Fluorescence in situ hybridization (FISH) of voided urine sediment is a sensitive and specific test for the detection of urothelial carcinoma. The time required for slide preparation using the conventional cytospin method is lengthy.To present an alternative to the conventional cytospin method.We compared the results of an improved filter monolayer method with published results of the conventional cytospin method. A total of 624 patients with cytology and FISH analyses were followed with cystoscopy and/or bladder biopsy. Fluorescence in situ hybridization analysis was performed on 624 cases using fluorescence-labeled probes to the pericentromeric regions of chromosomes 3, 7, and 17 and band 9p21; cytology was also performed in all cases.A total of 217 (34.7%) of 624 patients had follow-up bladder biopsies, and 170 of these (78.3%) had urothelial carcinoma. The sensitivity for cancer detection was higher for FISH than for urine cytology (92.9% [158/ 170] for FISH vs 72.9% [124/170] for urine cytology, P = <5%). The specificity was equivalent for FISH and urine cytology (97.5% [443/454] for FISH vs 92.2% [419/454] for cytology). The sensitivity for FISH was better (92.9% vs 81%), and there was no significant difference in specificity (97.5% vs 96%) between the filter method and the conventional cytospin method. Unlike the conventional cytospin method, the filter method did not require multiple centrifugation and decantation steps or investment in dedicated equipment.The improved filter method was faster, easier, and less expensive than published results with the conventional cytospin method with better sensitivity and equivalent specificity.
We thank Barde et al1 for critically going through the research we published2. Our sampling strategy allowed us to recruit participants having elements of evenness till the point they got tested for SARS-CoV-2. It was important to consider this aspect and take it into account because, in any case-control investigation, the cases that become available for inquiry come to medical attention due to various preceding selection factors and recruitment of controls should keep such considerations into account. The ICMR-COVID-19 data portal helped us in doing so and to sample cases and controls from the pool of symptomatic healthcare workers (HCWs) who were tested for SARS-CoV-2. This helped in reducing potential sampling biases. It was worth considering in this context that the reasons for asymptomatic HCWs getting tested for SARS-CoV-2 could potentially be different and heterogeneous from the symptomatic ones. However, this is not to say that the results would remain the same, had we considered including cases from the pool of infected but asymptomatic HCWs. We would further add that the evidence generated though one million tests conducted during January through April 2020 in India showed that about 28 per cent of all SARS-CoV-2-positive cases were asymptomatic3- presenting a different picture from what the authors of the letter suggested. Interestingly, one could trace the unfolding saga of HCQ in COVID-19 as far back as in February 2020, when the State Council of China, in a news conference, indicated the efficacy of HCQ in COVID-194. The results from the study by Gautret et al5 as well as several other analyses highlighting the use of HCQ in COVID-19 started making rounds on social media much before the first version of the HCQ prophylaxis advisory was released by the COVID-19 National Task Force in India67. The enthusiastic media coverage of US President Donald Trump's endorsement of HCQ for COVID-19 was also headline news since mid-March 2020. With such incidents, and the ability to purchase HCQ over the counter, we would not be surprised if a proportion of the HCWs were self-medicating prior to the release of the advisory. While we acknowledge that the usual limitations of self-reported data continue to be applicable to our dataset, it was not inconceivable that a small proportion of the HCWs had consumed six or more doses by the time our recruitment period closed. Further, as highlighted in our methods section, the cases and controls were matched for location (testing centre) and temporality (testing date). We decided not to match on variables such as gender and age to avoid the risk of overmatching, as it had been observed that such demographic factors were associated with SARS-CoV-2 infection, and we could not rule out if they were situated along the causal pathway8. We appreciate the observation that the subgroup analysis may have smaller sample sizes and reiterate the need for larger clinical trials to provide definitive evidence to resolve some of the dilemmas. Given the restrictions of working within a pandemic setting, and the need to generate evidence rapidly, keeping pace with the changing epidemiology of COVID-19, we acknowledge such limitations. The current case-control investigation was designed in the context of prophylaxis against acquisition of SARS-CoV-2 infection and not for treatment of COVID-19. As such, we find no contradiction between the findings in our study and the recommendations for the management of COVID-19. At this juncture, we maintain that the findings are indicative of an association between HCQ prophylaxis and protection against SARS-CoV-2 infection, and would also like to address the popular misconception that if a 95 per cent confidence interval (CI) includes the null value and another excludes it, the interval excluding the null is the more precise one. The precision of the statistical estimation, however, is measured by the width of the CI (which was narrow in our study, and therefore, indicative) and not solely guided by the inclusion of the null or any specific value9, let alone its appearance with a specific P value.
Smokeless tobacco products (STPs) carry assorted microbial population that contributes to carcinogens synthesis like tobacco-specific nitrosamines (TSNAs). Extensive exploration of microbiota-harboring STPs is required to understand their full carcinogenic potential. Here, we applied 16S rRNA gene sequencing to investigate bacteriome present in moist STPs immensely consumed in India (Khaini, Moist-snuff, Qiwam, and Snus). Further, the functional metagenome was speculated by PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) to assign the abundance of genes related to nitrogen metabolism, bacterial toxins, antibiotic drug resistance and other pro-inflammatory molecules. Highly diverse bacterial communities were observed in all moist STPs. Taxonomic analysis revealed a total of 549 genera belonging to four major phyla Proteobacteria, Firmicutes, Bacteroidetes and Actinobacteria. Overall, the core bacterial genera Acinetobacter, Bacillus, Prevotella, Acetobacter, Lactobacillus, Paracoccus, Flavobacterium, and Bacteroides were significantly abundant in moist STPs. Elevated moisture-holding products like Moist-snuff and Qiwam harbor rich bacterial species diversity and showed similar bacteriome composition. Furthermore, Qiwam products showed the highest level of genes associated with nitrogen metabolism, antibiotic resistance, toxins, and pro-inflammation (predicted by PICRUSt) which can contribute to the synthesis of TSNAs and induction of oral cancer. The present broad investigation of moist STPs-associated bacteriome prevalence and their detailed metabolic potential will provide novel insight into the oral carcinogenesis induced by STPs.
Abstract Carcinogens present in smokeless tobacco (SLT) like tobacco‐specific nitrosamines can be metabolized by the cytochrome P450 (CYP450) enzyme. Functionally, the CYP450 enzyme resides in a heme pigment to perform the catalytic activity. The CYP1A1 is one of the main extrahepatic CYP450 enzymes known to detoxify toxic substances and activate carcinogens. The CYP1A1 inhibition by potential inhibitors reduce the chance of oral cancer. The current study aimed to explore more about the inhibitor binding site and identification of lead alkaloids, that could work as putative inhibitors against target CYP1A1. In respect, we have performed docking studies, virtual screening of alkaloids, and natural product libraries against CYP1A1 followed by molecular dynamic simulations and binding free energy calculations. Docking studies of tobacco‐specific nitrosamine (TSNA) products and their similar carcinogen analogs revealed that the heme group is bound to the floor of the bowl‐shaped cavity whereas carcinogens are bound to the roof of the rounded shape cavity. Furthermore, virtual screening and binding free energy calculations revealed Tomatidine as a putative inhibitor against CYP1A1. On the basis of altogether outcomes of the current study, we have concluded that the addition of lead‐hit alkaloid Tomatidine and others in SLT products may be working as a supplement that could be able to reduce the expression of human CYP1A1 and suppresses carcinogenic by‐products formations.
e23029 Background: Underrepresentation of older adults (≥65 years) in clinical trials may limit important evidence for regulatory and clinical decision-making. Prior FDA analysis 1 demonstrated underrepresentation of older adults in oncology clinical trials. With recent efforts to encourage inclusion of older adults, we evaluated representation in clinical trials using updated data. Methods: This analysis used patient-level data from pivotal trials supporting approvals of new drugs and biologics, and expanded indications from 2010-2020 for cancers with high incidence in the U.S. population and older adults: breast (BC), colorectal (CRC), non-small cell lung (NSCLC), prostate (PC), chronic myeloid leukemia (CML), and multiple myeloma (MM). Age distribution of trial participants compared to incident cases from the NCI SEER Program was analyzed using the Enrollment to Incidence Ratio (EIR). For each cancer-age group, EIR is the percentage of trial participants divided by percentage of incident cases. Previously established EIR categories of < 0.8, 0.80-1.20, and > 1.2 indicate under-, adequate, and over-representation, respectively. Results: The analysis included 86000 participants in 152 trials. Adults >65 yrs were underrepresented in BC trials. Adults >75 yrs were underrepresented in BC, CRC, NSCLC, CML, and MM trials (Table 1). Conclusions: Despite slight variation across cancers, adults >75 yrs appeared to be underrepresented in clinical trials, excepting PC. Given heterogeneity in the natural history by cancer site, incidence may not best represent age distribution of the intended use population for all trials. Further evaluation using prevalence as a comparator may provide additional insights. Additionally, results may be affected by clinical factors such as stage; however, comparison is limited by SEER data element availability. Planned sensitivity analyses such as stratification by drug class and line of therapy may further elucidate enrollment patterns. References: Singh H, Kanapuru B, Smith C, et al: FDA analysis of enrollment of older adults in clinical trials for cancer drug registration: A 10-year experience by the U.S. Food and Drug Administration. Journal of Clinical Oncology 35:10009-10009, 2017. [Table: see text]
Abstract Background To review and summarize all U.S. Food and Drug Administration (FDA) approvals of programmed death (PD)-1 and PD-ligand 1 blocking antibodies (collectively referred to as PD-[L]1 inhibitors) over a 6-year period and corresponding companion/complementary diagnostic assays. Materials and Methods To determine the indications and pivotal trials eligible for inclusion, approval letters and package inserts available on Drugs@FDA were evaluated for approved PD-[L]1 inhibitors to identify all new indications granted from the first approval of a PD-[L]1 inhibitor on September 4, 2014, through September 3, 2020. The corresponding FDA drug and device reviews from the marketing applications for the approved indications were identified through FDA internal records. Two reviewers independently extracted information for the endpoints, efficacy data, basis for approval, type of regulatory approval, and corresponding in vitro diagnostic device test. The results were organized by organ system and tumor type. Results Of 70 Biologic Licensing Application or supplement approvals that resulted in new indications, 32 (46%) were granted based on response rate (ORR) and durability of response, 26 (37%) on overall survival, 9 (13%) on progression-free survival, 2 (3%) on recurrence-free survival, and 1 (1%) on complete response rate. Most ORR-based approvals were granted under the accelerated approval provisions and were supported with prolonged duration of response. Overall, 21% of approvals were granted with a companion diagnostic. Efficacy results according to tumor type are discussed. Conclusion PD-[L]1 inhibitors are an effective anticancer therapy in a subset of patients. This class of drugs has provided new treatment options for patients with unmet need across a wide variety of cancer types. Yet, the modest response rates in several tumor types signal a lack of understanding of the biology of these diseases. Further preclinical and clinical investigation may be required to identify a more appropriate patient population, particularly as drug development continues and additional treatment alternatives become available. Implications for Practice The number of PD-[L]1 inhibitors in drug development and the associated companion and complementary diagnostics have led to regulatory challenges and questions regarding generalizability of trial results. The interchangeability of PD-L1 immunohistochemical assays between PD-1/PD-L1 drugs is unclear. Furthermore, robust responses in some patients with low levels of PD-L1 expression have limited the use of PD-L1 as a predictive biomarker across all cancers, particularly in the setting of diseases with few alternative treatment options. This review summarizes the biomarker thresholds and assays approved as complementary and companion diagnostics and provides regulatory perspective on the role of biomarkers in oncology drug development.
'%3e%3ccircle r='20' fill='%23008'/%3e%3ccircle r='17.5' fill='%23fff'/%3e%3ccircle r='3.5' fill='%23008'/%3e%3cg id='d'%3e%3cg id='c'%3e%3cg id='b'%3e%3cg id='a' fill='%23008'%3e%3ccircle r='.875' transform='rotate(7.5 -8.75 133.5)'/%3e%3cpath d='M0 17.5.6 7 0 2l-.6 5L0 17.5z'/%3e%3c/g%3e%3cuse xlink:href='%23a' transform='rotate(15)'/%3e%3c/g%3e%3cuse xlink:href='%23b' transform='rotate(30)'/%3e%3c/g%3e%3cuse xlink:href='%23c' transform='rotate(60)'/%3e%3c/g%3e%3cuse xlink:href='%23d' transform='rotate(120)'/%3e%3cuse xlink:href='%23d' transform='rotate(-120)'/%3e%3c/g%3e%3c/svg%3e)
