Cyclohexylfentanyl  and TMCPF  were partial agonists less potent than morphine (EC50 = 430 nM). Based on the results, cyclopropyl‐, cyclobutyl‐, and cyclopentylfentanyl would be expected to induce intoxication or cause fatal poisonings at similar concentrations to fentanyl, while the toxic or fatal concentrations of cyclohexylfentanyl and TMCPF would be expected to be much higher.Fentanyl analogs represent an important group of new psychoactive substances and knowing their efficacy and potency might assist in interpreting observed concentrations. The potency of fentanyl analogs can be estimated from in vitro studies and can be used to establish structure–activity relationships. In this study, recombinant CHO‐K1 cells (AequoScreen) expressing the human μ‐opioid receptor were used to establish dose–response curves via luminescent analysis for cyclopropyl‐, cyclobutyl‐, cyclopentyl‐, cyclohexyl‐, and 2,2,3,3‐tetramethylcyclopropylfentanyl (TMCPF), on three separate occasions, using eight different concentrations in an eight‐fold serial dilution in triplicates starting at ~60 μM. Fentanyl was used as a full agonist reference while morphine and buprenorphine were included for comparison. Cyclopropylfentanyl  are partial agonists with potency lower than buprenorphine using an AequoScreen assay. Similarly, predictions of potency based on the structure could be of value in scheduling decisions on new uncharacterized NPS. Potency can be studied in several ways, including functional studies in laboratory animalsAlicyclic fentanyls share their overall chemical structure with fentanyl, except for the substitution of the propionamide with amides with increasingly large cyclic structures containing either a cyclopropyl‐, cyclobutyl‐, cyclopentyl‐, cyclohexyl‐, or 2,2,3,3‐tetramethylcyclopropyl ring . This can be compared with an EC50 for cyclopropylfentanyl of 11 nM reported by the Drug Enforcement Administration,i) or β‐arrestin to study cyclopropyl‐ and cyclopentylfentanyl, and TMCPF. For the mini‐Gi assay they reported EC50 values of 42 and 190 nM, with efficacies of 280% and 159% (compared with hydromorphone), for cyclopropyl‐ and cyclopentylfentanyl, respectively. Similarly, for the β‐arrestin assay they reported EC50 values of 15 and 180 nM, with efficacies of 158% and 127% (compared with hydromorphone), for cyclopropyl‐ and cyclopentylfentanyl, respectively. For TMCPF, no signal was observed in either assay.The structure–activity relationships for fentanyl analogs have been investigated and reviewed.Previous literature indicates that both the potency and the efficacy differ between the different alicyclic fentanyl analogs but it is difficult to ascertain how the ring size impact these parameters. Therefore, the aim of this study was to determine the μ‐opioid receptor activity induced by a complete series of alicyclic fentanyls and to investigate the structure–activity relationships regarding potency and efficacy.2Reference standards of cyclopropyl‐, cyclobutyl‐, cyclopentyl‐, cyclohexyl‐, and TMCPF were purchased from Cayman Chemicals . The cell culture medium used was DMEM/Ham’s F12 with 15 mM HEPES, L‐glutamine, and without phenol red, from Thermo Fisher . Digitonin, ATP, trypsin, and protease‐free BSA were from Sigma‐Aldrich . Fetal bovine serum (FBS) was from Life Technologies, Thermo Fisher . Coelenterazine was from Nanolight Tech . Stock solutions of 500 μM coelenterazine were prepared in methanol (and protected from light), 50 mM digitonin in DMSO, and 10 mM ATP in Milli‐Q water and stored at −20°C2+ concentration.2+, coelenterazine is oxidized with the emission of light.2, in Ham’s F12 medium supplemented with 10% FBS and passaged every 3–4 days. The cells were not cultured beyond 30 passages.The receptor activation assay was carried out on AequoScreen recombinant CHO‐K1 cell lines purchased from Perkin Elmer  expressing the human μ‐opioid receptor (ES‐542‐AV) and subunit Gα16 coupling receptor activation to an increase in intracellular Ca5 cells/mL. Coelenterazine was added to the cells to a concentration of 2.5 μM. The cells were gently incubated on a rotating wheel at room temperature for 3 hours while protected from light. The alicyclic fentanyls were prepared in 96‐well plates , in triplicate, at final concentrations of 20,000, 4,000, 800, 160, 32, 6.4, 1.28, 0.256, 0.0512, 0.01024 ng/mL in each well (concentrations after adding the cells). Fentanyl, morphine, and buprenorphine were analyzed in the same concentration range to serve as μ‐opioid receptor full‐ and partial agonist references. As positive controls digitonin (67 μM) and ATP (7 μM) were used. Wells containing cells and medium without drug were used as negative controls. The receptor activation at each drug concentration was determined by dispensing 50 μL of cells into each well  using a TECAN Spark 10 M  for the subsequent luminescence reading. The reading protocol was set to 200 luminosity readings, and the cells were added to each well at reading cycle 10 (baseline). Luminescence reading was carried out for ~25 s before moving on to the next well.Prior to the dose–response assays, the cells were cultured to a confluency of 70–90% and then trypsinized, centrifuged (150 × g for 5 min at room temperature), and resuspended in pre‐warmed assay medium  at a concentration of 3 × 10The experiments for each substance were repeated on three different days comprising 6 days of analysis. Fentanyl was included as a reference every day and the data set for fentanyl contains seven experiments, including two from the same day.Luminescence data from each well were summarized over the total reading time and blank measurements were subtracted. The response signals were normalized to the digitonin signal for each plate and then normalized to the plateau signal of fentanyl , denoted as 100% activity.50 values and efficacy with 95% confidence intervals (profile likelihood) and curve fittings  were calculated using all data points  using GraphPad Prism version 8.3.0 for Windows . The efficacy  of all fentanyl analogs was compared with that of the full agonist fentanyl  using a one‐way ANOVA with Dunnett correction for multiple tests. Differences in potency, as Log (EC50) values from the regression, were compared between fentanyl and all fentanyl analogs  using a one‐way ANOVA with Dunnett correction for multiple tests.The ECFull dose–response curves were obtained for cyclopropyl‐, cyclobutyl‐, cyclopentyl‐, and cyclohexylfentanyl, as well as TMCPF, fentanyl, morphine, and buprenorphine, see Figure 50 = 4.3 nM) and cyclobutylfentanyl (EC50 = 6.2 nM) were the most potent of the alicyclic fentanyls, being slightly less potent  than fentanyl (EC50 = 2.0 nM). Cyclopropyl‐ and cyclobutylfentanyl showed no significant difference in potency but significant differences in potency were observed for all other fentanyl analogs , in the following order (most potent first): fentanyl > cyclopropylfentanyl = cyclobutylfentanyl > cyclopentylfentanyl > TMCPF > cyclohexylfentanyl. Interestingly, both cyclohexylfentanyl and TMCPF were partial agonists, showing only 48% and 65% activation compared with fentanyl, respectively, see Table P value 0.07) and cyclopentylfentanyl  compared with fentanyl.Cyclopropyl‐ . Also using a GTPγS binding assay, Hassanien et al50 value of 32 nM for fentanyl, while the Drug Enforcement Administration reported EC50 values of 32 nM and 17 nM for fentanyl and morphine, respectively. Using assays based on cAMP, Kuo et al50 values of 180, 0.2, and 1 nM for morphine, buprenorphine, and fentanyl, respectively, while Yu et al50 values of 5.3 and 0.02 nM for morphine and buprenorphine, respectively. Finally, Vasudevan et al reported an EC50 of 68 nM for fentanyl with an efficacy of 261% (compared with hydromorphone) using an assay based on the recruitment of mini‐Gi.To the best of our knowledge fentanyl, morphine, and buprenorphine have never been compared using an assay based on the aequorin system, but a few studies using human receptors have been conducted using other reporting systems. Lipinski et al50 value obtained in this study, 1.7 nM, is similar to data obtained from receptor binding studies (1.2 and 1.6 nM) as well as from the cAMP assay (1 nM), while lower than those obtained from GTPγS binding and mini‐Gi recruitment . Morphine on the other hand had an EC50 value of 430 nM compared with literature values in the range of 5–180 nM. Only two studies evaluated both fentanyl and morphine in the same model system. Yu et alAs expected, the measured effective concentrations differed more than tenfold between assays, both between different types of assays but also between assays of the same type. For fentanyl, the ECThe five alicyclic fentanyls can be divided into two distinct groups. The three smaller analogs, cyclopropyl‐, cyclobutyl‐, and cyclopentylfentanyl were all full agonists with potencies similar to fentanyl, while cyclohexylfentanyl and TMCPF behaved like partial agonists of similar efficacy to buprenorphine but with lower potency. It was remarkable how suddenly the agonist behavior changed when going from a cyclopentyl ring to a cyclohexyl ring, and it is postulated that this might be due to steric hindrance at the binding site.50 value and the efficacy of fentanyl. In our study, cyclopropylfentanyl was a full agonist 2.5‐fold less potent than fentanyl. In other studies the EC50 varied from 2.9‐fold more potent to 1.7‐fold less potent than fentanyl with efficacies between 84% and 107% compared with fentanyl.50‐values compared with fentanyl are similar to those reported in previous studies, even though cyclopropylfentanyl appears somewhat less potent than previously reported. That said, when looking at the efficacies, cyclobutyl‐ and cyclopentylfentanyl appear to be full agonists in our study while they have previously been reported as partial agonists.Except for cyclohexylfentanyl, the alicyclic fentanyl analogs have been studied before, although not together.Based on the results, cyclopropyl‐, cyclobutyl‐, and cyclopentylfentanyl would be expected to induce intoxication or cause fatal poisonings at similar concentrations to fentanyl, while the concentrations of cyclohexylfentanyl and TMCPF required to cause intoxication would be expected to be much higher. That said, it is difficult to extrapolate from in vitro receptor activation to potency in vivo as the latter is also affected by important pharmacokinetic factors such as uptake, distribution, plasma binding, blood–brain barrier penetration, metabolism, and elimination. Even though analogs with lower potency and efficacy can still be abused, as illustrated by the high number of fatalities observed with buprenorphine,Earlier studies from our group have shown that the main routes of metabolism for alicyclic fentanyls include dealkylation to form normetabolites as well as oxidation of the alicyclic rings. With increasing ring size fewer normetabolites are formed, in favor of oxidation.In our study, using the AequoScreen assay, all alicyclic fentanyl analogs exhibited activity at the μ‐opioid receptor. Cyclopropyl‐, cyclobutyl‐, and cyclopentylfentanyl were all full agonists with a similar potency to fentanyl. On the contrary cyclohexylfentanyl and TMCPF were partial analogs of similar efficacy to buprenorphine but with lower potency.Vinnova, Eurostars Project ID: 113377 (the NPS‐reform project), and Strategic Research Area in Forensic Sciences (Strategiområdet forensiska vetenskaper) at Linköping University, grant numbers: 2016:4 and 2018:1.


Thiamine, an essential vitamin for aerobic metabolism and glutathione cycling, may decrease the effects of critical illnesses. The objective of this study was to determine whether intravenous thiamine administration can reduce vasopressor requirements in patients with septic shock.This study was a prospective randomized double-blind placebo-controlled trial. We included adult patients with septic shock who required a vasopressor within 1–24 h after admission between March 2018 and January 2019 at a tertiary hospital in Thailand. Patients were divided into two groups: those who received 200 mg thiamine or those receiving a placebo every 12 h for 7 days or until hospital discharge. The primary outcome was the number of vasopressor-free days over 7 days. The pre-defined sample size was 31 patients per group, and the study was terminated early due to difficult recruitment.p = 0.197, mean difference − 0.9, 95% CI (− 2.9 to 0.5)). However, the reductions in lactate (p = 0.024) and in the vasopressor dependency index (p = 0.02) at 24 h were greater among subjects who received thiamine repletion vs. the placebo. No statistically significant difference was observed in SOFA scores within 7 days, vasopressor dependency index within 4 days and 7 days, or 28-day mortality.Sixty-two patients were screened and 50 patients were finally enrolled in the study, 25 in each group. There was no difference in the primary outcome of vasopressor-free days within the 7-day period between the thiamine and placebo groups (mean: 4.9 days (1.9) vs. 4.0 days (2.7), Thiamine was not associated to a significant reduction in vasopressor-free days over 7-days in comparison to placebo in patients with septic shock. Administration of thiamine could be associated with a reduction in vasopressor dependency index and lactate level within 24 h. The study is limited by early stopping and low sample size.http://www.clinicaltrials.in.th/index.php?tp=regtrials&menu=trialsearch&smenu=fulltext&task=search&task2=view1&id=3330.TCTR, TCTR20180310001. Registered 8 March 2018, Supplementary information accompanies this paper at 10.1186/s12871-020-01195-4. Thiamine is a water-soluble vitamin-containing antioxidant. In the aerobic metabolism of cells, thiamine is an essential vitamin, acting as a cofactor of pyruvate dehydrogenase and alpha-ketoglutarate transketolase of the Krebs cycle as well as in the pentose-phosphate shuttle that occurs in mitochondria . An expePatients with septic shock have high metabolic consumption and have been observed to have many manifestations similar to patients with thiamine deficiency syndrome, including vasodilatation, hypotension, cardiac failure and elevated lactate levels . A retroWe performed a prospective single-centre randomized double-blind placebo-controlled study to determine whether thiamine administration is associated with improvements in clinical outcomes for patients with septic shock. Patients were enrolled at Ramathibodi Hospital, Mahidol University - a tertiary academic medical centre. The study was approved by The Committee on Human Rights, Related to Research Involving Human Subjects and based on the Declaration of Helsinki, Faculty of Medicine Ramathibodi Hospital, Mahidol University (protocol number: ID 12–60-05). Patients or relatives provided written informed consent prior to enrolment. The trial was registered in the Thai Clinical Trials Registry (TCTR20180310001).We enrolled consecutive patients between March 2018 and January 2019. We included adult patients (≥18 years) who had suspected infections, showed a Sequential Organ Failure Assessment (SOFA) score ≥ 2, were on a vasopressor or had been administered inotropic drugs for at least 1 h but no more than 24 h, and had a lactate level > 2 mmol/L; these patients were enrolled from emergency departments or the inpatient department unit. We excluded patients based on the following criteria: (1) receipt of thiamine > 100 mg within 24 h before enrolment, (2) thiamine allergy or anaphylaxis, (3) pregnancy, (4) cancer or diseases having a 6-month survival rate ≤ 50% and (5) diagnosed cardiac beriberi, peripheral beriberi, Wernicke-Korsakoff syndrome or re-feeding syndrome.1) in 50 mL of 5% DW every 12 h, with continued infusion for 30 min. Patients in the placebo group received 50 mL of 5% DW every 12 h, with continued infusion for 30 min, for 7 days or until discharge of both groups. The placebo was identical in appearance to thiamine; patients, caregivers and outcome assessors remained blinded throughout the study period. Other septic shock management protocols, such as fluid resuscitation, antibiotics and septic work-ups, followed the Surviving Sepsis Campaign guidelines, 2016 [Patients were randomized via 1:1 block computer-generated randomization with conceal envelope technique to receive either thiamine or a placebo. Patients in the thiamine group received 200 mg of thiamine hydrochloride , changes in SOFA scores from baseline to day 7 (or sooner if the patient was discharged) and 28-day mortality. Due to the effects of thiamine possibly being shorter than 7 days, patients would either recover or die. We conducted post hoc analyses of the effects of thiamine on changing SOFA scores, the vasopressor dependency index over 4 days and the difference between SOFA scores on days 1 and 4, as similarly performed in previous studies [Thiamine levels were analysed in plasma via the fluorescence technique, which measured thiamine diphosphate (thiamine pyrophosphate), in which the most important and active form is an intracellular compound, making it the best marker of thiamine nutritional status. Thiamine deficiency, utilizing this technique, was defined as a level less than 70 nmol/L .The vasopressor dependency index was calculated from the inotropic score divided by the mean arterial pressure (inotropic score = (dopamine dose × 1) + (dobutamine dose × 1) +  +  + (phenylephrine dose × 100)), and all doses were expressed as mcg/kg/min .2), the platelet count [After patients were enrolled, all patient demographic data were recorded, and blood was drawn for collection to measure the arterial lactate levels at baseline and arterial lactate levels at 24 h after the first dose. All of the patients’ blood was collected for measurement of their thiamine pyrophosphate levels at baseline before intervention, and parameters of the SOFA scores, including creatinine, total bilirubin, the partial pressure of oxygen .After a total of 10 months, our inclusion criteria were met by 62 patients. From this number, 12 patients were excluded , which was greater than that in the placebo group, with a median of 0.03 mmHg− 1 (IQR: − 0.09 to 0.12), p value: 0.020. Moreover, the lactate reduction within 24 h in the thiamine group had a median of 1.0 mmol/L (IQR: − 0.3 to 1.8) and was greatly reduced, more so than in the placebo group: median: 0.5 mmol/L (IQR: − 0.2 to 1.0), p value: 0.024 . In the thiamine group, 5 patients died (20%), while in the placebo group, 7 patients died (28%)  within 28 days. No patients in the thiamine group died within 7 days while receiving thiamine administration; however, 4 patients in the placebo group died over the course of 7 days  Fig. ; howeverTaking into account the major limitations of early stopping the study and small sample size, no evidence of differences in vasopressor-free days between the patients receiving thiamine or a placebo in 7 days was found. We found that 24 h after administration of the intervention, patients in the thiamine group had a reduction in their vasopressor dependency index as well as decreased lactate, more so than those in the placebo group. No other secondary outcomes were significantly different.In general, the rationale for thiamine administration in septic shock is supported by a high incidence of low thiamine levels in critically ill patients and a high thiamine consumption state from increased mitochondrial oxidative stress during critical illnesses . ThiaminThe results of the present study suggest that no difference in the number of vasopressor-free days, mortality, SOFA score or vasopressor dependency index occurred within 7 days. However, within the statistical power limitations, these results also suggest that early administration of thiamine (within 24 h), reduced lactate and the vasopressor dependency index, also within 24 h. Although only a few of the individuals in this study population were thiamine deficient, this number was still less than those other studies. This situation may have been due to the fact that this study differed in population, race, nutritional status and/or early randomization , 9. LargIn our study, we found that thiamine administration could reduce lactate levels compared with those in patients not receiving thiamine. The outcomes were different from previous findings by Donnino et al. , in whicRegarding physical effects, this study showed a greater reduction in the 24-h vasopressor dependency index in the thiamine group than in the placebo group. We assumed that this improved the microvascular function, as in the pentose-phosphate shuttle that occurs in mitochondria. However, we did not test clinical changes in the cardiac index or vascular resistance. Moreover, we cannot exactly explain the mechanism.In the post hoc analysis of our study, the outcome of organ failure improved in the first 4 days; therefore, the administration of thiamine might not necessarily last long. On the other hand, the use of thiamine for less than 4 days in the study of Hwang et al. (who administered thiamine and vitamin C to septic shock patients for 2 days) did not improve the SOFA score . HoweverStrengths of our study. First, the design of this study used double blind randomization in that we blinded both the patients and investigators to reduce selection bias. Second, we included patients early and limited the time to randomization. Third, this trial measured thiamine levels at the time of randomization before administering the intervention, which showed a background of thiamine levels in our population with septic shock.Our study did have limitations. First, it had a small sample size and an early stopping point and was insufficiently powered; this limited validity of the results may have led to selection bias. Moreover, the risk of type I and II errors should be taken into consideration and the results of post hoc analyses should be interpreted with caution. Further studies are needed to evaluate the effectiveness of thiamine on vasopressor requirements. Second, we did not compare differing dosage levels of thiamine. The dosage of thiamine in our study was 200 mg IV every 12 h for 7 days, which was different from that in a study by Woolum JA. et al. . AdditioThiamine was not associated to a significant reduction in vasopressor-free days over 7-days in comparison to placebo in patients with septic shock. Administration of thiamine could be associated with a reduction in vasopressor dependency index and lactate level within 24 h. The study is limited mainly by early stopping and low sample size. Further studies are needed to evaluate the effectiveness of thiamine on vasopressor requirements.Additional file 1:Figure 1. Changes of SOFA scores within 7 days. Figure 2. Changes of the Vasopressor Dependency index within 7 days.


We aimed to obtain a set of health state utility scores of patients with esophageal cancer (EC) and precancerous lesions in China, and to explore the influencing factors of health‐related quality of life (HRQoL).A hospital‐based multicenter cross‐sectional study was conducted. From 2013 to 2014, patients with EC or precancerous lesions were enrolled. HRQoL was assessed using a European quality of life‐5 dimension (EQ‐5D‐3L) instrument. Multivariable linear regression analysis was performed to explore the influencing factors of the EQ‐5D utility scores.A total of 2090 EC patients and 156 precancer patients were included in the study. The dimension of pain/discomfort had the highest rate of self‐reported problems, 60.5% in EC and 51.3% in precancer patients. The mean visual analog scale (VAS) score for EC and precancer patients were 68.4 ± 0.7 and 64.5 ± 3.1, respectively. The EQ‐5D utility scores for EC and precancer patients were estimated as 0.748 ± 0.009 and 0.852 ± 0.022, and the scores of EC at stage I, stage II, stage III, and stage IV were 0.693 ± 0.031, 0.747 ± 0.014, 0.762 ± 0.015, and 0.750 ± 0.023, respectively. According to the multivariable analyses, the factors of region, occupation, household income in 2012, health care insurance type, pathological type, type of therapy, and time points of the survey were statistically associated with the EQ‐5D utility scores of EC patients.There were remarkable decrements of utility scores among esophageal cancer patients, compared with precancer patients. The specific utility scores of EC would support further cost‐utility analysis in populations in China. Esophageal cancer (EC) is one of the most prevalent malignant tumors in the upper digestive system. According to GLOBOCAN 2018, it is the seventh most common cancer and the sixth most common cause of death from cancer worldwide, and the estimated numbers of EC new cases and deaths in 2018 were 572 034 and 508 585, respectively.et al. successfully developed Chinese utility values for EQ‐5D‐3L health states using the time trade‐off method.Quality of life (QoL) has been one of the critical indicators in cost‐utility analysis in health economic evaluation.et al. reported EC significantly impaired Chinese patients' HRQoL in daily life after treatmentet al. reported that personal characteristics were associated with patients' HRQoL in China.In recent years, HRQoL has become a major measurement of clinical research. Several studies have measured the HRQoL directly in EC patients.The objectives of our study were as follows: (i) To obtain a set of health state utility scores of patients with EC and precancerous lesions in China using the EQ‐5D instrument, and (ii) to evaluate the determinants of HRQoL and the relationship between these influencing factors and EQ‐5D utility.The National Cancer Center of China conducted a hospital‐based multicenter cross‐sectional study, namely the Cancer Screening Program in Urban China (CanSPUC), which provides free screening services for Chinese urban residents aged from 40–69 years. The target cancers in this screening program were lung, breast, colorectal, liver, stomach and esophageal cancers. It was a major public health service project supported by the central government of China. This project was initiated in August 2012, and has now covered 29 provinces nationwide. The screening process consisted of three steps: the initial assessment of a high‐risk population, further screening for cancer, and health economic evaluation.This current EQ‐5D study was one part of the overall project, CanSPUC. We aimed to use the utility instrument EQ‐5D‐3L to systematically evaluate the HRQoL in patients with EC or precancerous lesions in China. From 2013 to 2014, a total of 12 provinces in China were enrolled in the CanSPUC, which were distributed in four geographic regions .We identified cases of esophageal precancerous lesions as low grade intraepithelial lesions (LSIL) and high grade intraepithelial lesions (HSIL); LSIL included mild dysplasia and moderate dysplasia, and HSIL referred to severe dysplasia and carcinoma, in situ.In the present study, patients were selected using the method of convenience sampling in each involved medical center. The eligibility criteria for participants were as follows: (i) Patients were 40–69 years of age at the initial diagnosis with EC or precancerous lesions by screening, from September 2013 to December 2014; (ii) residents of the 12 selected provinces; and (iii) able to understand the survey procedure and complete the survey questionnaire. The survey was approved by the Institutional Review Board of the Cancer Hospital of Chinese Academy of Medical Sciences . Written informed consent was signed before each participant was enrolled into the study.A total of 2090 patients with EC and 156 patients with precancerous lesions were included in the present study. Each patient was interviewed with a structured questionnaire for sociodemographic, clinical, and HRQoL information. The HRQoL was assessed using the EQ‐5D‐3L questionnaire. In the EQ‐5D questionnaire, respondents were at particular levels in particular dimensions, and the three levels of each dimension were categorized into “no problems” (level 1) and “any problem” (levels 2 and 3).First, study protocol and data collection training were provided by the National Cancer Center of China for all the principle staff from the abovementioned 12 sites. Second, all the participating physicians in local centers/hospitals were trained for in‐person interviewing using a structured questionnaire with an EQ‐5D instrument (Chinese version). A face‐to‐face interview was either administered by a trained interviewer, or alternatively, self‐administered by capable patients in the presence of the project staff member who could answer any doubts the patients had about the interview. Furthermore, data input and basic data checks were also performed in the 15 collaborative sites. The National Cancer Center of China conducted multiple rounds of data logistical checks by interacting with local staff, and was responsible for the database building, data cleaning, and data analyses.P‐values <0.05 were considered statistically significant. All hypothetical tests were two‐sided.Frequencies and percentages were used for categorical variables, and the mean ± standard deviation (SD) was used for continuous variables. Means of EQ VAS scores and EQ‐5D utility scores were analyzed , using the Kruskal‐Wallis test, which is appropriate for non‐normal data. The Kruskal‐Wallis test was also used to compare the means of EQ‐5D utility scores across different categories of sociodemographics  and clinical characteristics . Finally, we conducted a multivariate linear ordinary least square (OLS) regression analysis to explore the impact of important variables, by inputting variables with statistical significance confirmed in the univariate analysis, and using a stepwise approach. OLS regression analysis is known to be the most commonly used and optimal method for HSU multivariate analyses so far,Data were entered into the EpiData software , using a double entry method. Logical check and statistical analyses were performed using SAS statistical software for Windows, version 9.3 .The sociodemographic and clinical characteristics of the patients are summarized in Table A total of 2090 patients with EC were included in the analysis , with a mean age of 62.64 ± 9.06 years. Most of the patients were 65–69 years of age and of all the cancer patients in the analysis, 39.38% were from the eastern region. A majority of the EC patients were married (94.69%). Among 1920 patients with available pathological information, 1417 patients were diagnosed with squamous cell carcinoma and 142 patients were diagnosed with adenoma. Among 1936 patients with available stage information, 761 patients were diagnosed with stage II cancer, whereas only 194 had stage I cancer. Of all the EC patients, 611 (29.23%) patients underwent surgery, 385 (18.42%) patients received chemotherapy and 303 (14.50%) patients received radiotherapy.There was a total of 156 patients with esophageal precancerous lesions , with a mean age of 57.29 ± 12.86 years. The sociodemographic characteristics were similar to those of the EC patients. Among 70 patients with available pathological information, 36 patients were diagnosed with high grade squamous intraepithelial neoplasms and 34 patients with low grade squamous intraepithelial tumors. A total of 63 patients underwent surgery and 62 patients received symptomatic treatment.P‐values <0.05 . Figures P‐values <0.05). The mean EQ‐VAS scores were 69.5 ± 2.2 at stage I, 69.8 ± 2.1 at stage II, 70.5 ± 2.1 at stage III, and 64.8 ± 1.8 at stage IV. After applying the preference weights of the Chinese population, the overall EQ‐5D utility scores of cancer patients and patients with precancerous lesions were 0.748 ± 0.009 and 0.852 ± 0.022, respectively. Compared with EC patients, patients with precancerous lesions were statistically associated with higher EQ‐5D utility scores . A significant difference of EQ‐5D utility scores was detected among four cancer stages . The corresponding mean EQ‐5D utility scores were 0.693 ± 0.031 at stage I, 0.747 ± 0.014 at stage II, 0.762 ± 0.015 at stage III, and 0.750 ± 0.023 at stage IV.Figure ores Fig a1 , level of education (P = 0.031), and age at diagnosis (P = 0.041) were significantly associated with EQ‐5D utility scores among patients with esophageal precancerous lesions in univariate analyses. However, the region (P < 0.0001), occupation (P = 0.021), health care insurance type (P = 0.034), pathological type (P = 0.0011), type of therapy (P < 0.0001), and time points of the survey (P < 0.0001) were statistically associated with the EQ‐5D utility scores among cancer patients.The associations between EQ‐5D utility scores and population characteristics are shown in Table F = 3.988, P < 0.001, R2 = 0.279). Additionally, for cancer patients, the factors of occupation, household income in 2012, pathological type, type of therapy, and time points of the survey were statistically associated with EQ‐5D utility scores in the multivariate analysis .Table This current work is a unique large‐scale multicenter study focusing on the HRQoL of patients with EC or precancerous lesions assessed by an internationally comparable and utility instrument, the EQ‐5D questionnaire. Our results provided reliable utility estimates for HRQoL in patients with EC or precancerous lesions using a well‐validated method, which will be informative for future detailed cost‐effectiveness evaluations.et al. reported the proportion of five dimensions in 209 EC patients in Anhui, where the percentages of respondents reporting problems of pain/discomfort, anxiety/depression, usual activity, mobility, and self‐care were 38.3%, 25.4%, 22.0%, 18.2% and 12.0%.N = 188 720), that was the Chinese National Health Services Survey (NHSS), where the percentages of respondents reporting problems of pain/discomfort, anxiety/depression, usual activity, mobility, and self‐care in the population aged 45–64 years were found to be approximately 14.0%, 5.8%, 3.6%, 4.8%, and 2.3%, respectively.et al. reported that the worst status of quality of life in cancer patients occurred when patients were receiving treatment.We found that pain/discomfort posed a major problem, followed by anxiety/depression, problem of usual activity, problem of mobility, and problem of self‐care in sequential order. This finding is consistent with the results of another HRQoL analysis of EC using the EQ‐5D instrument in Anhui Province, China.In this study, we used the VAS method to derive values for the health state. In the mentioned NHSS study, the average VAS in the Chinese general population aged 45–64 years was found to be 79.3.et al reported that the utility scores were negatively associated with the severity of EC.et al. reported worse HRQoL in patients with earlier stage of colorectal cancer compared with those at stage III and IV.As expected, the cancer patients (0.748) suffered a larger decrease in quality of life than patients with precancerous lesions (0.852). However, there were no significant differences of both EQ‐5D utility scores and VAS scores between males and females, which suggested that sex was not an influencing factor of HRQoL. The scores differed notably among cancer stages. There is some debate about the association between EQ‐5D utility score and the stage of EC. It was surprising to see that the utility score for cancer stage I was the lowest, and it was inconsistent with the results of previous studies.et al. have also reported that having new rural cooperative medical insurance significantly improved the HRQoL of residents.et al. reported that esophagectomy for cancer had a temporary negative impact on most aspects of self‐reported HRQoL, which typically recovered within the first postoperative year.For patients with EC, compared with the western region, people from the east or the northeast had lower EQ‐5D utility scores, inconsistent with the results mentioned above.For patients with esophageal precancerous lesions, our finding that the western patients suffered lower EQ‐5D utility scores than the eastern and northeastern patients could be explained by the unequal economic development between China's eastern and western areas. The economic conditions and healthcare services in the western areas lag behind the eastern areas because of the limitations of geographical location. Our results suggested that patients with diplomas of junior high school or undergraduate or above had lower EQ‐5D utility scores that patients with diplomas of primary school or below, which may be because the highly‐educated patients suffered higher stress from jobs and from living a faster‐paced life.The ability to place a value on the physical and emotional experiences of patients undergoing screening is important in the quality‐adjustment of any survival advantage that might be afforded by cancer screening.One potential limitation is that this study was a cross‐sectional survey rather than a longitudinal study. It did not provide a comprehensive description of the temporal trend of HRQoL. However, as a key part of the CanSPUC, we will continue with the long‐term follow‐up survey in subsequent years. In addition, EQ‐5D‐5L, a new version of the EQ‐5D questionnaire has been developed with a higher sensitivity,In conclusion, the section of our study based on the EQ‐5D instrument substantially provided the detailed HRQoL utility values of EC patients across mainland China, which will be informative for future cost‐utility analyses. We also provided information about the variables affecting the HRQoL of EC patients. Psychological intervention, social support, early diagnosis, and early treatment, and critical illness insurance are needed to help to improve the quality of life in patients. The findings of influencing factors are beneficial for future EC prevention and control efforts.The authors confirm that there is no conflict of interest.


There is no standardized guideline to screen, image, or refer patients with non‐alcoholic fatty liver disease (NAFLD) to a specialist. In this study, we used transient elastography (TE) to examine the fibrosis stages at which patients are first diagnosed with NAFLD. Subsequently, we analyzed metabolic markers to establish cut‐offs beyond which noninvasive imaging should be considered to confirm NAFLD/non‐alcoholic steatohepatitis fibrosis in patients.Charts spanning July 2015–April 2018 for 116 NAFLD patients who had TE performed were reviewed. Univariate and multivariate analysis of metabolic markers was conducted.P = 0.01) and A1c (P = 0.05) were significantly different. Optimal cut‐offs for these markers to detect liver fibrosis on TE were AST >43 U/L and A1c >6.6%. The logistic regression function combining these two variables to reflect the probability (P) of the patient having advanced fibrosis (F3–F4) on TE yielded the formula: P = eR/(1 + eR), where R = −8.56 + 0.052 * AST + 0.89 * A1c.At the first hepatology visit, TE showed 73% F0–F2 and 27% F3–F4. Univariate analysis showed that high‐density lipoproteins (HDL), hemoglobin A1c (A1c), aspartate transaminase (AST), and alanine transaminase (ALT) were significantly different between the F0–F2 and F3–F4 groups. Multivariate analysis showed that AST . Diabetes (A1c >6.6%) and AST >43 U/L were the most predictive in identifying NAFLD patients with advanced fibrosis on imaging. We proposed a formula that may be used to prioritize NAFLD patients at higher risk of having advanced fibrosis for specialist referral and imaging follow‐up. In this study, NAFLD patients at a tertiary care center are stratified by fibrosis stage and a logistic regression analysis is conducted to identify common metabolic markers most predictive of high risk NAFLD patients. We establish laboratory value cutoffs for the two most significant biomarkers to help guide timely and appropriate referral of NAFLD/NASH patients from primary care setting to a specialist. Non‐alcoholic fatty liver disease (NAFLD) and its more severe inflammatory form, non‐alcoholic steatohepatitis (NASH), are two of the most common etiologies of liver disease in the United States today. Around 10% of patients with NAFLD will progress to NASH, with up to 25% of this subset developing cirrhosis and half of the subset dying from associated complications.NAFLD/NASH is often asymptomatic, so initial suspicion for the condition can follow incidental findings of abnormal liver enzyme levels.The aim of our retrospective study was twofold. First, given the nonstandardized manner in which NAFLD/NASH is diagnosed in the primary care setting, we conducted a cross‐sectional analysis to investigate which stage of liver fibrosis patients appear to have on USE by the time they present to a specialist for suspected NAFLD/NASH. Second, we performed a univariate and multivariate analysis on serum metabolic markers of this patient population to establish lab value cut‐offs beyond which noninvasive imaging such as USE should be considered by future providers to more promptly evaluate patients for significant NAFLD/NASH fibrosis.This is a retrospective cross‐sectional study on 116 adult patients aged 23–79 years who were referred to a hepatologist at a tertiary care center for NAFLD/NASH between July 2015 and April 2018. In order to focus solely on patients with NAFLD/NASH without other confounding etiologies of liver disease, patients who had chronic liver disease from an etiology other than NAFLD/NASH, such as alcohol , viral hepatitis, and biliary disease, were excluded. All charts of included patients were reviewed to verify that the diagnosis of NAFLD/NASH was correctly assigned and were not fibrosis of other etiologies misclassified as NASH. The study was approved by the institutional review board (IRB) at our center. All patients underwent US‐based transient elastography (TE) using FibroScan. The following demographic, clinical, and laboratory data were recorded: age, gender, BMI, glucose, albumin, lipid panel, hepatic function panel, platelets, and hemoglobin A1c (A1c).All patients had TE performed by an experienced operator. An exam was considered reliable if interquartile range (IQR) was less than 15%. A patient was considered to have F0–1 fibrosis if kPa was 2.5–7, F2 if kPa was 7.1–9.5, F3 fibrosis if kPa was 9.6–12.5, and F4 if kPa was >12.5.P = 0.05. Univariate analysis among categorical variables was performed using the unpaired T‐test. Variables that were significant on univariate analysis were included in multivariate analysis. Area under the receiver operating characteristic curve (AUROC) was used to validate a variable's ability to distinguish between degrees of fibrosis. Youden index was used to estimate appropriate cut‐off values for significant variables.Statistical analysis was performed using GraphPad and R. Significance level was set at n = 85), while 27% had stages F3–F4 fibrosis (n = 31) . Ten of the patients in the F0–F2 group and two of the patients in the F3–F4 group had some alcohol use recorded. Although not every patient had a liver biopsy, elastography fibrosis staging did correlate with histological results in 76.0% of the 33 patients who underwent a liver biopsy with documented results (Table ). Correlation was defined as being classified within the same F0–F2 or F3–F4 category when comparing elastography results to biopsy results.A total of 116 patients were included in the study. Mean age was 52.6 ± 14.4 years, with 64.6% female and 35.4% male. TE was performed using FibroScan and, at the first hepatology appointment, showed that 73% had stages F0–F2 fibrosis (P < 0.0001), alanine transaminase (ALT) (P = 0.0009), high‐density lipoproteins (HDL) (P = 0.0304), and A1c (P < 0.0001) levels. Multivariate analysis excluding patients with missing data showed significant differences in AST  and A1c  levels. There was no difference in BMI, low‐density lipoproteins (LDL), alkaline phosphatase (ALK), platelets (PLT), and albumin levels  (e is Euler's number 2.72.The AUROC curve was used to evaluate the ability of AST and A1c to discriminate between F0–F2 and F3–F4 patients (Fig. NAFLD is a growing epidemic in the United States. Analysis of liver ultrasound data between 1988 and 1994 reported that 19% of adults had NAFLD, while a meta‐analysis of studies from 2006 to 2014 estimated an increased NAFLD prevalence of 24%.et al. recording a prevalence as high as 41.0%.et al. explored the prevalence of NAFLD and advanced fibrosis among T2DM patients and found 72% to have NAFLD and 21% to have advanced fibrosis.In order to more promptly identify NAFLD patients with potentially significant fibrosis from the primary care setting, laboratory markers must be used to help guide decision‐making on when to order noninvasive imaging and refer to a specialist for follow‐up. Various scores and algorithms have been developed that include a wide variety of markers from basic liver function panels to proteins such as γ‐GT or α2‐macroglobulin, indicative of liver fibrosis.To help providers more promptly identify NAFLD patients at risk of advanced fibrosis in clinical settings such as endocrine or primary care clinics, we established an equation to calculate the probability that a NAFLD patient will have stages F3–F4 fibrosis on noninvasive imaging based on their AST and A1c. While other scores and algorithms have been published, each has its own pros and cons. The NAFLD Liver Fat Score and the BARD score do not distinguish between stages of fibrosis.In conclusion, the main goal of our study was to identify laboratory parameters most indicative of advanced fibrosis on noninvasive imaging in patients suspected to have NAFLD. To that end, AST >43 and A1c >6.6% appear to be most indicative in our cohort. These parameters should be routinely screened for in primary care or algorithmically incorporated into the electronic medical record through our proposed algorithm to help provide better guidance on which patients should be evaluated by TE for fibrosis secondary to NAFLD. In this way, NAFLD patients most at risk of having significant liver fibrosis can be more promptly identified and be referred to an appropriate specialist for follow‐up.Dina L. Halegoua‐De Marzio is a consultant for Gilead and Interept. She also receives research grant support from BMS, Intercept, Genfit, Gilead, Inventiva, and Galmed. Jonathan M. Fenkel is a consultant for Gilead. He receives research grant support from Abbvie, Conatus, Gilead, and HCV‐Target. None of these companies or organizations had a role in the study design, data collection, analysis, or publication of this manuscript.Christine Shieh and Dina L. Halegoua‐De Marzio designed the study. Christine Shieh and Matthew L. Hung analyzed and interpreted the data. Christine Shieh drafted the article. All were involved in critical revision of the article.


T1‐weighted, T2*‐weighted and quantitative susceptibility mapping (QSM) information. The proposed method consists of four steps: Highly iterative image co‐registration, manual segmentation on the average training‐data template, supervised learning for pattern recognition, and a final convex optimisation step imposing further spatial constraints to refine the solution. This led to solutions in greater agreement with manual segmentation than the standard Morel atlas based approach. Furthermore, we show that the multi‐contrast approach boosts segmentation performances. We then investigated whether prior knowledge using the training‐template contours could further improve convex segmentation accuracy and robustness, which led to highly precise multi‐contrast segmentations in single subjects. This approach can be extended to most 3D imaging data types and any region of interest discernible in single scans or multi‐subject templates.Thalamic alterations occur in many neurological disorders including Alzheimer's disease, Parkinson's disease and multiple sclerosis. Routine interventions to improve symptom severity in movement disorders, for example, often consist of surgery or deep brain stimulation to diencephalic nuclei. Therefore, accurate delineation of grey matter thalamic subregions is of the upmost clinical importance. MRI is highly appropriate for structural segmentation as it provides different views of the anatomy from a single scanning session. Though with several contrasts potentially available, it is also of increasing importance to develop new image segmentation techniques that can operate multi‐spectrally. We hereby propose a new segmentation method for use with multi‐modality data, which we evaluated for automated segmentation of major thalamic subnuclear groups using  It is considered the central relay station for sensory and motor information as nearly all sensory and motor signals are sent to the thalamus prior to reaching the cortex. It is also thought to have an integrative role as thalamic structures receive, process, sort and send information between specific subcortical and cortical areas, and might be involved in regulation of sleep and wakefulness, memory, emotion, consciousness, awareness, attention, ocular motility, learning and motor control processes Jürgen, .The thalamus is composed of several major substructures. The internal medullary lamina is a thin sheet of white matter that runs longitudinally through the thalamus separating it into medial and lateral regions. In the anterior part, the internal medullary lamina forks to isolate the anterior thalamic nucleus; thus, thalamic nuclei can be broken down into four regions based on their position relative to the lamina, that is, anterior, medial, lateral and posterior subnuclear groups  sequence. Tourdias, Saranathan, Levesque, Su, and Rutt —a relatively new quantitative MRI contrast—has also gained increasing interest in recent times. Deistung et al.  illustraTraditionally, however, the anatomy of the thalamus has been inferred from post‐mortem tissue examinations. The most widely used histological atlas was developed by Morel et al.  segmentation, pattern recognition and a final refinement step using a convex formulation.Details on study subjects, MRI acquisition and pre‐processing are given below. For now, we will assume all subject data has been spatially co‐registered to a common reference space, from which multi‐subject templates (one for each contrast) have been computed. We will also assume hereafter (specific details given below) that regions of interest have been manually traced (at least once) with the aid of such templates. We then consider the following multi‐class labelling problem.2.1ℓ class labels, with each class referring to a segmented region. Let n = n1n2n3, be the vectorised volume in template space. For each xi, we have c image intensities or MRI parameter values, T1‐, T2*‐weighted signals and QSM. We then identify a set of possible class labels, X as yi ∈{0, 1, 2, 3}.For each voxel in the image volume domain 2.2m‐dimensional feature vector. Features describe objects, in our case voxel information reflecting thalamic tissue properties. In this work, we set out to develop a multi‐spectral approach to exploit features from several contrast types, whereby the key features are intensity/MRI parameter values: fk(xi), k = 1, 2, 3 from T1, T2*‐weighted MRI and QSM, which return different contrast characteristics for tissues with different local concentrations of water, iron, myelin and so forth. For each contrast, we also selected additional features which are the result of an empirical study of the feature space. These are mean, μ and standard deviation, σ, across the 26‐neighbourhood and intensity/MRI parameter values for the six closest 3D neighbours in each contrast, leading to a feature space of m = 27 dimensions. All features were then scaled by their normalised variance . It should be noted that this feature space was selected for the present application through an investigation of classification accuracy versus feature space dimensionality on a data subset. This might differ for other data types and/or target regions.In the reference coordinate system, we then build the feature space: 2.3Y for n voxels. Each template voxel is therefore described by the pair , where ψi is the m‐dimensional feature vector of voxel xi and yi is its label. We define the labelled training dataset as T=ψ1y1…ψnyn. We set out to solve a classification problem based on supervised learning, in which we train a classifier to derive a decision mapping for new observations. Initially, we explored the performance of several classification methods including support vector machine, random forest, Naive‐Bayes, k‐nearest neighbours (k‐NN) and Parzen classifiers using a data subset. In this preliminary study, we obtained greater accuracy with two classifiers: k‐NN (k = 3) and Parzen classifiers, which are described in  = l given the measured data f(x). From this, winner‐takes‐all segmentation can be derived selecting the class with the highest probability value in each voxel. This, however, often results in scattered clusters of misclassified voxels that break the smoothness and continuity of segmented regions. Hereby, therefore, we introduce an additional convex optimisation step to further improve the spatial cohesiveness of tissue segments.Classification routines yield a posterior probability distribution x in the image domain Ω. Because this is a hard combinatorial problem, we use a convex relaxation to facilitate the optimisation, see  problem:u defined as the L1‐norm of a discrete finite‐difference approximation of the two‐dimensional gradient  and N = 116  healthy subjects, respectively. The latter was an ageing cohort previously investigated with QSM  and test (Dataset II) datasets consisted of 2.7The imaging protocol, QSM reconstruction and spatial normalisation methods (briefly summarised below) are essentially identical to those in a previous ageing study  under the following imaging protocol:T1‐weighed data were acquired using a 3D MPRAGE sequence  = 7°, echo time (TE) = 4.37 ms, receiver bandwidth (RB) = 140 Hz per pixel, echo spacing = 11.1 ms, repetition time (TR) = 2,500 ms; 256 × 256 × 192 matrix dimensions , 1 × 1 × 1 mm3 voxel size, twofold parallel acceleration and further 7/8 partial Fourier undersampling for phase encoding. The total scan time was 5:08 min.T2*‐/susceptibility‐weighted data were obtained from a fully flow‐compensated, 3D spoiled gradient‐echo sequence. Scan parameters were: α = 17°, TE = 20 ms, RB = 100 Hz per pixel, TR = 28 ms; matrix, 256 × 224 × 80 with voxel resolution of 1 × 1 × 2 mm3; and twofold parallel acceleration for phase encoding. The total scan time was 5:32 min. All susceptibility maps were inspected to exclude subjects with severe calcifications or microbleeds.2.82.8.1QSM is a relatively new contrast modulated by the local content of chemical species that have different magnetic susceptibilities than soft tissue and water  gradient echo MRI sequences. Multi‐channel complex data were combined for optimal phase reconstruction using an adaptive algorithm Walsh, , precede2.8.2T2*‐weighted magnitude images were affine co‐registered to their corresponding bias‐corrected MPRAGE volume using ANTs  bias corrected . The references throughout were the internal white matter lamina of the thalamus, and other contrast variations consistent with prior knowledge based on the Morel atlas. Three major thalamic subregions, namely, lateral, medial and posterior nuclear groups, were manually traced as illustrated in Figure N = 16  individual test datasets were delineated for algorithm validation . For simplicity, however, in this study, we report two representative summary measures: The global classification error rate  and the true positive (TP) rate for non‐background (i.e. subnuclear group) regions. In the first instance, algorithm performance evaluations were carried out for the thalamus nuclear group segmentation from high SNR templates (Dataset II average), including a comparison with standard Morel atlas based segmentation. Subsequently, error measures were also computed for individual  test data.T1‐weighted MRI) registration in ANTs  incorporating both rigid (multi‐resolution) and non‐linear , given the trained classifier, its mapping is applied to independent test data yielding class labels and posterior probabilities.multi‐class convex segmentation, where posterior probabilities are used in the data term of the convex optimisation formulation defined in Equation In Algorithm https://github.com/veronicacorona/multicontrastSegmentation.git.Algorithm 1Procedural steps for multi‐contrast segmentation.The supervised learning and convex segmentation steps of the algorithm were implemented in MATLAB R2017b  and are available at Training stageInput: Multi‐contrast training data1: Spatial normalisation2: Contrast‐specific template generation3: Manual (or atlas based) template segmentation4: Supervised classification (training)Output: Trained classifierNew segmentationInputs: Multi‐contrast test data and a trained classifier5: Spatial normalisation6: Supervised classification (testing)7: Multi‐contrast convex segmentationOutput: Regional contoursRemark 1All MRI datasets in this study were spatially standardised via nonlinear co‐registration to a common coordinate system. This enabled custom training from a single set of regional contours in template space. Future applications of this algorithm could alternatively consider using manual tracings from each individual training dataset. The only requirement is that all contrasts for a given subject must share a common frame of reference.3In what follows we present our numerical results obtained independently for Dataset II described in section 3.1k‐NN and Parzen classifiers  the extent of putative thalamic regions. Therefore, segmentation results are reported in Table 3.2.3λ, that requires optimisation for optimal solution smoothness. In this study, λ was optimised empirically on a small subset: For 3‐NN, we chose λ = 1, and for Parzen λ = 5. We then confirmed the validity of this choice calculating overall classification errors (on the N = 116 template dataset) for a range of regularisation parameters. Results from this validation experiment are summarised in Table The 3‐NN and Parzen based segmentation results in Figure 3.2.4T1‐, T2*‐weighting and QSM all provide differentially relevant information about internal thalamic boundaries. In order to substantiate this claim, we estimated algorithm performance for all the available combinations, that is, one, two or three data types, using the same 27‐dimensional feature space that was previously optimised. CS errors are shown in Figure A unique aspect of the proposed algorithm is that it can integrate information from several MRI contrasts capturing simultaneously different views of the anatomy. In this study, we hypothesised that 3.3w in N = 6 test subset, we explored how classification error varies as a function of w. This is illustrated in Figure w = 0.4.We also confirmed that constraining the data term for fidelity with training‐average tissue priors is feasible and desirable to improve accuracy and robustness in single‐subject thalamic subnuclei segmentation. The consistency weight, w with greater certainty and specificity.The primary aim of this analysis was to evaluate if performance with this extension was pre‐processing method dependent. In light of Figure From a qualitative standpoint, Figure 4T1, T2*‐weighting and QSM. We confirmed that using all information maximised performance, and also found evidence suggesting that QSM was the most informative contrast type for this segmentation problem. Different data types or new implementations for other anatomical regions will require new calibration work.In this study, we present a data‐driven method to segment several internal thalamic boundaries using multi‐contrast MRI data. We had three imaging contrasts available to drive the segmentation procedure: This work was motivated by the observation that study‐wise MRI templates obtained using highly iterative non‐linear coregistration routines are showing superb anatomical detail over and above what can be inferred from individual datasets. It is therefore unsurprising these are being used to trace regions of interest that are not available from automated segmentation tools  will be optimal for other regions and/or data types. This warrants further investigation. We also would like to point out that future work could also formulate the classification and convex optimisation steps as a joint problem to reduce the propagation of errors. Additionally, in future work the TV segmentation term will be extended to 3D.It is also worth noting that posterior probability maps from individual datasets can be noisy. In this study, with a view to make the convex segmentation algorithm more robust in this regime, we introduced an additional data fidelity weight in An important consideration for early adopters of this method is that posterior probability maps can only be obtained from models trained on separate data. In this study, we had sufficient power to split the dataset into training and test subsets. However, future studies wanting to implement this algorithm with limited available data may consider, for example, an algorithmic extension for synthetic data augmentation.In conclusion, this work presented a highly versatile multi‐contrast segmentation framework and its successful application to identify thalamic substructures. In practice, this method can be seen as the basis to segment any brain structure identifiable (or labelled) on any widely available template or atlas (e.g. the Ilinsky atlas (Ilinsky et al.,


Endobronchial ultrasound (EBUS) elastography assists in the differentiation of benign and malignant lymph nodes (LNs) during transbronchial needle aspiration (TBNA). However, previous studies have not compared B‐mode sonographic images (BSIs) and EBUS elastography images (EEIs) with final pathological diagnoses in radiologically normal‐sized (computed tomography [CT]‐negative) LNs.Consecutive patients with CT‐negative LNs, who received EBUS‐TBNA, were retrospectively reviewed. Images of BSIs and EEIs of each LN were stored and independently evaluated. EEIs were assessed by calculating the stiffness area ratio . The receiver operating characteristic curve was used to calculate the cutoff value for the SAR. Diagnostic test parameters were evaluated for each EBUS finding.P < 0.001). At the SAR cutoff of 0.41, the sensitivity, specificity, positive predictive value, negative predictive value (NPV), and diagnostic accuracy rate (DAR) of elastography were 88.2%, 80.2%, 78.9%, 89.0%, and 83.9%, respectively. The logistic regression analysis showed that elastography was the strongest predictor of malignancy . The highest NPV (96.6%) was achieved with a combination of BSIs and EEIs.A total of 132 patients (149 LNs) were enrolled, and the median SAR of malignant LNs was significantly higher than that of benign LNs (0.58 vs. 0.32, EBUS elastography predicted malignant LNs with a high DAR and NPV in CT‐negative LNs. The NPV was highest when EEIs were combined with BSIs. Therefore, the combined evaluation of CT‐negative LNs using EEIs and BSIs may help bronchoscopists perform EBUS‐TBNA more efficiently.Endobronchial ultrasound elastography accurately predicted malignancy with a high diagnostic accuracy rate and negative predictive value in radiologically normal‐sized lymph nodes. The additional use of B‐mode sonographic features resulted in a higher negative predictive value.Endobronchial ultrasound elastography can guide the accurate collection of specimens with transbronchial needle aspiration, even in radiologically normal‐sized lymph nodes. It can also readily distinguish benign and malignant lymph nodes, thus avoiding unnecessary punctures. Endobronchial ultrasound elastography accurately predicted malignancy with a high diagnostic accuracy rate and negative predictive value in radiologically normal‐sized lymph nodes. The additional use of B‐mode sonographic features resulted in a higher negative predictive value. Endobronchial ultrasound‐guided transbronchial needle aspiration (EBUS‐TBNA) has developed into the most widely used standard sampling technique for mediastinal and hilar lesions, irrespective of their benign or malignant status.Recently, one cohort study reported that proper preoperative staging was associated with survival benefits in patients with non‐small cell lung cancer (NSCLC).For diagnosing and staging with EBUS‐TBNA in patients with lung cancer, it is necessary to accurately select the LNs to be punctured. B‐mode sonographic findings  and vascular patterns on power Doppler mode have previously been reported as useful EBUS parameters for distinguishing benign and malignant LNs.Elastography is an ultrasonographic method for generating objective strain images of tissue compressibility. EBUS elastography has made it possible to detect and colorize the hardness of LNs. Hard tissues are shown in blue, while intermediate tissues are shown in green, and soft tissues are shown in yellow or red. A recent meta‐analysis characterized the differences between benign LNs and malignant LNs when evaluated using EBUS elastography.Elastography has been previously used in the breast, thyroid, liver, pancreas, and gastrointestinal tract.The aim of this study was to evaluate the diagnostic utility of EBUS elastography, and identify the most accurate EBUS parameters for the differentiation of benign and malignant CT‐negative LNs.The medical records of consecutive patients with mediastinal and/or hilar LNs, who underwent EBUS‐TBNA at the university hospital of the University of Occupational and Environmental Health, Japan (UOEH) between April 2015 and November 2018, were retrospectively analyzed. Targeted LNs that underwent EBUS‐TBNA had enlargements on chest CT (short axis diameter ≥ 5 mm) or high [18F]‐fluorodeoxyglucose (FDG) uptake on PET‐CT . CT‐negative LNs were defined by a short axis diameter of less than 1 cm on chest CT. Before EBUS‐TBNA, each patient underwent thin section CT, using a 1 mm slice thickness. This study was approved by the institutional review board (No. H30‐074), and written informed consent was obtained from all participants. EBUS‐TBNA was used when clinically required, and was not performed solely for the purposes of this study.z‐axis modulation with Real E.C. technique, Toshiba Medical Solutions). All PET‐CT images were obtained using a PET‐CT scanner . Patients received an intravenous administration of 4.0 MBq/kg 18F‐FDG in the sitting position after fasting for 6 hours, and a PET‐CT scan 60 minutes later. Chest CT images were reviewed by two pulmonologists (KU and SH) who were blinded to the results of the final pathological diagnoses, as well as the BSIs and EEIs. PET‐CT images were evaluated by an independent and blinded radiologist.Chest CT scans were performed using a single source 32‐detector or 64‐detector CT scanner . The settings were as follows: 1 mm collimation, 0.5 second rotation time, 27 or 53 pitch , and 120 kV. The noise level was set at 10 standard deviations using automatic tube current modulation  and a 22‐gauge needle . All procedures were performed by residents under the supervision of a bronchoscopist (KU) with sufficient experience, as previously reported.A dedicated ultrasound processor  was used to evaluate EBUS images in B‐mode sonography and EBUS elastography, and vascular patterns were evaluated with power Doppler ultrasound. The target LN was evaluated in B‐mode ultrasonography at its maximum diameter, and the images were stored in JPEG format. EEIs evaluated at the same location were also stored in JPEG format, as previously reported.The BSIs and EEIs were reviewed by two pulmonologists (KU and SH), who were blinded to the results of the pathological diagnoses and CT images. Based on a previously reported BSI classification,The image analysis software program ImageJ 1.45sThe evaluation of the utility of a combination of elastographic and B‐mode sonographic features was based on a previous retrospective study.Histological and cytological specimens were evaluated by an independent cytologist and pathologist blinded to the BSIs and EEIs. The final diagnosis of each LN was based on the pathological evidence obtained from EBUS‐TBNA, surgery, and bacterial culture, or the demonstration of the absence of disease progression on clinical and radiological follow‐up (at least six months).P‐values. P‐values <0.05 were considered statistically significant. The statistical analyses were performed with EZRData are presented as frequency, median (range), and percentage. The sensitivity, specificity, positive predictive value (PPV), NPV, and DAR were calculated for each LN according to standard definitions. ROC analysis and Youden index (sensitivity + specificity − 1) were used to calculate the optimal cutoff for the SAR value. Based on a two‐sided hypothesis, comparisons between the two groups were examined using the Fisher's exact test or Mann‐Whitney U test. All B‐mode sonographic and EBUS elastographic parameters, which were potentially predictive of malignant LNs,Between April 2015 and November 2018, EBUS‐TBNA was performed in 464 patients (663 LNs) at the UOEH hospital. A total of 143 (164 CT‐negative LNs) patients underwent EBUS‐TBNA; among these patients, six (eight LNs) with insufficient follow‐up and five (seven LNs) with missing imaging data were excluded. Thus, 132 patients (149 LNs) were eventually included in the study.Table P < 0.001)  Fig . The sen001) Fig .Figure P < 0.001), heterogeneous echogenicity (P < 0.001), absence of CHS (P = 0.004), presence of CNS (P = 0.048), and malignancy on elastography (P < 0.001). Logistic regression analysis revealed that when EBUS elastography was suggestive of malignancy, the EBUS elastographic finding was the strongest independent predictor of malignant LNs . The sensitivity, specificity, PPV, NPV, and DAR were 88.2%, 80.2%, 78.9%, 89.0%, and 83.9%, respectively. Additionally, by adding B‐mode sonography to EBUS elastography, the sensitivity of LN malignancy increased to 98.3% (58/59) and the NPV increased to 96.6% (28/29).Table P = 0.046). On EBUS images, all three LNs with a short‐axis diameter less than or equal to 5.0 mm were finally diagnosed as benign. The median short‐axis size of the false negative LNs on EBUS elastography was 9.3 mm.Table This is the first study to compare detailed EBUS findings, including elastography, with pathological diagnoses in CT‐negative LNs. The results suggested that EBUS elastography can be more predictive of malignancy compared to other B‐mode findings. Combined evaluation using EBUS elastography and B‐mode sonography in CT‐negative LNs yielded the highest NPV for predicting malignancy in small‐sized mediastinal and hilar LNs.P = 0.001); however, the sensitivities were equivocal .Various EBUS elastography evaluation methods for mediastinal and hilar LNs have been described.The present study demonstrated that quantitative evaluation of EBUS elastography using the SAR could accurately predict malignancy in CT‐negative LNs with a high NPV; this result is supported by two prior retrospective studies,Small‐sized breast lesions have been reported to result in false negative diagnoses on breast ultrasonography with elastography.LNs can be hardened due to calcification in patients with a history of pulmonary tuberculosis, pneumoconiosis, or anthracosis; this can result in false positive results for malignancy on EBUS elastography.A retrospective study of 1061 mediastinal and hilar LNs reported that 96.0% (381/397) were benign, based on the following features: round shape, distinct margin, heterogeneous echogenicity, and CNS.Two recent meta‐analyses have reported the prevalence of occult LN metastasis to range from 12.8% to 15.0% in NSCLC patients with CT‐negative LNs.Small LNs on EBUS tended to be finally diagnosed as benign. To date, no studies have evaluated the final diagnosis  of CT‐negative LNs based on 1 mm size increments on EBUS and CT. This is the first study to report that such differences in LN size affect the frequency of malignancy in CT‐negative LNs. Furthermore, the final diagnosis was benign in all LNs with a short‐axis diameter less than or equal to 5.0 mm on EBUS. This result is similar to that of a previous retrospective study, which reported a final benign diagnosis for all 14 patients with mediastinal LNs smaller than 5.0 mm on EBUS images.This study had several limitations. First, it utilized a single‐center retrospective design, and had a relatively small sample size. Second, the same bronchoscopist did not perform all the procedures; therefore, the skill of the bronchoscopist may have affected EBUS image analysis. Third, the BSIs and EEIs were only analyzed with static images; therefore, image selection bias may also have occurred. Fourth, this study also included LNs that had not been surgically removed in patients with lung cancer. Nevertheless, the true benignity of the LNs was clinically and radiologically evaluated. Further prospective, multicenter trials are required to confirm the results of this study.In conclusion, the high DAR of EBUS elastography can predict malignancy in CT‐negative LNs with a higher NPV compared to B‐mode findings. Additionally, EBUS elastography demonstrated the highest NPV for malignancy, when used in combination with B‐mode sonography. Consequently, the combined evaluation of CT‐negative LNs using EEIs and BSIs may be helpful for bronchoscopists to perform EBUS‐TBNA efficiently.The authors declare that they have no competing interests.


Bordetella pertussis, the causative agent of whooping cough, and identified nine novel small RNAs (sRNAs) that were transcribed during the bacterial colonization of murine tracheas. Among them, four sRNAs were more strongly expressed in vivo than in vitro. Moreover, the expression of eight sRNAs was not regulated by the BvgAS two‐component system, which is the master regulator for the expression of genes contributing to the bacterial infection. The present results suggest a BvgAS‐independent gene regulatory system involving the sRNAs that is active during B. pertussis infection.We performed RNA sequencing on  BGBordet–GengouBprB. pertussis sRNADIGdigoxigeninIGRintergenic regionRACErapid amplification of cDNA endRgtArepressor of glutamate transportRNA‐seqRNA sequencingsRNAsmall RNASSStainer–ScholteWTwild typeBordetella pertussis causes whooping cough, a contagious respiratory disease that has been resurging recently despite high vaccination coverage.Bordetella media, the BvgAS system activates the transcription of a set of genes (Bvg‐activated genes) including various virulence genes. Conversely, this system is inactivated at temperatures lower than 26°C or in the presence of MgSO4 (40–50 mm) or nicotinic acid (10–20 mm), and B. pertussis eventually does not express the Bvg‐activated genes. The former bacterial state is called the Bvg+ phase, and the latter is the Bvg− phase. The BvgAS system is considered to play a major role in the expression of genes involved in the pathogenesis of B. pertussis; however, recent in vivo studies found that several Bvg‐activated genes were repressed in B. pertussis colonizing the respiratory tracts of mice.et al. also reported that approximately 30% of all genes were differentially expressed between in vitro and in vivo conditions.B. pertussis clinical strain, the BvgAS system of which was dysfunctional due to a spontaneous mutation in the bvgS gene, was isolated from a pertussis patient.B. pertussis, many types of sRNAs have been identified or predicted by an in silico analysis and RNA‐seq on the bacteria grown in vitro.B. pertussis sRNAs are involved in the regulation of in vivo gene expression, which is associated with the establishment of bacterial infection. In the present study, we performed in vivo RNA‐seq on B. pertussis colonizing the murine tracheas and identified novel sRNAs that were strongly expressed during colonization.Bacterial small RNAs (sRNAs) are functional noncoding RNA molecules that range between 50 and 500 nucleotides in length.In vivo expression of sRNAs were analyzed by RNA‐seq using tracheas of three mice independently infected with B. pertussis‐type strain 18323. This organism was grown at 37°C on Bordet–Gengou agar  containing 1% HIPOLYPEPTON , 1% glycerol, 15% defibrinated horse blood, and 10 µg/mL ceftibuten (BG plate). The bacteria recovered from the colonies on BG plates were suspended in Stainer–Scholte (SS) broth650 of 0.2, and cultured at 37°C for 14 hr with shaking. Bacterial CFUs were estimated from OD650 values according to the following equation: 1 OD650 = 3.3 × 109 CFU/mL. Seven‐week‐old male C57BL/6J mice  were anesthetized with a mixture of medetomidine , midazolam , and butorphanol  at final doses of 0.3, 2, and 5 mg/kg body weight, respectively, and intranasally inoculated with B. pertussis 18323 (1 × 107 CFU) in 50 μL of SS medium using a micropipette with a needle‐like tip. On Day 4 after inoculation, mice were killed with pentobarbital, and the tracheas were excised and frozen in liquid nitrogen. Total RNA was extracted from the tracheas with TRIzol Reagent , treated with RNase‐Free DNase , and then purified with the PureLink RNA Mini Kit (Thermo Fisher Scientific) according to the manufacturer's instructions. Bacterial and murine ribosomal RNAs (rRNAs) were simultaneously depleted from the total RNA using the Ribo‐Zero rRNA Removal Kit for Human/Mouse/Rat and Gram‐Negative Bacteria . The quality and quantity of RNA samples were assessed using the Agilent 2100 Bioanalyzer . Reverse transcription was performed with the rRNA‐depleted RNA, SuperScript III Reverse Transcriptase (Thermo Fisher Scientific), and Random Primer N9 (Takara Bio), and double‐stranded DNA was then synthesized using DNA polymerase I . The resultant complementary DNA (cDNA) was sheared to approximately 600 bp fragments using Covaris S220  and purified with Agencourt AMPure XP beads . Libraries of the cDNA fragments were then prepared with the KAPA Library Preparation Kit  and TruSeq adapters (Illumina), and sequenced with a HiSeq 2500 (Illumina) to obtain 101 bp single‐end reads. The sequenced reads were mapped to the genomic DNA of B. pertussis 18323 (GenBank: NC_018518.1) using CLC Genomics Workbench, version 8.0.3 . All animal experiments were approved by the Animal Care and Use Committee of the Research Institute for Microbial Disease, Osaka University, and conducted according to the Regulations on Animal Experiments at Osaka University. The numbers of total sequenced reads were 54, 143, and 137 million, and 0.06%, 0.72%, and 0.04% of the reads in each sample were aligned to the genome sequence of B. pertussis 18323. A large portion of the reads aligned to the bacterial genome corresponded to protein‐, rRNA‐, and transfer RNA‐coding sequences , whereas the residual reads were aligned to the intergenic regions: the numbers of reads were 1180, 1316, and 836, respectively. We predicted that these noncoding sequences located in the intergenic regions are potential sRNA sequences. Among these sRNA candidates, we selected nine novel sRNAs, for which the number of sequenced reads was more than 20 counts, and designated them B. pertussis sRNA (Bpr)1–9 according to a previous studyhttps://blast.ncbi.nlm.nih.gov/Blast.cgi) and sRNAMap (http://srnamap.mbc.nctu.edu.tw).In vitro and in vivo expression of Bpr1–9 were compared by qRT‐PCR analyses. Total RNA was extracted and purified from the tracheas of mice independently infected with B. pertussis Tohama, a vaccine strain, and two clinical strains B. pertussis 18323. Total RNA was also prepared from the four strains of B. pertussis and Bvg+‐ and Bvg−‐locked mutants derived from B. pertussis 18323 grown in vitro using the PureLink RNA Mini Kit and RNase‐Free DNase according to the manufacturer's instructions. The Bvg+‐ and Bvg−‐locked mutants, which constitutively express the Bvg+ and Bvg− phenotypes, respectively, were constructed by the site‐directed mutagenesis of BvgS to replace Arg with His at position 570 and to delete the region of amino acid positions from 542 to 1020, respectively,bvgS‐C3‐pABB‐CRS2‐Gm and ΔbvgS‐pABB‐CRS2‐GmEscherichia coli DH5α λpir, and then transconjugated into B. pertussis 18323 by triparental conjugation with the helper strain E. coli HB101 harboring pRK2013,in vitro‐cultured bacteria were reverse transcribed into cDNA using the PrimeScript RT Reagent Kit (Takara Bio) with random hexamers in a total volume of 20 µL. The transcription levels of target RNAs were estimated from the amounts of the resultant cDNA measured with the StepOnePlus Real‐Time PCR System  using the Power SYBR Green PCR Master Mix (Thermo Fisher Scientific) and the primers listed in Table B. pertussis 18323 colonizing murine tracheas were significantly higher  than those in in vitro‐cultured bacteria  and the Bvg−‐locked mutant. These results indicate that the expression of Bpr1–7 and 9 is independent of the BvgAS regulatory system, whereas that of Bpr8 is BvgAS dependent.a Figure . By conts Figure . The in s Figure . By contB. pertussis 18323 was confirmed by rapid amplification of cDNA end (RACE) and Northern blotting. For the determination of the transcription start and termination sites of the Bpr, 5′‐ and 3′‐RACE were performed using a SMARTer RACE 5′/3′ Kit (Takara Bio) according to the manufacturer's instructions. In brief, total RNA was extracted from in vitro‐cultured B. pertussis 18323 and polyadenylated by poly(A) polymerase (New England Biolabs). After reverse transcription by SMARTScribe Reverse Transcriptase, the resultant cDNA was used as a template for PCR with Universal primer and each bpr‐specific primers  and one termination site (3280298) were detected in the transcripts of Bpr5 (528 and 342 bases), indicating the presence of two overlapping transcripts of different length. Northern blotting was performed using a DIG Northern Starter Kit . For production of digoxigenin (DIG)‐labeled RNA probes, partial antisense strands of bpr and recA genes were amplified from B. pertussis 18323 using appropriate primers  extracted from in vitro‐cultured B. pertussis 18323 was subjected to electrophoresis in a 1.5% denaturing formaldehyde agarose gel, transferred to a positively charged membrane , and UV cross‐linked to the membrane. The membrane was then independently incubated with DIG‐labeled RNA probes for each Bpr and recA, respectively, followed by alkaline phosphate‐conjugated sheep anti‐DIG immunoglobulin G, and visualized with CDP‐Star. Northern blotting using the RNA probes for Bpr4, 8, and 9 detected a single band, whereas Bpr5 migrated as two bands  that was found to reduce the translation of BP3831, a periplasmic amino acid‐binding protein of an ABC transporter, by base pairing with the 5′ untranslated region of BP3831 mRNA.B. pertussis. In the present study, we identified nine types of novel sRNAs that were strongly expressed during the bacterial colonization, and demonstrated that the expression of four types of sRNAs  was stronger in vivo than in vitro. To the best of our knowledge, this is the first study to identify the in vivo strongly expressed sRNAs of B. pertussis. Bpr4, 5, 8, and 9, which were strongly expressed in vivo, may be involved in regulating the expression of genes necessary for the bacterial colonization or infection. In Salmonella enterica serovar Typhimurium, PinT, a PhoP‐induced sRNA, was shown to be upregulated by up to 100‐fold during the infection, and regulated the expression of the invasion‐associated effectors and virulence genes required for intracellular survival.et al. also reported that Ysr170, a strongly expressed sRNA in Yersinia pestis invading host cells, contributed to the bacterial intracellular survival.B. pertussis. In addition, we found that the expression of Bpr1–7 and 9 was not regulated by the BvgAS system. Although the BvgAS system was previously considered to be the master virulence regulator in B. pertussis,in vitro and in vivo conditions,in vivo gene expression. Several groups reported the PlrSR two‐component system and BspR/BtrA, an anti‐σ factor, as accessory regulatory systems downstream of BvgAS, which may play a part in this complex gene regulatory system in vivo.B. pertussis infection. Further research is currently in progress in our laboratory to identify genes whose expression is regulated by the sRNAs and elucidate the mechanisms by which the sRNAs regulate the gene expression.sRNAs regulate the expression of genes involved in a wide variety of physiological processes in bacteria, including the adaptation to host environments and virulence.The authors declare that there are no conflict of interests.


CRISPR loss‐of‐function screens in 484 cell lines to systematically investigate cellular drug mechanism‐of‐action. We observed an enrichment for positive associations between the profile of drug sensitivity and knockout of a drug's nominal target, and by leveraging protein–protein networks, we identified pathways underpinning drug sensitivity. This revealed an unappreciated positive association between mitochondrial E3 ubiquitin–protein ligase MARCH5 dependency and sensitivity to MCL1 inhibitors in breast cancer cell lines. We also estimated drug on‐target and off‐target activity, informing on specificity, potency and toxicity. Linking drug and gene dependency together with genomic data sets uncovered contexts in which molecular networks when perturbed mediate cancer cell loss‐of‐fitness and thereby provide independent and orthogonal evidence of biomarkers for drug development. This study illustrates how integrating cell line drug sensitivity with CRISPR loss‐of‐function screens can elucidate mechanism‐of‐action to advance drug development.Low success rates during drug development are due, in part, to the difficulty of defining drug mechanism‐of‐action and molecular markers of therapeutic activity. Here, we integrated 199,219 drug sensitivity measurements for 397 unique anti‐cancer drugs with genome‐wide  CRISPR screens in 484 cancer cell lines to systematically investigate anticancer drug mechanism of action, yielding insights into the genetic contexts and cellular networks underpinning drug response.This study integrates pharmacological and  An array of biochemical, biophysical, computational and cellular assays are used to investigate drug mechanism‐of‐action  . We expanded on published single agent drug sensitivity data  and 86% of all possible drug/cell line IC50 measurements have been experimentally evaluated  2 which explained 2.8% of the total variance , we analysed the measurements of the screens separately. Analysis of the drug response variation across cell lines revealed that PC 1 (28.7% variance captured) was significantly and negatively correlated with cell line growth rate , particularly for chemotherapy agents and cell cycle inhibitors  and gene fitness effects  across the 484 cell lines  of the anti‐cancer drugs screened  of the 358 drugs with target annotation and for which the target was knocked‐out with the CRISPR‐Cas9 library, we identified significant drug–gene pairs with their putative targets  which were not significantly associated with the CRISPR loss‐of‐function measurements of their nominal targets  had an association with either the target (26.3%) or a functionally related protein , and significant associations were predominantly found with proteins further away in the PPI network, close to the average length of all paths (lG = 3.9). As an example, MIEN1 gene expression is positively correlated with multiple EGFR and ERBB2 inhibitors, which can be explained, not by a functional relationship, but more likely by genomic co‐localisation with ERBB2 on chromosome 17. Hence, CRISPR‐Cas9 screens are powered to discriminate genes which are likely to be functionally linked to drug response.The strongest drug–gene pair associations were between a drug and its canonical target(s) rather than components of the PPI network, and significance decreased  as the interaction distance increased Fig A. To excEGFR inhibitors are the most abundant drug class in our set, and we observed that multiple inhibitors (e.g. cetuximab) showed significant associations with EGFR and known pathway members, for example SHC1 and GRB2  of the tested drugs had no significant drug–gene associations. A number of possible technical and biological factors may underpin this observation. In support of a link between drug selectivity and significant gene–drug associations  displayed no significant association with any PI3K isoform  and the remaining compounds (n = 22) are correlated with core fitness proteins closely connected in the PPI network.Our analysis can also provide insights into possible off‐target activity of drugs. Unsupervised clustering of the drug–gene associations effect sizes (betas) revealed classes of inhibitors with similar targets and mechanism‐of‐action Fig I. Of notBCL2 family member myeloid cell leukaemia 1 (MCL1) were strongly and nearly exclusively associated with their putative target, suggesting these are potent and specific compounds in cells , is significantly associated with MCL1 inhibitors sensitivity , where MCL1 inhibitors are in clinical development  . Models trained with only CRISPR displayed overall better predictions compared to models only trained with gene expression, and models trained with both data types out‐performed all others  and we searched independently for significant associations between each measurement type (drug response or gene fitness) and 519 genomic  and 15,368 gene expression features  had one or more robust pharmacogenomic associations , and based on CRISPR dependency data, for multiple members of the cIAP pathway, including BIRC2, MAP3K7 and RNF31 . Critically, the strength of these associations reflects specificity and polypharmacology of the cancer drugs, with highly selective and potent drugs showing the strongest associations with their nominal target. Significant drug–gene associations define networks of protein interactions that are functionally related with drug targets and underpin drug response. This revealed a previously unappreciated interaction between et al, et al, et al, Preclinical biomarker development is an important step in drug discovery and is associated with increased success rates during clinical development  drug polypharmacology which is difficult to deconvolute using single‐gene knockout data; (ii) intrinsic difference between protein inhibition and knockout; (iii) a dosage‐dependent response leading to incomplete inhibition of the drug target; (iv) functional redundancy between protein isoforms resulting in less penetrant effects with gene knockout; and (v) technical limitations of CRISPR‐Cas9 screens such as the introduction of DNA double‐strand breaks and sgRNA on‐target and off‐target effects variability across cancer cell lines. We expect that some of these issues can be addressed by expanding this analysis to integrate other types of functional genomic screens, such as CRISPR inhibition, which might mimic drug inhibition more closely and does not introduce double‐strand breaks.We used CRISPR loss‐of‐function data sets to comprehensively study drug mechanism‐of‐action in cancer cells. CRISPR screening data are now available for many cell lines, and the profiling of compounds across cell line panels is already regularly performed, and so this approach could become a routine step during drug development. In particular, it is likely to have utility during the hit‐to‐lead or lead optimisation stages of drug development to select compound series with optimal potency and selectivity. It could also be useful for novel and uncharacterised cell active compounds, particularly if integrated with orthogonal experimental (e.g. such as kinobead assays) or computational approaches (e.g. drug pocket binding) to find direct targets and interrogate mechanisms‐of‐action. The utility of this approach is likely to expand as the availability of CRISPR knockout screening data, and other data sets such as CRISPR activation and inhibition, increases across ever larger collections of highly annotated cancer cell models. In conclusion, this study illustrates a new approach for investigating cellular drug mechanism‐of‐action that can be applied to multiple critical aspects of drug development.http://cancer.sanger.ac.uk/cell_lines/download). Detailed cell line model information is available through Cell Model Passports database (https://cellmodelpassports.sanger.ac.uk/)   annotation was manually curated from literature  project  were estimated comparing samples with the respective control plasmid. Gene‐independent deleterious effects induced by copy number amplifications in CRISPR‐Cas9 screens .The CRISPR‐Cas9 screens for the 484 cancer cell lines considered in this study  were assl, et al  and withet al, n_components) set to 10. For the drug response data set, and only for the PCA analysis, missing values of each drug were imputed using the drug mean IC50 response across the rest of the cell lines. Imputation was not required for the CRISPR‐Cas9 data set since the matrix had no missing values.Principal component analysis was performed using scikit‐learn  and the null model which excludes the CRISPR gene fitness scores vector e and its parameter β1(θ1^). The parameter inference is performed using maximum likelihood estimation:We statistically assessed the significance of each association by performing likelihood‐ratio tests between the alternative model . Contrary to performing the adjustment across all tests, per drug correction has the following benefits: (i) associations assembled from the different screening platforms (GDSC1 and GDSC2) are kept separate hence not biasing for measurement type; and (ii) drugs with responses across larger subsets of cancer cell lines, for example Nutlin‐3a response across TP53 wild‐type cell lines, display stronger associations than most drugs; thus, correcting across all drugs would retain more associations from these drugs at a specific error rate, i.e. 10%, compared to the rest.We tested all the single‐feature pairwise associations between the 480 compounds and the 16,643 genes, making a total of 7,988,640 tested associations. et al, igraph Python wrapper   on a negative logarithmic scale, and it is calculated only when the standard relation in an assay is known to be “=”. Activity thresholds were defined according to the target protein family, based on the Illuminating the Druggable Genome consortium (IDG https://druggablegenome.net/ProteinFam) as follows: Kinases: ≤ 30 nM; GPCRs: ≤ 100 nM; Nuclear Receptors: ≤ 100 nM; Ion Channels: ≤ 10 μM; Others: ≤ 1 μM.In order to define whether a drug is considered active in an Conceptualisation: EG and MJG; Formal analysis: EG; Data curation: EG, CP, DvdM, ABa, HL, JTL, BS, CC, FI, SF and MJG; Drug response acquisition and processing: DvdM, TM, ABa, LR, WY, EL, JH, CT, CH, IM, FT, JM, ABe and HL; Drug annotation: EG, AS‐C, GP, FMB, PJ, EAC, ARL, CC and MJG; Writing original draft preparation: EG and MJG; Writing, reviewing and editing: all authors; Visualisation: EG; Supervision: ABa, AL, JTL, BS, CC, FI, SF and MJG; Funding acquisition: SF and MJG.This work was funded in part by AstraZeneca. M.J.G. receives funding from AstraZeneca. M.J.G., F.I. and A.R.L. receive funding from Open Targets, a public–private initiative involving academia and industry. F.I. performs consulting for the CRUK‐AstraZeneca Functional Genomics Centre. J.T.L., B.S., C.C. and S.F. are current employees of AstraZeneca and hold stock in AstraZeneca.Expanded View Figures PDFClick here for additional data file.Dataset EV1Click here for additional data file.Dataset EV2Click here for additional data file.Dataset EV3Click here for additional data file.Dataset EV4Click here for additional data file.Dataset EV5Click here for additional data file.Dataset EV6Click here for additional data file.Dataset EV7Click here for additional data file.Dataset EV8Click here for additional data file.Review Process FileClick here for additional data file.