Critical Appraisal and Future Challenges of Artificial Intelligence and Anticancer Drug Development.

The conventional rules for anti-cancer drug development are no longer sufficient given the relatively limited number of patients available for therapeutic trials. It is thus a real challenge to better design trials in the context of new drug approval for anti-cancer treatment. Artificial intelligence (AI)-based in silico trials can incorporate far fewer but more informative patients and could be conducted faster and at a lower cost. AI can be integrated into in silico clinical trials to improve data analysis, modeling and simulation, personalized medicine approaches, trial design optimization, and virtual patient generation. Health authorities are encouraged to thoroughly review the rules for setting up clinical trials, incorporating AI and in silico methodology once they have been appropriately validated. This article also aims to highlight the limits and challenges related to AI and machine learning.

Long-Term Pharmacokinetic Follow-Up of Abiraterone Acetate in Patients with Metastatic Castration-Resistant Prostate Cancer.

This ABIGENE pharmacokinetic (PK) study sought mainly to characterize the unchanged drug PK during long-term abiraterone acetate (AA) administration in advanced prostate cancer patients (81 patients). It was observed that individual AA concentrations remained constant over treatment time, with no noticeable changes during repeated long-term drug administration for up to 120 days. There was no correlation between AA concentrations and survival outcomes. However, a significant association between higher AA concentrations and better clinical benefit was observed (p = 0.041). The safety data did not correlate with the AA PK data. A significant positive correlation (r = 0.40, p < 0.001) was observed between mean AA concentration and patient age: the older the patient, the higher the AA concentration. Patient age was found to impact steady-state AA concentration: the older the patient, the higher the mean AA concentration. Altogether, these data may help to guide future research and clinical trials in order to maximize the benefits of AA metastatic castration-resistant prostate cancer patients.

Molecular and nutritional markers in head and neck cancer.

PURPOSE OF REVIEW: There is still a need of biomarkers in the induction and neoadjuvant settings for squamous cell carcinoma of the head and neck (SCCHN). The objective of this concise review article is to give an overview on both predictive and prognostic biomarkers potentially useful for the management of SCCHN. RECENT FINDINGS: Human papilloma virus (HPV) positivity translated by the presence of the protein indicator p16 is synonymous of favorable prognosis SCCHN. However, there is some disparity for disease evolution among p16 positive SCCHN. A lack of correlation between immunohistochemistry (IHC) and precise quantification of active epidermal growth factor receptors (EGFRs) may explain the absence of link between EGFR expression performed by IHC and response to EGFR targeting therapies reported in SCCHN. Circulating tumor cells (CTCs) have the property to share the main somatic mutations and genetic rearrangements with the primary tumors. A particular potential interest lies on the possibility to predict patient outcome based on a single-CTC analysis. SUMMARY: This short review indicates that key biological marker reflecting disease outcome is not yet emerging for a clinical use in SCCHN. Hopes can be put into the so-called liquid biopsies incorporating circulating tumor cells and circulating tumor DNA.

Artificial Intelligence and Anticancer Drug Development-Keep a Cool Head.

Artificial intelligence (AI) is progressively spreading through the world of health, particularly in the field of oncology. AI offers new, exciting perspectives in drug development as toxicity and efficacy can be predicted from computer-designed active molecular structures. AI-based in silico clinical trials are still at their inception in oncology but their wider use is eagerly awaited as they should markedly reduce durations and costs. Health authorities cannot neglect this new paradigm in drug development and should take the requisite measures to include AI as a new pillar in conducting clinical research in oncology.

Dihydropyrimidine dehydrogenase gene variants for predicting grade 4-5 fluoropyrimidine-induced toxicity: FUSAFE individual patient data meta-analysis.

BACKGROUND: Dihydropyrimidine dehydrogenase (DPD) deficiency is the main known cause of life-threatening fluoropyrimidine (FP)-induced toxicities. We conducted a meta-analysis on individual patient data to assess the contribution of deleterious DPYD variants *2A/D949V/*13/HapB3 (recommended by EMA) and clinical factors, for predicting G4-5 toxicity. METHODS: Study eligibility criteria included recruitment of Caucasian patients without DPD-based FP-dose adjustment. Main endpoint was 12-week haematological or digestive G4-5 toxicity. The value of DPYD variants *2A/p.D949V/*13 merged, HapB3, and MIR27A rs895819 was evaluated using multivariable logistic models (AUC). RESULTS: Among 25 eligible studies, complete clinical variables and primary endpoint were available in 15 studies (8733 patients). Twelve-week G4-5 toxicity prevalence was 7.3% (641 events). The clinical model included age, sex, body mass index, schedule of FP-administration, concomitant anticancer drugs. Adding *2A/p.D949V/*13 variants (at least one allele, prevalence 2.2%, OR 9.5 [95%CI 6.7-13.5]) significantly improved the model (p < 0.0001). The addition of HapB3 (prevalence 4.0%, 98.6% heterozygous), in spite of significant association with toxicity (OR 1.8 [95%CI 1.2-2.7]), did not improve the model. MIR27A rs895819 was not associated with toxicity, irrespective of DPYD variants. CONCLUSIONS: FUSAFE meta-analysis highlights the major relevance of DPYD *2A/p.D949V/*13 combined with clinical variables to identify patients at risk of very severe FP-related toxicity.

Checkpoint inhibitors and anti-angiogenic agents: a winning combination.

The combination of immune checkpoint inhibitors and anti-angiogenic agents is a promising new approach in cancer treatment. Immune checkpoint inhibitors block the signals that help cancer cells evade the immune system, while anti-angiogenic agents target the blood vessels that supply the tumour with nutrients and oxygen, limiting its growth. Importantly, this combination triggers synergistic effects based on molecular and cellular mechanisms, leading to better response rates and longer progression-free survival than treatment alone. However, these combinations can also lead to increased side effects and require close monitoring.

Manipulating the gut and tumor microbiota for immune checkpoint inhibitor therapy: from dream to reality.

The past decade has witnessed a revolution in cancer treatment by shifting from conventional therapies to immune checkpoint inhibitors (ICIs). These immunotherapies unleash the host immune system against the tumor and have achieved unprecedented durable remission. However, 80% of patients do not respond. This review discusses how bacteria are unexpected drivers that reprogram tumor immunity. Manipulating the microbiota impacts on tumor development and reprograms the tumor microenvironment (TME) of mice on immunotherapy. We anticipate that harnessing commensals and the tumor microbiome holds promise to identify patients who will benefit from immunotherapy and guide the choice of new ICI combinations to advance treatment efficacy.

Abigene, a Prospective, Multicentric Study of Abiraterone Acetate Pharmacogenetics in Metastatic Castration-Resistant Prostate Cancer.

Abiraterone acetate (AA) is the first-in-class of drugs belonging to the second-generation of agents inhibiting androgen neosynthesis in advanced prostate cancer. A cumulative experience attests that germinal gene polymorphisms may play a role in the prediction of anticancer agent pharmacodynamics variability. In the present prospective, multicentric study, gene polymorphisms of CYP17A1 (AA direct target) and the androgen transporter genes SLCO2B1 and SLCO1B3 (potential modulators of AA activity) were confronted with AA pharmacodynamics (treatment response and toxicity) in a group of 137 advanced prostate cancer patients treated in the first line by AA. The median follow-up was 56.3 months (95% CI [52.5-61]). From multivariate analysis, rs2486758 C/C (CYP17A1) and PSA (≥10 ng/mL) were associated with a shorter 3-year biological PFS (HR = 4.05, IC95% [1.46-11.22]; p = 0.007 and HR = 2.08, IC95% [1.31-3.30]; p = 0.002, respectively). From a multivariate analysis, the rs743572 (CYP17A1) and performance status were independently associated with significant toxicity (OR = 3.78 (IC95% [1.42-9.75]; p = 0.006 and OR = 4.54; IC95% [1.46-13.61]; p = 0.007, respectively). Host genome characteristics may help to predict AA treatment efficacy and identify patients at risk for toxicity.

Host genetic variability and determinants of severe COVID-19.

Since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak, convergent studies have provided evidence that host genetic background may contribute to the development of severe coronavirus disease (COVID-19). Here, we summarize how some genetic variations, such as in SARS-CoV-2 receptor angiotensin-converting enzyme 2 or interferon signaling pathway, may help to understand why some individuals can develop severe COVID-19.

Checkpoint inhibitors in a marriage: consented or arranged?

There is currently a strong development of therapeutic combinations with checkpoint inhibitors (CPIs). The most promising combinations with CPIs concern anti-angiogenic agents and BRAF/MEK inhibitors. The timing of the initiation of the combination should be particularly well investigated for chemotherapy. Combinations between CPIs raise questions about risk/benefit ratio and overall clinical activity.

Autophagopathies: from autophagy gene polymorphisms to precision medicine for human diseases.

At a time when complex diseases affect globally 280 million people and claim 14 million lives every year, there is an urgent need to rapidly increase our knowledge into their underlying etiologies. Though critical in identifying the people at risk, the causal environmental factors (microbiome and/or pollutants) and the affected pathophysiological mechanisms are not well understood. Herein, we consider the variations of autophagy-related (ATG) genes at the heart of mechanisms of increased susceptibility to environmental stress. A comprehensive autophagy genomic resource is presented with 263 single nucleotide polymorphisms (SNPs) for 69 autophagy-related genes associated with 117 autoimmune, inflammatory, infectious, cardiovascular, neurological, respiratory, and endocrine diseases. We thus propose the term 'autophagopathies' to group together a class of complex human diseases the etiology of which lies in a genetic defect of the autophagy machinery, whether directly related or not to an abnormal flux in autophagy, LC3-associated phagocytosis, or any associated trafficking. The future of precision medicine for common diseases will lie in our ability to exploit these ATG SNP x environment relationships to develop new polygenetic risk scores, new management guidelines, and optimal therapies for afflicted patients.Abbreviations: ATG, autophagy-related; ALS-FTD, amyotrophic lateral sclerosis-frontotemporal dementia; ccRCC, clear cell renal cell carcinoma; CD, Crohn disease; COPD, chronic obstructive pulmonary disease; eQTL, expression quantitative trait loci; HCC, hepatocellular carcinoma; HNSCC, head and neck squamous cell carcinoma; GTEx, genotype-tissue expression; GWAS, genome-wide association studies; LAP, LC3-associated phagocytosis; LC3-II, phosphatidylethanolamine conjugated form of LC3; LD, linkage disequilibrium; LUAD, lung adenocarcinoma; MAF, minor allele frequency; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; NSCLC, non-small cell lung cancer; OS, overall survival; PtdIns3K CIII, class III phosphatidylinositol 3 kinase; PtdIns3P, phosphatidylinositol-3-phosphate; SLE, systemic lupus erythematosus; SNPs, single-nucleotide polymorphisms; mQTL, methylation quantitative trait loci; ULK, unc-51 like autophagy activating kinase; UTRs, untranslated regions; WHO, World Health Organization.

Liposomal irinotecan (Onivyde): Exemplifying the benefits of nanotherapeutic drugs.

Irinotecan is a topoisomerase inhibitor, widely used in treatment of malignancies including pancreatic ductal adenocarcinoma (PDAC) as part of the FOLFIRINOX regimen prescribed as a first-line treatment in several countries. However, irinotecan has not been successfully introduced as a second-line treatment for pancreatic cancer and few randomized clinical studies have evaluated its added value. Efficacy of liposomal irinotecan (nal-IRI) combined with 5-fluorouracil and leucovorin (5-FU/LV) was reported in the phase III NAPOLI-1 trial in metastatic PDAC following failure of gemcitabine-based therapy. Several features of nal-IRI pharmacokinetics (PK) could result in better outcomes versus nonliposomal irinotecan. Irinotecan is a prodrug that is converted to active SN-38 by carboxylesterase enzymes and inactivated by cytochrome P450 3A4/3A5. SN-38 is inactivated by UGT1A1 enzymes. Individual variations in their expression and activity could influence enhanced localized irinotecan activity and toxicity. Liposomal irinotecan exploits the enhanced permeability and retention effect in cancer, accumulating in tumor tissues. Liposomal irinotecan also has a longer half-life and higher area under the concentration-time curve (0-∞) than nonliposomal irinotecan, as the liposomal formulation protects cargo from premature metabolism in the plasma. This results in irinotecan activation in tumor tissue, leading to enhanced cytotoxicity. Importantly, despite the longer exposure, overall toxicity for nal-IRI is no worse than nonliposomal irinotecan. Liposomal irinotecan exemplifies how liposomal encapsulation of a chemotherapeutic agent can alter its PK properties, improving clinical outcomes for patients. Liposomal irinotecan is currently under investigation in other malignancies including biliary tract cancer (amongst other gastrointestinal cancers), brain tumors, and small-cell lung cancer.

COVID-19 vaccination and cancer immunotherapy: should they stick together?

The combination of COVID-19 vaccination with immunotherapy by checkpoint inhibitors in cancer patients could intensify immunological stimulation with potential reciprocal benefits. Here, we examine more closely the possible adverse events that can arise in each treatment modality. Our conclusion is that caution should be exercised when combining both treatments.

Myocarditis and COVID-19 mRNA vaccines: a mechanistic hypothesis involving dsRNA.

While tolerance to COVID-19 vaccination is considered satisfactory, a phenomenon of myocarditis, although rare, is becoming a safety concern in mRNA COVID-19 vaccination. The presence of low residual levels of double-strand RNA (dsRNA) has been reported in mRNA COVID-19 vaccine preparations. dsRNA is a known inducer of immune-inflammatory reactions. dsRNA present in vaccine nanoparticles may be suspected to be at the origin of the still unexplained cases of myocarditis.

TAXOMET: A French Prospective Multicentric Randomized Phase II Study of Docetaxel Plus Metformin Versus Docetaxel Plus Placebo in Metastatic Castration-Resistant Prostate Cancer.

BACKGROUND: Docetaxel (DOCE) is a standard of care in metastatic castration-resistant prostate cancer (mCRPC). Several retrospective studies suggested a decrease in Prostate Cancer incidence and mortality with metformin (MET). MET has also demonstrated anti-tumor activity in Prostate Cancer preclinical models, with increased apoptosis when added to DOCE. We aimed at exploring the role of MET in combination with DOCE in mCRPC. PATIENTS AND METHODS: Non-diabetic mCRPC patients were randomly assigned to receive DOCE 75 mg/m2 every 21 days + prednisone (5 mg. BID) with either MET 850 mg BID (D+M) or placebo (D+P) up to 10 cycles. Prostate-Specific Antigen (PSA) response ≥50% from baseline was the primary end point. Secondary end points included objective response rate (ORR), progression-free survival (PFS), overall survival (OS), toxicity and quality of life (QoL). RESULTS: Out of 99 patients were randomized (D+M = 50; D+P = 49) in 10 French centers. The median follow-up was 86 (IQR 73-88) months. The PSA-response rate reached 66% in the D+M arm, but was not different from that observed in the D+P arm (63%, P = 0,94). In the D+M and D+P arms, the ORR was 28% and 24%, the median PFS was 7.8 and 6.0 months and the median OS was 27 and 20 months (ns), respectively. Diarrhea grade I to II was more frequent in the MET arm (66% vs. 43%). No impairment of QoL was observed. CONCLUSION: MET addition failed to improve the standard DOCE regimen in mCRPC. Further research targeting tumor cell metabolism should be performed.

PD-L1 regulation revisited: impact on immunotherapeutic strategies.

A particularly promising cancer treatment is the use of monoclonal antibodies (mAbs) against immune checkpoints (i.e., immune checkpoint inhibitors; ICIs). However, many patients experience relapse and severe adverse events. To overcome these negative issues and improve efficiency, current approaches rely on combinatorial treatments, including some modulating the expression of programmed cell death receptor 1 (PD-1)/programmed death ligand 1 (PD-L1) immune checkpoints directly. In this review, we examine the recently discovered pathways involved in PD-L1 expression and highlight the relevant druggable strategies that are being developed to both improve the response rate and avoid the onset of resistance. Altogether, these new strategies will pave the way for effective treatment combinations in future oncology clinical trials.

More light on cancer and COVID-19 reciprocal interaction.

Cancer patients are vulnerable to COVID-19 with consequences on treatment delays and on mortality rate. This Comment explores the interaction between COVID-19 and cancer with attention paid to the modulation by cancer treatments of both ADAM17 and TMPRSS2, the proteases which control ACE2 processing, the SARS-CoV-2 target.

Population pharmacokinetic and pharmacodynamic modeling of capecitabine and its metabolites in breast cancer patients.

PURPOSE: The present study was performed to examine relationships between systemic exposure of capecitabine metabolites (5-FU, 5'-DFCR and 5'-DFUR) and toxicity or clinical response in patients with metastatic breast cancer. METHODS: A population pharmacokinetic model for capecitabine and its three metabolites was built. Typical parameter values, characteristics of random distributions, associated with parameters, and covariates impact were estimated. Area under the curve (AUC) were computed for 5-FU and compared with grades of toxicity. Pharmacokinetic modeling was based on data collected on the first treatment cycle. Toxicity was assessed on the two first treatment cycles. RESULTS: The study was conducted in 43 patients. The population pharmacokinetic model (a one-compartment model per compound) was able to capture the very complex absorption process of capecitabine. Statistically significant covariates were cytidine deaminase, alkaline phosphatase and dihydrouracilemia (UH2)/uracilemia (U) ratio. UH2/U ratio was the most significant covariate on 5-FU elimination and CDA on the transformation of 5'-DFCR in 5'-DFUR. A trend was observed between 5-FU AUC and thrombopenia toxicity grades, but not with other toxicities. Best clinical response was not linked to systemic exposure of capecitabine metabolites. CONCLUSION: In our study, we propose a model able to describe, meanwhile, and its main metabolites, with a complex absorption process and inclusion of enzyme activity covariates such as CDA and UH2/U ratio. Trial registration Eudract 2008-004136-20, 2008/11/26.