Prostate cancer is globally the second most commonly diagnosed cancer type in men.Recent studies suggest that mutations in DNA repair genes are associated with aggressive forms ofprostate cancer and castration resistance. Prostate cancer with DNA repair defects may bevulnerable to therapeutic targeting by Poly(ADP‐ribose) polymerase (PARP) inhibitors. PARPenzymes modify target proteins with ADP‐ribose in a process called PARylation and are inparticular involved in single strand break repair. The rationale behind the clinical trials that led tothe current use of PARP inhibitors to treat cancer was to target the dependence of BRCA‐mutantcancer cells on the PARP‐associated repair pathway due to deficiency in homologousrecombination. However, recent studies have proposed therapeutic potential for PARP inhibitorsin tumors with a variety of vulnerabilities generating dependence on PARP beyond the syntheticlethal targeting of BRCA1/BRCA2 mutated tumors, suggesting a wider potential than initiallythought. Importantly, PARP‐associated DNA repair pathways are also closely connected toandrogen receptor (AR) signaling, which is a key regulator of tumor growth and a centraltherapeutic target in prostate cancer. In this review, we provide an extensive overview of publishedand ongoing trials exploring PARP inhibitors in treatment of prostate cancer and discuss theunderlying biology. Several clinical trials are currently studying PARP inhibitor mono‐andcombination therapies in the treatment of prostate cancer. Integration of drugs targeting DNArepair pathways in prostate cancer treatment modalities allows developing of more personalizedcare taking also into account the genetic makeup of individual tumors.

Background: The effect of post-vaccination adverse events on immunogenicity is unknown. We aimed to explore relationship between post-vaccination adverse reactions and antibody levels during 6-month follow-up. Methods: Blood was serially drawn from healthcare workers after the second dose of BNT162b2 mRNA vaccine (Day 12, 30, 60, 90, 120, 150, and 180) and anti-SARS-CoV-2 spike IgG (S-IgG) levels were measured. Following each vaccine dose, volunteers completed a questionnaire regarding adverse reactions (symptomatic vs. asymptomatic groups). Results: A total of 395 subjects received the second dose of the vaccine. The main results were as follows: (i) fever after the 2nd dose was independently associated with the median S-IgG level at all follow-up time points; (ii) significantly higher S-IgG levels were observed in the symptomatic group of patients without prior COVID-19 infection throughout the entire follow-up period; (iii) prior COVID-19 positivity resulted in higher S-IgG levels only in the asymptomatic group from Day 90 of the follow-up period; (iv) both prior COVID-19 disease with asymptomatic status and symptomatic status without prior COVID-19 infection resulted in similar S-IgG antibody levels; (v) significantly lower serum S-IgG levels were observed in smokers. Conclusion: Fever may play an important role in the post-vaccination immune response in the long term.

Background: Post-COVID manifestation is defined as persistent symptoms or long-term complications beyond 4 weeks from disease onset. Fatigue and memory impairment are common post-COVID symptoms. We aimed to explore associations between the timeline and severity of post-COVID fatigue and anti-SARS-CoV-2 antibodies. Methods: Fatigue and memory impairment were assessed in a total of 101 post-COVID subjects using the Chalder fatigue scale (CFQ-11) and a visual analogue scale. Using the bimodal scoring system generated from CFQ-11, a score ≥4 was defined as severe fatigue. Serum anti-SARS-CoV-2 spike (anti-S-Ig) and nucleocapsid (anti-NC-Ig) antibodies were examined at two time points: 4–12 weeks after onset of symptoms, and beyond 12 weeks. Results: The serum level of anti-S-Ig was significantly higher in patients with non-severe fatigue compared to those with severe fatigue at 4–12 weeks (p = 0.006) and beyond 12 weeks (p = 0.016). The serum level of anti-NC-Ig remained high in patients with non-severe fatigue at both time points. In contrast, anti-NC-Ig decreased significantly in severe fatigue cases regardless of the elapsed time (4–12 weeks: p = 0.024; beyond 12 weeks: p = 0.005). The incidence of memory impairment was significantly correlated with lower anti-S-Ig levels (−0.359, p < 0.001). Conclusion: The systemic immune response reflected by antibodies to SARS-CoV-2 is strongly correlated with the severity of post-COVID fatigue.

Background: Long COVID is a condition characterized by long-term sequelae persisting after the typical convalescence period of COVID-19. Previous reports have suggested the role of an unsatisfactory immune response and impaired viral clearance in the pathogenesis of long COVID syndrome. We focused on potential associations between post-vaccination changes of antibody titers and the severity of long COVID symptoms and factors influencing the state of remission observed in patients with long COVID after vaccination. Methods: The severity of long COVID symptoms and serum anti-SARS-CoV-2 spike (S-Ig) and nucleocapsid (NC-Ig) levels were assessed in 107 post-COVID subjects at two time points: at baseline, and 17–24 weeks later. Besides, vaccination status was also assessed. Symptoms were evaluated based on the Chalder fatigue scale (CFQ-11) and visual analogue scale (VAS). Results: Serum level of S-Ig and NC-Ig at baseline were significantly higher in the patients with non-severe fatigue than those with severe fatigue, and this difference remained significant at follow-up in the case of NC-Ig. NC-Ig level above median was as an independent predictor for complete remission at follow-up. The difference in NC-Ig levels in subgroup analyses (severe fatigue vs. non-severe fatigue; complete remission vs. incomplete remission or progression) was found to be significant only in patients who received vaccination. Conclusions: The immune response against the SARS-CoV-2 nucleocapsid may play a more important role than the spike in the course of long-term COVID syndrome.

Polymorphisms of CYP450 metabolizer enzymes and transport proteins play crucial roles in the inter-individual variability of drug efficiency. The aim of our study was to predict the frequency of functional variants of CYP2D6, CYP2C19 and ABCB1 genes in the Hungarian population. One hundred twelve unrelated healthy subjects donated DNA sample in the study. ABCB1 C3435T and G2677T/A single-nucleotide polymorphisms (SNPs) were determined by LightCycler polymerase chain reaction. Because only limited amount of data is available on the rare allelic variants of CYP2D6 in the European populations, our study applied an expanded set of CYP2D6 and CYP2C19 alleles by using AmpliChip test. Our results show that the CYP2D6 phenotypes were 1.9% ultra-rapid metabolizer, 6.5% intermediate metabolizer (IM), 8.3% poor metabolizer (PM) and 83.3% extensive metabolizer (EM), and the CYP2C19 phenotypes were 1.8% PM, 31.2% IM and 67% EM. The prevalence of the commonly observed CYP2D6 and CYP2C19 alleles in our study corresponds with that of other European populations. Nevertheless, our study confirms that extending the CYP2D6 allele set with loss-of-function variants such as CYP2D6*7, *9, *41 is worth considering. Frequency of the wild type ABCB1 3435C was 42.8% whereas the prevelance of 2677 G was 50.4%. Although frequency data of G2677T/A SNP in the European area are limited, some discrepancies with other studies were found.

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Pharmacogenomic biomarker availability of Hungarian Summaries of Product Characteristics (SmPC) was assembled and compared with the information in US Food and Drug Administration (FDA) drug labels of the same active substance (July 2019). The level of action of these biomarkers was assessed from The Pharmacogenomics Knowledgebase database. From the identified 264 FDA approved drugs with pharmacogenomic biomarkers in drug label, 195 are available in Hungary. From them, 165 drugs include pharmacogenomic data disposing 222 biomarkers. Most of them are metabolizing enzymes (46%) and pharmacological targets (41%). The most frequent therapeutic area is oncology (37%), followed by infectious diseases (12%) and psychiatry (9%) (p < 0.00001). Most common biomarkers in Hungarian SmPCs are CYP2D6, CYP2C19, estrogen and progesterone hormone receptor (ESR, PGS). Importantly, US labels present more specific pharmacogenomic subheadings, the level of action has a different prominence, and offer more applicable dose modifications than Hungarians (5% vs 3%). However, Hungarian SmPCs are at 9 oncology drugs stricter than FDA, testing is obligatory before treatment. Out of the biomarkers available in US drug labels, 62 are missing completely from Hungarian SmPCs (p < 0.00001). Most of these belong to oncology (42%) and in case of 11% of missing biomarkers testing is required before treatment. In conclusion, more factual, clear, clinically relevant pharmacogenomic information in Hungarian SmPCs would reinforce implementation of pharmacogenetics. Underpinning future perspective is to support regulatory stakeholders to enhance inclusion of pharmacogenomic biomarkers into Hungarian drug labels and consequently enhance personalized medicine in Hungary.

Prostate cancer is the fifth leading cause of male cancer death worldwide. Although docetaxel chemotherapy has been used for more than fifteen years to treat metastatic castration resistant prostate cancer, the high inter-individual variability of treatment efficacy and toxicity is still not well understood. Since prostate cancer has a high heritability, inherited biomarkers of the genomic signature may be appropriate tools to guide treatment. In this review, we provide an extensive overview and discuss the current state of the art of pharmacogenomic biomarkers modulating docetaxel treatment of prostate cancer. This includes (1) research studies with a focus on germline genomic biomarkers, (2) clinical trials including a range of genetic signatures, and (3) their implementation in treatment guidelines. Based on this work, we suggest that one of the most promising approaches to improve clinical predictive capacity of pharmacogenomic biomarkers in docetaxel treatment of prostate cancer is the use of compound, multigene pharmacogenomic panels defined by specific clinical outcome measures. In conclusion, we discuss the challenges of integrating prostate cancer pharmacogenomic biomarkers into the clinic and the strategies that can be employed to allow a more comprehensive, evidence-based approach to facilitate their clinical integration. Expanding the integration of pharmacogenetic markers in prostate cancer treatment procedures will enhance precision medicine and ultimately improve patient outcomes.