OS) and recurrence-free survival (RFS) were compared by type of IRE (in situ for local tumor control or IRE of potentially positive margins with resection) and by receipt of adjuvant chemotherapy. RESULTS: Thirty-nine patients had IRE in situ, 61 had IRE for margin extension, and 19 received adjuvant chemotherapy. Most (97.00%) underwent induction chemotherapy. OS was 28.71 months (interquartile range [IQR] 19.17, 51.19) from diagnosis, with no difference by IRE type (hazard ratio [HR] 1.05 for margin extension [p = 0.85]) or adjuvant chemotherapy (HR 1.14 [p = 0.639]). RFS was 8.51 months (IQR 4.95, 20.17) with no difference by IRE type (HR 0.90 for margin extension [p = 0.694]) or adjuvant chemotherapy (HR 0.90 [p = 0.711]). CONCLUSION: These findings suggest that adjuvant therapy may have limited benefit for patients treated with induction chemotherapy followed by local control with IRE for unresectable pancreatic cancer. Further study of the duration and timing of systemic therapy is warranted to maximize benefit and limit toxicity.

R-Loop-Mediated ssDNA Breaks Accumulate Following Short-Term Exposure to the HDAC Inhibitor Romidepsin.

Histone deacetylase inhibitors (HDACi) induce hyperacetylation of histones by blocking HDAC catalytic sites. Despite regulatory approvals in hematological malignancies, limited solid tumor clinical activity has constrained their potential, arguing for better understanding of mechanisms of action (MOA). Multiple activities of HDACis have been demonstrated, dependent on cell context, beyond the canonical induction of gene expression. Here, using a clinically relevant exposure duration, we established DNA damage as the dominant signature using the NCI-60 cell line database and then focused on the mechanism by which hyperacetylation induces DNA damage. We identified accumulation of DNA-RNA hybrids (R-loops) following romidepsin-induced histone hyperacetylation, with single-stranded DNA (ssDNA) breaks detected by single-cell electrophoresis. Our data suggest that transcription-coupled base excision repair (BER) is involved in resolving ssDNA breaks that, when overwhelmed, evolve to lethal dsDNA breaks. We show that inhibition of BER proteins such as PARP will increase dsDNA breaks in this context. These studies establish accumulation of R-loops as a consequence of romidepsin-mediated histone hyperacetylation. We believe that the insights provided will inform design of more effective combination therapy with HDACis for treatment of solid tumors. IMPLICATIONS: Key HDAC inhibitor mechanisms of action remain unknown; we identify accumulation of DNA-RNA hybrids (R-loops) due to chromatin hyperacetylation that provokes single-stranded DNA damage as a first step toward cell death.

Novel Tumor Growth Rate Analysis in the Randomized CLARINET Study Establishes the Efficacy of Lanreotide Depot/Autogel 120 mg with Prolonged Administration in Indolent Neuroendocrine Tumors.

INTRODUCTION: Tumor quantity while receiving cancer therapy is the sum of simultaneous regression of treatment-sensitive and growth of treatment-resistant fractions at constant rates. Exponential rate constants for tumor regression/decay (d) and growth (g) can be estimated. Previous studies established g as a biomarker for overall survival; g increases after treatment cessation, can estimate doubling times, and can assess treatment effectiveness in small cohorts by benchmarking to large reference data sets. Using this approach, we analyzed data from the clinical trial CLARINET, evaluating lanreotide depot/autogel 120 mg/4 weeks (LAN) for treatment of neuroendocrine tumors (NETs). METHODS AND MATERIALS: Computed tomography imaging data from 97 LAN- and 101 placebo-treated patients from CLARINET were analyzed to estimate g and d. RESULTS: Data from 92% of LAN- and 94% of placebo-treated patients could be fit to one of the equations to derive g and d (p < .001 in most data sets). LAN-treated patients demonstrated significantly slower g than placebo recipients (p = .00315), a difference of 389 days in doubling times. No significant difference was observed in d. Over periods of LAN administration up to 700 days, g did not change appreciably. Simulated analysis with g as the endpoint showed a sample size of 48 sufficient to detect a difference in median g with 80% power. CONCLUSION: Although treatment of NETs with LAN can affect tumor shrinkage, LAN primarily slows tumor growth rather than accelerates tumor regression. Evidence of LAN efficacy across tumors was identified. The growth-retarding effect achieved with LAN was sustained for a prolonged period of time. IMPLICATIONS FOR PRACTICE: The only curative treatment for neuroendocrine tumors (NETs) is surgical resection; however, because of frequent late diagnosis, this is often impossible. Because of this, treatment of NETs is challenging and often aims to reduce tumor burden and delay progression. A novel method of analysis was used to examine data from the CLARINET trial, confirming lanreotide depot/autogel is effective at slowing tumor growth and extending progression-free survival. By providing the expected rate and doubling time of tumor growth early in the course of treatment, this method of analysis has the potential to guide physicians in their management of patients with NETs.

Identification of Non-Small Cell Lung Cancer Sensitive to Systemic Cancer Therapies Using Radiomics.

PURPOSE: Using standard-of-care CT images obtained from patients with a diagnosis of non-small cell lung cancer (NSCLC), we defined radiomics signatures predicting the sensitivity of tumors to nivolumab, docetaxel, and gefitinib. EXPERIMENTAL DESIGN: Data were collected prospectively and analyzed retrospectively across multicenter clinical trials [nivolumab, n = 92, CheckMate017 (NCT01642004), CheckMate063 (NCT01721759); docetaxel, n = 50, CheckMate017; gefitinib, n = 46, (NCT00588445)]. Patients were randomized to training or validation cohorts using either a 4:1 ratio (nivolumab: 72T:20V) or a 2:1 ratio (docetaxel: 32T:18V; gefitinib: 31T:15V) to ensure an adequate sample size in the validation set. Radiomics signatures were derived from quantitative analysis of early tumor changes from baseline to first on-treatment assessment. For each patient, 1,160 radiomics features were extracted from the largest measurable lung lesion. Tumors were classified as treatment sensitive or insensitive; reference standard was median progression-free survival (NCT01642004, NCT01721759) or surgery (NCT00588445). Machine learning was implemented to select up to four features to develop a radiomics signature in the training datasets and applied to each patient in the validation datasets to classify treatment sensitivity. RESULTS: The radiomics signatures predicted treatment sensitivity in the validation dataset of each study group with AUC (95 confidence interval): nivolumab, 0.77 (0.55-1.00); docetaxel, 0.67 (0.37-0.96); and gefitinib, 0.82 (0.53-0.97). Using serial radiographic measurements, the magnitude of exponential increase in signature features deciphering tumor volume, invasion of tumor boundaries, or tumor spatial heterogeneity was associated with shorter overall survival. CONCLUSIONS: Radiomics signatures predicted tumor sensitivity to treatment in patients with NSCLC, offering an approach that could enhance clinical decision-making to continue systemic therapies and forecast overall survival.

Pilot Study Assessing Tolerability and Metabolic Effects of Metformin in Patients With Li-Fraumeni Syndrome.

BACKGROUND: Li-Fraumeni syndrome (LFS) is a highly penetrant autosomal dominant cancer predisposition disorder caused by germline TP53 pathogenic variants. Patients with LFS have increased oxidative phosphorylation capacity in skeletal muscle and oxidative stress in blood. Metformin inhibits oxidative phosphorylation, reducing available energy for cancer cell proliferation and decreasing production of reactive oxygen species that cause DNA damage. Thus, metformin may provide pharmacologic risk reduction for cancer in patients with LFS, but its safety in nondiabetic patients with germline TP53 pathogenic variants has not been documented. METHODS: This study assessed safety and tolerability of metformin in nondiabetic LFS patients and measured changes in metabolic profiles. Adult patients with LFS and germline TP53 variant received 14 weeks of metformin. Blood samples were obtained for measurement of serum insulin-like growth factor-1, insulin, and insulin-like growth factor binding protein 3. Hepatic mitochondrial function was assessed with fasting exhaled CO2 after ingestion of 13C-labeled methionine. Changes in serum metabolome were measured. All statistical tests were 2-sided. RESULTS: We enrolled 26 participants: 20 females and 6 males. The most common adverse events were diarrhea (50.0%) and nausea (46.2%). Lactic acidosis did not occur, and there were no changes in fasting glucose. Cumulative mean 13C exhalation was statistically significantly suppressed by metformin (P = .001). Mean levels of insulin-like growth factor binding protein 3 and insulin-like growth factor-1 were statistically significantly lowered (P = .02). Lipid metabolites and branched-chain amino acids accumulated. CONCLUSIONS: Metformin was safe and tolerable in patients with LFS. It suppressed hepatic mitochondrial function as expected in these individuals. This study adds to the rationale for development of a pharmacologic risk-reduction clinical trial of metformin in LFS.

Progress and Opportunities to Advance Clinical Cancer Therapeutics Using Tumor Dynamic Models.

There is a need for new approaches and endpoints in oncology drug development, particularly with the advent of immunotherapies and the multiple drug combinations under investigation. Tumor dynamics modeling, a key component to oncology "model-informed drug development," has shown a growing number of applications and a broader adoption by drug developers and regulatory agencies in the past years to support drug development and approval in a variety of ways. Tumor dynamics modeling is also being investigated in personalized cancer therapy approaches. These models and applications are reviewed and discussed, as well as the limitations and issues open for further investigations. A close collaboration between stakeholders like clinical investigators, statisticians, and pharmacometricians is warranted to advance clinical cancer therapeutics.

Revisiting the role of ABC transporters in multidrug-resistant cancer.

Most patients who die of cancer have disseminated disease that has become resistant to multiple therapeutic modalities. Ample evidence suggests that the expression of ATP-binding cassette (ABC) transporters, especially the multidrug resistance protein 1 (MDR1, also known as P-glycoprotein or P-gp), which is encoded by ABC subfamily B member 1 (ABCB1), can confer resistance to cytotoxic and targeted chemotherapy. However, the development of MDR1 as a therapeutic target has been unsuccessful. At the time of its discovery, appropriate tools for the characterization and clinical development of MDR1 as a therapeutic target were lacking. Thirty years after the initial cloning and characterization of MDR1 and the implication of two additional ABC transporters, the multidrug resistance-associated protein 1 (MRP1; encoded by ABCC1)), and ABCG2, in multidrug resistance, interest in investigating these transporters as therapeutic targets has waned. However, with the emergence of new data and advanced techniques, we propose to re-evaluate whether these transporters play a clinical role in multidrug resistance. With this Opinion article, we present recent evidence indicating that it is time to revisit the investigation into the role of ABC transporters in efficient drug delivery in various cancer types and at the blood-brain barrier.

SDHB-related pheochromocytoma and paraganglioma penetrance and genotype-phenotype correlations.

PURPOSE: Succinate dehydrogenase subunit B (SDHB) gene mutations are associated with an aggressive clinical disease course of pheochromocytoma/paraganglioma (PHEO/PGL). Limited information is available concerning PHEO/PGL penetrance among SDHB mutation carriers with regards to primary tumor location, specific mutation type, and gender. We assessed PHEO/PGL penetrance in SDHB mutation carriers and described the clinical presentation and disease course. METHODS: Asymptomatic relatives (N = 611) of 103 index patients were tested for SDHB mutations. Mutation carriers (N = 328) were offered PHEO/PGL screening, of which 241 participated and were included in penetrance analysis. For additional disease outcome analysis, the 103 index patients and 40 screened individuals who developed PHEO/PGL were included. Clinical data were collected between October 2004 and June 2016. RESULTS: Forty (16.60%) of the 241 screened individuals developed PHEO/PGL during the study. The penetrance estimate in this population was 49.80% (95% CI 29-74.9) at 85 years. A significantly higher age-related penetrance of disease was observed in males compared to females, with 50% penetrance achieved at age 74 vs. not reached. Age-related penetrance analysis demonstrated 4 mutations (Ile127Ser, IVS1+1G>T, Exon 1 deletion, Arg90X) presenting with a slower rate of disease development (50% penetrance ages, respectively: not achieved, 70, 63, 61 years) compared to Arg46X and Val140Phe mutations (50% penetrance at 38 years). CONCLUSIONS: Here, we found a higher estimated penetrance compared to several other studies, and a striking difference in age-related penetrance between male and female SDHB mutation carriers with no association between mutation and gender or tumor location.