What is the association between donor-recipient biological relationship and outcomes after living donor kidney transplantation?In this cohort study including more than 70 000 transplants, after taking donor, recipient, and immunologic factors into account, transplants from donors who were biologically related to their recipients had a higher rate of allograft failure compared with transplants from unrelated donors.These findings suggest that kidney donors who are related to their recipients may share genetic or socioenvironmental predispositions to kidney disease that shorten allograft longevity. The proportion of living donor kidney transplants from donors unrelated to their recipients is increasing in the US.To examine the association between donor-recipient biological relationship and allograft survival after living donor kidney transplant.This retrospective cohort study used Organ Procurement and Transplantation Network data on US adult living donor kidney transplants (n = 86 154) performed from January 1, 2000, to December 31, 2014, excluding cases in which recipients previously received a kidney transplant (n = 10 342) or key data were missing (n = 2832). Last follow-up was March 20, 2020.Donor-recipient biological relationship.The primary outcome was death-censored allograft failure. Univariate and multivariable time-to-event analyses were performed for death-censored allograft failure for the overall cohort, then separately for recipients with and without primary diagnoses of cystic kidney disease and for transplants from African American and non–African American donors.P = .03). When stratified by primary disease, this association persisted only for recipients without cystic kidney disease. When stratified by donor race, this association persisted only for transplants from African American donors.Among the 72 980 transplant donor and recipients included in the study , 43 174 (59%) donors and recipients were biologically related and 29 806 (41%) were unrelated. Donors related to their recipients were younger  and less likely to be female (24 848 [58%] vs 19 142 [64%]) or White (26 933 [62%] vs 23 081 [77%]). Recipients related to their donors were younger , more likely to be female (18 035 [42%] vs 10 530 [35%]), and less likely to have cystic kidney disease (2530 [6%] vs 4600 [15%]). Related pairs had fewer HLA mismatches overall . After adjustment for HLA mismatches, donor and recipient characteristics, and transplant era, donor-recipient biological relationship was associated with higher death-censored allograft failure (hazard ratio, 1.05; 95% CI, 1.01-1.10; In this cohort study, living donor kidney transplants from donors biologically related to their recipients had higher rates of allograft failure than transplants from donors unrelated to their recipients after HLA matching was accounted for. Further study is needed to determine which genetic or socioenvironmental factors are associated with this finding. This cohort study uses US adult living donor kidney transplant data to examine the association between donor-recipient biological relationship and allograft survival after living donor kidney transplant. Among the most notable shifts is a marked increase in the frequency of living kidney donation from donors without biological relationships to their recipients. In 2000, approximately 1 in 4 donor-recipient pairs was not biologically related; by 2019, this proportion had more than doubled.1Despite efforts to increase kidney transplant rates in the US, the annual number of living kidney donors has stagnated during the past 2 decades.8 found similar allograft survival for recipients who are related to their donors and those who are not, although these analyses have not consistently accounted for the association between biological relationship and HLA mismatching. Of importance, unrelated recipients have a higher likelihood of acute rejection early after transplant, perhaps reflecting a greater degree of HLA matching when donors and recipients are related.9 However, related donor-recipient pairs may also share genetic predispositions to kidney disease and/or decreased kidney function, potentially partly explaining the higher rate of postdonation kidney failure observed in living donors who are related to their recipients.12 Given that some transplant candidates may have multiple potential donors from whom to choose, a better understanding of the association between donor-recipient biological relationship and posttransplant outcomes can help inform donor selection. We therefore sought to determine whether living donor kidney transplants from biologically related donors have higher rates of allograft failure after accounting for degree of HLA mismatching.The association between the marked increase in living unrelated kidney transplant and allograft outcomes is incompletely understood. Prior investigators13 This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.We identified all adult donor-recipient pairs for living donor kidney transplants performed in the US from January 1, 2000, to December 31, 2014, using the Organ Procurement and Transplantation Network Standard Transplant Analysis and Research file (2020Q1). This study interval was selected to ensure at least 5 years of follow-up for all transplant recipients. After excluding prior transplant recipients and pairs missing data on key variables, a final cohort for the primary analysis comprised 72 980 donor-recipient pairs . Secondary outcomes were composite allograft failure , recipient death, and 1-year rejection.2 and Wilcoxon rank sum tests for categorial and continuous variables, respectively. Unadjusted death-censored allograft survival was assessed using the Kaplan-Meier method and log-rank test. We performed univariate and multivariable time-to-event analyses for death-censored allograft failure using Cox proportional hazards regression models for the overall cohort, then separately for recipients with and without a primary diagnosis of cystic kidney disease, and finally for transplants from African American donors and non–African American donors. Model covariates were chosen based on clinical significance. In the first adjusted model, only donor-recipient biological relationship and HLA-A, -B, and -DR mismatches were included. A second model added donor and recipient characteristics, and a third model also added transplant era. Cox proportional hazard regression models were then recalculated using composite allograft failure and recipient death as outcomes.Donor and recipient demographic variables and number of HLA matches were compared for related vs unrelated donor-recipient pairs using χ2 tests, followed by univariate and multivariable logistic regression. Causes of allograft failure for related vs unrelated transplants were compared using χ2 tests.We next performed post hoc analyses comparing 1-year rejection and causes of allograft failure for related vs unrelated transplants among the subsets of patients with data available for each. The proportion of recipients in each group experiencing rejection within 1 year of transplant was compared using χFinally, to determine whether results would be similar if we included transplants that occurred more recently , we repeated all time-to-event analyses mentioned above using a cohort of transplants performed from January 1, 2000, to December 31, 2019.Statistical significance was identified by a 2-sided α = .05. All analyses were performed using Stata/MP15 statistical software (StataCorp).A total of 72 980 living donor kidney transplants  that occurred from 2000 to 2014 were included in the primary analytic cohort , less likely to be female (24 848 [58%] vs 19 142 [64%]), and less likely to be White (26 933 [62%] vs 23 081 [77%]) . RecipieRelated donor-recipient pairs had higher degrees of HLA matching compared to unrelated pairs . OverallP < .001) (P = .005). Finally, further inclusion of study era attenuated the association, which remained significant  (Allograft failure was observed after 5214 (17%) unrelated and 8155 (19%) related transplants, whereas recipient death was observed after 5162 (17%) unrelated and 8205 (19%) related transplants. Death-censored allograft failure was similar after related and unrelated transplants  . After fP = .03) .P = .03), this association was not present among recipients with cystic kidney disease   .APOL1 (OMIM 603743) risk variants to our findings,15 the cohort was stratified by donor race. In fully adjusted models, donor-recipient biological relationship was associated with increased death-censored allograft failure in transplants from African American donors  but not transplants from non–African American donors   .P = .02)  .Short-term rejection within 1 year of transplant occurred in 6092 (8%) of transplants, including 2925 (10%) from unrelated donors and 3167 (7%) from related donors  or more recently with genetic testing for known monogenic variants associated with cystic disease.18 As a result, related donor candidates with potential evidence of disease, those who are unable to be adequately screened, or those for whom the intended recipient has a genetic variant that has yet to be identified are likely to be excluded, potentially accounting for the absence of an increased risk of allograft failure from related donors in patients with cystic kidney disease in this study.One possibility for the association is that unrecognized shared genetic predispositions to kidney disease between recipients and biologically related donors contribute to the observed inferior outcomes. This hypothesis is consistent with prior evidence that donors who are biologically related to their recipients are more likely to develop end-stage kidney disease compared with their counterparts who are unrelated to their recipients.APOL1 risk variants, can also be challenging during donor evaluations, given that most individuals and allografts with these genetic variants will not experience kidney disease or allograft failure, respectively. The adjusted models in this study revealed that donor-recipient biological relationship was predominantly associated with allograft failure in transplants from African American donors, a finding perhaps attributable to a higher proportion of related donors with APOL1 risk variants associated with shorter allograft survival and lower postdonation kidney function.20 The results of this study also suggest a greater association of donor-recipient biological relationship with allograft failure in mismatched pairs. This finding may reflect the fact that the small proportion of unrelated pairs with no HLA mismatches have a genetic distance that is more similar to related pairs than other unrelated pairs. Given that the observed frequency of 0 HLA mismatches is higher among unrelated pairs than expected by random chance from the general population, additional similarities not captured in this study are likely between these donors and recipients.Complex polygenic predispositions to kidney failure, on the other hand, are not as readily identifiable, and many are yet to be recognized. In addition, the presence of known risk factors for kidney disease, such as 21 Although it is theoretically possible that recipients of allografts from close relatives would behave differently than recipients of allografts from unrelated donors resulting in differences in medication adherence after transplant, there is no evidence to support this notion. Furthermore, this hypothesis is contradicted by evidence that medication nonadherence after kidney transplant is predominantly driven by practical limitations , health literacy, and medication beliefs—factors likely not expected to be influenced by the donor-recipient relationship.25 Economic factors also play a large role in access to and outcomes after transplant.27 Although we included recipient insurance type and employment status in adjusted models, these surrogates may not adequately capture socioeconomic status, especially given the small proportion of recipients using Medicaid as primary payer.Alternatively, it is possible that the shared predisposition to kidney disease among related donors and recipients with kidney disease is not exclusively genetic but also associated with environmental factors, including socioeconomic status, that are shared by related individuals. Shared environmental exposures may be distant and hard to identify, such as childhood nutritional deficiencies, access to care, allostatic load, or environmental toxins.This study did not find a significant association between donor-recipient biological relationship and 1-year rejection in adjusted models. Similarly, small differences in causes of allograft failure among transplant failures were of unclear clinical significance despite achieving statistical significance. However, both of these analyses were limited by incomplete or missing data. Improving understanding of the differences in outcomes for related vs unrelated transplants requires improved data capture of these elements.2 examined 3-year allograft survival rates for kidney transplants from parental donors, spousal donors, and other unrelated donors and found similar allograft survival between groups despite differences in HLA matching. However, their study was limited by short follow-up and did not adjust for HLA mismatching when analyzing outcomes. Another study,4 of 1000 living donor transplants from 1966 to 1994, found no difference between haploidentical living unrelated and living related transplants. However, this single-center analysis was limited by the small proportion (9%) of donors unrelated to their recipients and was performed in a different era. Multiple investigators have demonstrated increased rates of acute rejection after living unrelated kidney transplants compared with living related kidney transplants, presumably because of higher degrees of HLA mismatching.8 Our results extend these findings to conclude that, although related and unrelated donor-recipient pairs have similar outcomes in unadjusted analysis, conditional on all else (including HLA matching), living unrelated kidney transplants appear to experience longer allograft survival.Previous investigators have also studied the association between donor and recipient biological relationship and allograft outcomes. Terasaki et al9 For now, on the basis of this study’s findings, if choosing between an unrelated and related donor with similar degrees of HLA matching, it may be reasonable to choose an unrelated donor with no family history of kidney disease. Given the modest effect size of the study, the larger imperative is understanding the mechanism of this association. Broader investigational genetic testing of donors and recipients with extended follow-up is warranted to investigate the possibility of shared genetic predispositions to kidney disease as a mechanism underlying these findings. Although long-term biobanking of donor and recipient serum samples to allow future testing for as-yet-undiscovered risk variants should also be considered, these findings underscore the need for living donor programs to not overlook existing opportunities to identify genetic risk.29Ultimately, delineating the causes of the association between donor-recipient biological relationship and allograft failure is key to understanding the implications of this finding. For example, it would be inappropriate to infer that paired kidney exchanges that involve 2 related donor-recipient pairs should be pursued simply for the sake of producing unrelated donor-recipient pairs because both donors would still be related to recipients with kidney failure. In addition, it still seems that optimizing HLA matching should be prioritized.30 However, these variables could not be incorporated, given that 38% of donors were missing data on at least one. A high degree of concordance between donor and recipient race in the study cohort also precludes the ability to differentiate independent associations of each of these factors with posttransplant outcomes. Information about family history of kidney disease for living kidney donors was lacking, which may be more informative than donor-recipient biological relationship. Finally, the study cohort is only composed of transplants occurring in the US, and the results therefore may not be generalizable to other countries given known differences in outcomes for US vs other kidney transplant recipients.31This study has strengths and limitations. Strengths include the use of a large, nationally representative cohort and clearly identified biological relationships between the donor and recipient. Limitations include the possibility of residual confounding because of donor or recipient characteristics not included here. Although dialysis exposure and preemptive status at transplant were similar between groups, unmeasured differences in the timing of transplant for each group could have confounded the results, especially given missing data regarding pretransplant dialysis time. Additional donor characteristics that may be relevant had a high degree of missingness in the data set. For example, the Living Donor Kidney Donor Profile Index includes several donor variables absent from the study models, including systolic blood pressure, smoking, and body mass index or weight.Living donor kidney transplants from unrelated donors had longer allograft survival than those from related donors after HLA mismatching and donor and recipient characteristics were accounted for. Combined with prior evidence of an increased risk of kidney failure among donors related to their recipients, these findings should lead to additional study of the genetic and socioeconomic factors underlying familial clustering of kidney disease. These findings underscore the need for more precise risk assessments of kidney disease to guide living kidney donor screening and selection.


Chronic loss of Augmenter of Liver Regeneration (ALR) results in mitochondrial myopathy with cataracts; however, the mechanism for this disorder remains unclear. Here, we demonstrate that loss of ALR, a principal component of the MIA40/ALR protein import pathway, results in impaired cytosolic Fe/S cluster biogenesis in mammalian cells. Mechanistically, MIA40/ALR facilitates the mitochondrial import of ATP-binding cassette (ABC)-B8, an inner mitochondrial membrane protein required for cytoplasmic Fe/S cluster maturation, through physical interaction with ABCB8. Downregulation of ALR impairs mitochondrial ABCB8 import, reduces cytoplasmic Fe/S cluster maturation, and increases cellular iron through the iron regulatory protein-iron response element system. Our finding thus provides a mechanistic link between MIA40/ALR import machinery and cytosolic Fe/S cluster maturation through the mitochondrial import of ABCB8, and offers a potential explanation for the pathology seen in patients with ALR mutations. ALR have been described for this disorder. Some of these documented mutations result in premature stop codon, while the R194H mutation has been shown to affect the protein stability through increasing dissociation of its cofactor FAD  results in mitochondrial myopathy and cataract, and combined respiratory chain deficiency . Severalctor FAD . Cellulactor FAD . While pErv1-null yeast . Iron destined for Fe/S cluster synthesis is imported into mitochondria by mitoferrin 1/2 and is delivered to ISCU by frataxin. The fully assembled Fe/S clusters are then transferred to Fe/S cluster-containing proteins. Because several cytosolic proteins also require Fe/S clusters for their function, another set of cytosolic proteins, collectively named as the cytosolic iron/sulfur cluster assembly (CIA) machinery, facilitates the incorporation of Fe/S clusters into cytosolic proteins . Howevermyopathy . Conditill death . Previoull death . Additio. brucei .To support adequate Fe/S cluster biogenesis, iron first enters the cells through transferrin receptor-mediated uptake. It can subsequently be stored in the cytoplasm or incorporated into heme and Fe/S clusters in the mitochondria . While aIn yeast, Erv1p, together with Mia40, is part of the oxidative folding machinery required for the import of a subset of mitochondrial proteins. Mia40 oxidizes the cysteine residues within imported proteins, and the reduced Mia40 is re-oxidized by Erv1p, effectively recycling Mia40 for further use . A similIn this paper, we demonstrate that cytoplasmic Fe/S cluster maturation depends on a functional mitochondrial protein import system consisting of ALR and MIA40. Mitochondrial ALR facilitates the mitochondrial import of ABCB8, a protein needed for the maturation of cytosolic Fe/S proteins. Thus, a reduction in ALR and eventual reduction in the cytosolic Fe/S clusters leads to activation of IRP1 and subsequent cellular iron accumulation.Alr in mouse embryonic fibroblasts (MEFs) using pooled siRNA and demonstrated a significant reduction of Alr at the mRNA level  mRNA levels were increased in wild type MEFs with Alr downregulation  knockout (KO) MEFs with Alr siRNA. Alr knockdown in these cells resulted in a significant reduction in ALR protein levels  shRNA in order to examine the effect of Alr downregulation in the absence of IRP1, but we only achieved 40% downregulation of Aco1 at the mRNA level  and achieved a significant decrease in Aco1 transcript levels  using species-specific primer sets confirmed that only endogenous, but not exogenous, Alr was downregulated by siRNA -inducible expression system that allows for monitoring of protein accumulation after DOXY treatment. HEK293 cells stably expressing reverse tetracycline transactivator (rtTA3) were transfected with a tetracycline-responsive bicistronic construct containing GFP and a 6x-His-tagged gene of interest. This system results in mitochondrial protein accumulation in a time-dependent manner in response to DOXY treatment . To corrALR downregulation . Mouse embryonic fibroblasts were cultured in Dulbecco's Modified Eagle's Medium  supplemented with 10% fetal bovine serum (FBS), 100 U/ml penicillin, and 100 U/ml streptomycin. We have verified that Ireb2 was knockout in the Ireb2 KO MEFs. HEK293 cells were purchased from ATCC and cultured in Minimum Essential Medium  supplemented with 10% FBS, 100 U/ml penicillin, 100 U/ml streptomycin, and 1 mM sodium pyruvate. We have not performed separate verification since receiving the HEK293 cell line from ATCC. The cell lines were regularly using PCR-based mycoplasma detection kit (ABM) and were negative for mycoplasma contamination.Aco1 shRNA constructs were purchased from Openbiosystems and packaged into lentiviral vector as above. The culture supernatant was mixed with polybrene to a final concentration of 15 μg/ml and used to infect MEFs. To select for cells stably expressing Aco1 shRNA, MEFs were maintained in complete media with 6 µg/mL puromycin (Sigma) after infection. pLenti-rtTA3 (Addgene) was packaged into lentiviral vector in HEK293T cells after cotransfection with pSPAX and pMD2.G plasmids. Culture supernatant was used to infect HEK293 as described above, and cells with stable integration of viral genome were selected with 10 µg/mL Blasticidin (Invitrogen).Full-length and cytoplasmic isoforms of ALR were cloned into pHIV-eGFP vector. The resultant vector was packaged into lentiviral vector in HEK293T cells after cotransfection with pSPAX and pMD2.G plasmids. ALR, MIA40, TIM23, and mouse Alr and Aco1 were purchased from Dharmacon. siRNA against 3’UTR sequence of mouse Alr were purchased from Qiagen. siRNAs were transfected into HEK293 or MEF using Dharmafect 1 Transfection Reagent (Dharmacon). Plasmids were transfected into MEF using Lipofectamine 2000 reagent (Invitrogen) and into HEK293 cells using either Lipofectamine 2000 reagent (Invitrogen) or calcium phosphate transfection.Transfection siRNA against human RNA was isolated from cells using RNA-STAT60 (Tel-Test), and reverse transcribed with Taqman Reverse Transcription Reagents (Invitrogen) according to manufacturers’ instruction. Quantification of relative gene expression was done using Fast SYBR Green Master Mix (Applied Biosystems) and run on 7500 Fast Real-Time PCR system (Applied Biosystems). Primer sequences is included in the 55FeCl3 (Perkin Elmer) was first conjugated to nitrilotriacetic acid  before adding transferrin (Tf) in 2:1 molar ratio. The mix was incubated at room temperature for one hour. 55Fe-transferrin was separated from unbound 55Fe by running on PD-10 desalting column . For uptake experiment, cells were incubated with media containing 55 μg/ml 55Fe-Tf for two hours. Residual membrane-bound iron was removed by washing cells with cold 200 μM deferoxamine (DFO) in phosphate buffered saline (PBS). Radioactivity was quantified on a Beckman scintillation counter, and the results were normalized to cellular protein content of the same sample. For steady state cellular 55Fe content, cells were incubated with 280 μM of 55FeNTA for two days. The subcellular fractions were isolated and radioactivity in the fraction was measured as described above.Mitochondria from cells were purified using Mitochondrial Isolation Kit for Cells (Pierce) according to manufacturer’s instruction.Complex I and II activity were measured with Complex I and Complex II Enzyme Activity Microplate Assay Kit (MitoScience), respectively, according to manufacturer’s instruction. Xanthine oxidase activity was measured using AmplexRed Xanthine Oxidase Activity Kit (Invitrogen). For cytosolic aconitase assay, cytosolic fraction was concentrated on Amicon Ultra-0.5 Centrifugal Filter Unit with 10 kDa cutoff (Millipore) and the buffer was exchanged to PBS. The aconitase activity in the concentrated fraction was measured using Aconitase Activity Assay kit (MitoScience).60 hr after transfections, cells were trypsinized and equal number of cells were replated onto Seahorse XF96 cell culture plates in complete media. Cells were allowed to attach for 8 hr, and then washed with PBS twice to remove the complete media before incubating with assay medium . Oxygen consumption was measured using Seahorse Extracellular Flux Analyzer according to manufacturer’s instructions, and mitochondrial oxygen consumption was calculated as baseline oxygen consumption minus non-mitochondrial oxygen consumption (measured in the presence of 50 μM of rotenone and antimycin A).60 hr after siRNA transfection, cells were stained with propidium iodide (PI) and Hoechst 33342. Cell death rate was calculated as the number of PI-positive nuclei over total nuclei number.Twenty-four hours after transfection with Firefly reporter construct and Renilla luciferase construct , cells were solubilized in 1x passive lysis buffer (Promega). The lysates were loaded onto a 96 well plate, and the luciferase activity was determined using Dual Luciferase Assay System (Promega) with Modulus Microplate Reader (Turner Biosystems). The ratio between firefly and renilla luciferase activities was normalized to that of empty vector under corresponding treatments.ATP synthase F1 subunit alpha (ATP5a), cytochrome oxidase subunit 4 (COX4) and α-tubulin (Abcam), FLAG (Sigma), β- actin , GPAT (a generous gift from Dr. Roland Lill [University of Marburg]), or 70 kDa subunit SDH (Invitrogen) overnight, before the addition of horseradish peroxidase (HRP)-conjugated secondary antibodies (Jackson ImmunoResearch). The presence of target protein was visualized using Super Surgical Western Pico ECL substrate (Pierce). Quantification of western blotting image was done using ImageJ (NIH).Proteins were resolved on 4–12% Novex Bis-Tris poly-acrylamide gel (Invitrogen) and blotted onto nitrocellulose membrane (Invitrogen). Approximately 20–40 μg of whole cell lysate and approximately 6–10 μg of cytosolic or mitochondrial fractions were loaded onto the gel. Membranes were incubated with primary antibodies for ABCB8 (made in-house), ABCB7, MIA40, ALR, Tim 23, 6x-His, and GFP (ProteinTech), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), 36 hr after transfection, cells were treated with 1 ug/ml doxycycline, and harvested after 6 hr for mitochondrial fractionation. For carbonyl cyanide 3-chlorophenylhydrazone (CCCP) treatment, 2.5 uM CCCP was added at the fourth hour and the cells were incubated for additional 2 hr. The mitochondrial level of protein of interest is normalized to the GFP levels in the cytosolic fraction from the same sample.Mitochondrial pallets were lysed in PBS containing 1% Triton X100 (Sigma), protease inhibitor (G Biosciences) and 10 mM imidazole . The lysate was cleared via centrifugation and loaded to His Spin Trap spin column . The column was sequentially washed with PBC containing 20, 40, and 80 mM imidazole and eluted with PBS containing 200 mM imidazole. 100 mM DTT was included in the lysis buffer when indicated.Data are presented as mean ± standard error mean (SEM). Statistical significance was assessed with ANOVA, with post hoc Tukey’s test for multiple group comparison. All analysis were conducted using GraphPad Prism nine software. A P-value less than 0.05 was considered statistically significant. public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: i) Acceptance summary:This manuscript provides important mechanistic insights into how mutations in the Augmenter of Liver Regeneration (ALR) impacts iron handling and thus cellular iron content. This has potential implications for ALR in regenerative biology in other systems.Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, including Carlos Isales as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Mone Zaidi as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Thomas S Weiss (Reviewer #3).Thank you for submitting your article "Augmenter of Liver Regeneration Regulates Cellular Iron by Modulating Mitochondrial Transport of ATP-Binding Cassette B8" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential Revisions:1. While the work is interesting the manuscript suffers from a lack of convincing data with regards to sorting out Alr effects that are driven by the cytoplasmic isoform, versus the mitochondrial isoform. The separation between the different isoforms is shown only from figure 3; therefore, the results shown in figure 1 and 2 may have been interpreted differently if the two isoforms were differentiated. For example, in figure 1 the authors show that downregulating Alr had no significant effect on mitochondrial complex I and II activities, however, since there was no differentiation between mitochondrial and cytoplasmic isoforms, the lack of effect on mitochondrial complexes may imply enrichment of the cytoplasmic isoform. Additional data would be helpful.2. The authors describe a stable MEF line expressing Aco1 shRNA that they created in order to test the effects of Aco1 downregulation, however, they achieved only 40% downregulation of Aco1 at the mRNA level. Therefore, they add siRNA for Aco1 and achieved greater decrease in Aco1 transcript levels. Although this technique proved to be more efficient, it is recommended that the authors discuss why the shRNA technique, which is usually very efficient, did not work in this case, as well as how combining shRNA and siRNA is applicable in studying ALR disease.3. Mitochondrial function studies are missing from the paper. The authors mentioned in the result section that their limitation in performing mitochondrial function experiments was due to a difficulty to attain large amounts of mitochondria from MEF cells, as compared to 293 cells, which were used for this purposes. To my knowledge, MEFs are pretty easy in obtaining mitochondria for mitochondrial studies; furthermore, the authors could use more cells or bigger plates to obtain a high amount of mitochondria. Therefore, to my opinion, this explanation for using 293 cells is not valid.4. In the material and method section as well in the figure caption the authors should present more details about how the experiments are performed enabling scientists to reproduce the data: e.g.How long were the cells treated with siRNA before harvesting and analysis? Does the cells after ALR siRNA treatment show signs of apoptosis or cell stress as reported for murine embryonic stem cells after 72h of ALR-siRNA treatment (PMID: 20147447)?How much protein is loaded on the gel?What are the primer sequences for PCR differentiating endogenous and exogenous ALR (3'-UTR)?5. Endogenous expression and localization of ALR isoforms in MEFs and HEK293 cells should be shown (western blot range from 10 to 30 kDa). Figure S3A: There are no visible bands in EV lane in cytosolic and mitochondria fractions, which would correspond to endogenous expression. Essential Revisions:1. While the work is interesting the manuscript suffers from a lack of convincing data with regards to sorting out Alr effects that are driven by the cytoplasmic isoform, versus the mitochondrial isoform. The separation between the different isoforms is shown only from figure 3; therefore, the results shown in figure 1 and 2 may have been interpreted differently if the two isoforms were differentiated. For example, in figure 1 the authors show that downregulating Alr had no significant effect on mitochondrial complex I and II activities, however, since there was no differentiation between mitochondrial and cytoplasmic isoforms, the lack of effect on mitochondrial complexes may imply enrichment of the cytoplasmic isoform. Additional data would be helpful.We have included a representative western blot demonstrating the localization of various isoforms of ALR in MEF . We utilized a pool of 4 siRNA to downregulate ALR in MEF cells. Three out of the four siRNA target regions shared by the long and the short isoform of ALR. Therefore, we would expect that the long isoform of ALR would be targeted equally  compared to the short isoform of ALR. Although we only showed the change in full length ALR in the main figure, we included an uncropped gel in Figure 1 figure supplement 1B that demonstrated downregulation of the short isoform of ALR after siRNA treatment. We have also revised the manuscript to better highlight the fact that siRNA targets both long and short isoforms of ALR. To further corroborate our model, we demonstrated the defect of mitochondrial ABCB8 import in cells with Mia40 downregulation. Given the similar phenotype between ALR and MIA40 downregulation and the fact that ALR and MIA40 together form one of the mitochondrial protein import systems, we deduce that mitochondrial ALR is critical for ABCB8 import into the mitochondria and therefore regulates cellular iron homeostasis.2. The authors describe a stable MEF line expressing Aco1 shRNA that they created in order to test the effects of Aco1 downregulation, however, they achieved only 40% downregulation of Aco1 at the mRNA level. Therefore, they add siRNA for Aco1 and achieved greater decrease in Aco1 transcript levels. Although this technique proved to be more efficient, it is recommended that the authors discuss why the shRNA technique, which is usually very efficient, did not work in this case, as well as how combining shRNA and siRNA is applicable in studying ALR disease.Aco1 expression, thereby creating an artificial condition to test whether ALR still has an effect on cellular iron homeostasis independent of Aco1. We have added discussion in the text.While shRNAs are generally efficient, knockdown efficiency of the commercially available constructs have not been previously validated. It is well-documented that shRNA efficiency can be influenced by multiple factors, including the level of expression, the secondary structure of the shRNA, the location of the targeted sequences, and the exact sequence and thermodynamic property of the shRNA . The purpose of combining shRNA and siRNA is to utilize a multiple-targeting strategy to suppress 3. Mitochondrial function studies are missing from the paper. The authors mentioned in the result section that their limitation in performing mitochondrial function experiments was due to a difficulty to attain large amounts of mitochondria from MEF cells, as compared to 293 cells, which were used for this purposes. To my knowledge, MEFs are pretty easy in obtaining mitochondria for mitochondrial studies; furthermore, the authors could use more cells or bigger plates to obtain a high amount of mitochondria. Therefore, to my opinion, this explanation for using 293 cells is not valid.We have performed additional mitochondrial functional studies in MEFs and did not observe any changes in baseline oxygen consumption with ALR downregulation. The results are now included in Figure 1 figure supplement 1D.4. In the material and method section as well in the figure caption the authors should present more details about how the experiments are performed enabling scientists to reproduce the data: e.g.How long were the cells treated with siRNA before harvesting and analysis? Does the cells after ALR siRNA treatment show signs of apoptosis or cell stress as reported for murine embryonic stem cells after 72h of ALR-siRNA treatment (PMID: 20147447)?How much protein is loaded on the gel?What are the primer sequences for PCR differentiating endogenous and exogenous ALR (3'-UTR)?Thank you for raising this issue. Cells were harvested 48 hours after siRNA treatment for RNA analysis and 60-72hr after siRNA treatment for protein analysis. About 20-40ug of whole cell lysate and around 10ug of mitochondrial fraction were loaded to the gel. Additional details are also now included in figure legends. We did not observe significant cell death with ALR downregulation, and the results are now shown in Figure 1 figure supplement 1C. This difference likely reflects the distinct roles of ALR in differentiated versus undifferentiated cell types. The exogenous ALR sequence is human origin, and we have designed primers targeting specifically for human versus mouse ALR mRNA. The primer sequences are included in Supplemental table 1.5. Endogenous expression and localization of ALR isoforms in MEFs and HEK293 cells should be shown (western blot range from 10 to 30 kDa). Figure S3A: There are no visible bands in EV lane in cytosolic and mitochondria fractions, which would correspond to endogenous expression.The antibody we used has limited detection of mouse ALR. The lack of signal in Figure S3A was limited by short exposure period and the relatively low protein amount (6ug) per lane loaded onto the gel. We confirmed the localization of ALR in a separate western blot experiment shown in Figure 1 figure supplement 1A.


When a tester speaks silently, the patch shows excellent performance in recording the sEMG signals from three muscle channels and recognizing those frequently used instructions with high accuracy by using the wavelet decomposition and pattern recognization. The average accuracy of action instructions can reach up to 89.04%, and the average accuracy of emotion instructions is as high as 92.33%. To demonstrate the functionality of tattoo-like patches as a new human–machine interface (HMI) for patients with loss of voice, the intelligent silent speech recognition, voice synthesis, and virtual interaction have been implemented, which are of great importance in helping these patients communicate with people and make life more enjoyable.Throat cancer treatment involves surgical removal of the tumor, leaving patients with facial disfigurement as well as temporary or permanent loss of voice. Surface electromyography (sEMG) generated from the jaw contains lots of voice information. However, it is difficult to record because of not only the weakness of the signals but also the steep skin curvature. This paper demonstrates the design of an imperceptible, flexible epidermal sEMG tattoo-like patch with the thickness of less than 10 μm and peeling strength of larger than 1 N cm Tattoo-like wearable electronic patches could help patients who have lost the capacity for speech to communicate once again. The aftermath of surgeries for mouth and throat cancers can result in permanent voice loss, but the information needed to decode speech can still be recovered from the movements of facial muscles. Researchers led by Hongmiao Zhang and Lining Sun at China’s Soochow University and Chengkuo Lee at the National University of Singapore have developed flexible sensors that can be applied to the skin to capture this information. In a series of tests with human volunteers, they demonstrated that vocalization-associated muscle activity collected from these patches could be computationally decoded with up to 92% accuracy. Similar devices could eventually be coupled to voice synthesizers or other devices to help restore normal speech after cancer surgery.  Treatment can involve surgical removal of the tumor, radiation therapy, and chemotherapy, leaving patients with facial disfigurement as well as temporary or permanent loss of voice, which greatly hinders daily patient communication2.Speech is an important means by which humans communicate and express their emotions and opinions. In the United States, 53,000 adults are expected to be diagnosed with oral and oropharyngeal cancer in 20195. Studies have confirmed that sEMG generated by the muscles of the face and the lower jaw contains useful voice information related to speaking7. Different muscle motion patterns are produced by the contraction of different muscle groups, and the accompanying sEMG signals are different. In silent speech, the muscle groups of the face and the lower jaw correspond to different motion patterns, so it is entirely possible to distinguish the motion patterns from different sEMG signals and identify the internal speech information. Since the 1980s, sEMG from some smaller muscles associated with speech has been analyzed, and the results are promising. Michael S. Morse et al. used four-channel facial sEMG to recognize 10 English words. Their best accuracy rate was 58.0%, using the magnitude as the sEMG feature8. C. Jorgensen et al. used sEMG to perform six-word speech recognition in a real-time simulated environment, in which six words can be used as a control set for NASA's spacecraft Mars Cruiser. M. Janke et al. analyzed and compared sEMG generated from audible, whispered, and silent speech, indicating that speech recognition based on sEMG can be applied to silently mouthed speech9.Surface electromyography (sEMG) is a bioelectrical signal emitted from neuromuscular activity and can be recorded by electrodes on the surface of the human skeletal muscle, which are widely used in clinical medicine, kinematics, etc.10. These defects also practically limit mounting locations to relatively flat regions of the body, such as the forehead, back, chest, forearm, or thigh. The ability to extend the traditional sEMG electrode to measure the sEMG of the jaw is deficient.In fact, it is very difficult to acquire sEMG signals from the jaw and face by traditional sEMG electrodes because of not only the weakness of the signals but also the sharp skin curvature of this area. Traditional sEMG measurements use rigid electrodes coupled to the skin via electrolyte gels affixed with adhesive tape or straps. During the recording, the electrode sheet may be detached from the superficial skin, resulting from the drying of the gel and the movement of the muscle, leading to a decrease in measurement accuracy23. One of the major trends is to apply textiles made of functional yearns and coatings or to use flexible materials to fabricate devices for detecting physiological signals26, conducting drug delivery27, and realizing intuitive human– machine interfaces31. Another trend is the thin-film technique for stretchable electronics and wearables, including epidermal sensors, the epidermal electronic system (EES), and electronic tattoos (e-tattoos), which have demonstrated a wide range of functionalities, including physiological sensing43, on-skin display44, ultraviolet (UV) detection45, transdermal therapeutics34, human–machine interface (HMI)46, prosthetic electronic skin47, and skin-adhesive rechargeable batteries49.Owing to the recent advances and the rapid development in soft materials and micro-electromechanical system (MEMS) fabrication, the emerging field of wearable flexible electronic devices offers a technological solution to measure the sEMG of the face, jaw, neck, etc.10. Lu and colleagues proposed graphene electronic tattoo (GET) electrooculography (EOG) sensors to control a quadcopter wirelessly in real time to demonstrate the functionality of GET EOG sensors for the human–robot interface50. T. Ren et al. manufactured an intelligent laser-induced graphene artificial throat, which can not only generate sound but also detect sound in a single device51. H. Zhang et al. proposed a flexible hybrid device that can be attached to different parts of the body for the real-time monitoring of human physiological signals, such as respiratory information and the radial artery pulse52. It is apparent that using ultrathin dry electrodes instead of wet conductive gel silver/silver chloride (Ag/AgCl) electrodes to couple to human skin is beneficial for expanding the monitoring area for silent speech recognition and improving human comfort.J. A. Rogers et al. proposed EES interfaces that can record sEMG signals from four different bimanual gestures of forearms to control a drone quadrotorGenerally, the ability to accurately and imperceptibly monitor health sEMG is vital for healthcare professionals and patients. The development of machine-learning techniques in data analysis offers much assistance in decoding sEMG signals, which dramatically enhance the reliability of information recognition and expand the application fields. This study illustrates an epidermal sEMG tattoo-like patch that can be laminated on the jaw and face without any additional adhesives and imperceptibly measures the sEMG from a patient who has lost his/her voice. Experiments are conducted, and the sEMG signals are collected when the tester speaks silently. Through wavelet decomposition and machine-learning algorithms, the frequently used action and emotion instructions can be recognized with high accuracy. To demonstrate the functionality of the epidermal sEMG tattoo-like patch for the human–machine interface, action instructions of silent speech recognition are used to control an intelligent car, and emotion instructions are used to control a Bluetooth speaker and virtual interaction in real time Fig. .Fig. 1In10. The filamentary serpentine (FS) mesh electrodes involve bare metal in direct contact with the skin. Figure The electrode layout of the sEMG patch contributes to the magnitude of the electrical noise and crosstalk contamination, such as the electrode size, the interelectrode distance, and the electrode shape. As illustrated in Fig. The fabrication process follows the micromachining procedures described in the “Experimental section”  is used to simulate the deformation and stress distribution of the FS electrodes. Simulation and experimental results indicate that the FS electrode traces can be stretched over 20% (strain levels of skin: 10–20%), where the maximum principal elastic strain in the metals is 11.24% (fracture strain of Cu: 33.3%). The corresponding optical microscope (OM) images of the FS mesh electrodes show that the FS electrodes do not show any cracks when the FS electrode trace is stretched by 20%. More details and figures can be seen in the supplementary information Figs. –S5.The flow diagram of the sEMG system for intelligent silent speech recognition and the human–machine interface are depicted in Fig. Baseline: The tester was asked to remain still and breathe quietly for 5–10 s to keep the muscles relaxed.Action instructions : The tester was asked to speak five action instructions  silently.Emotion instructions : The tester was asked to speak six emotion instructions  silently.For patients with loss of voice, their action and emotion intentions are very important and must be expressed properly in their daily lives. Therefore, we selected five frequently used words, i.e., Front, Back, Left, Right, and Stop, as the basic action instructions to express their daily action intentions. Meanwhile, some common words, i.e., Happy, Sad, Hello, Goodbye, Hug, and Love, were chosen as the emotion instructions that these patients could use to express their emotions or greetings. The anterior belly of digastric (ABD), buccinators (BUC), and zygmaticus (ZYG) were selected as the target muscle groups because of their close connections with the talking and swallowing actions . Once the silent speech recognition system was set up, the tester was asked to carry out a series of tasks:Figure The procedure of the proposed silent speech recognition method based on the wavelet decomposition and pattern recognization is illustrated in Fig. The implementation of the wavelet decomposition and pattern recognition for data processing can be further elaborated, as shown in Fig. The original sEMG signal {s} is decomposed by the db4 wavelet; after four levels of decomposition, five-set coefficients are produced: {d1, d2, d3, d4, a4}. a4 is the low-frequency coefficient segment. d1, d2, d3, and d4 are the high-frequency coefficient segments. The waveforms of the wavelet coefficients a4 and d4 are similar to those of the original signal {s}, which means the wavelet coefficients {d4, a4} contain the most valid information of the original signal.The obtained wavelet coefficients are processed by three different threshold quantization functions, i.e., fixed threshold denoising, default threshold denoising, and soft threshold denoising, and then the signal is reconstructed. As shown in Fig. In this study, 150 feature vector sets were recorded from the five action instructions, and 180 feature vector sets were recorded from the six emotion instructions . Tenfold cross-validation was applied. Ninety percent of the feature vector sets were used for the training of the LDA, with the others used for testing. Figure The accuracies of the five action and six emotion instructions from the three individual channels and the combined channel are depicted in Fig. These sEMG signals are binned into discrete commands using the LDA classification algorithm. The accuracy of this classifier can then be visualized utilizing a confusion matrix Fig. , in whicSimilarly, the accuracy of the emotion instructions can be visualized by a confusion matrix Fig. . As showIn addition, it may be slightly insufficient to express emotions simply by relying on simple voice synthesis for people who have lost their voice. Therefore, we created a virtual character to represent the patient that could pronounce the patient’s words and make some body movements to better express their motions. As shown in Fig. In summary, an imperceptible epidermal sEMG tattoo-like patch is developed to monitor sEMG signals generated by the muscles of the face and the jaw. The epidermal sEMG electrodes manufactured by the MEMS process combined with a sterile wound dressing provide excellent flexibility and viscosity to adapt to the strain of skin. This tattoo-like patch shows excellent performance in recording the sEMG of three muscle channels when a tester speaks silently. The collected signals are processed by wavelet decomposition and a machine-learning algorithm to identify the action and emotion instructions of the tester. The results indicate that the average accuracy of the action instructions  from the combined channel can reach up to 89.6% and that the best accuracy of a single channel is 80.9%. For the emotion instructions , the average accuracy of the combined channel can reach up to 92.7%, and the best accuracy of a single channel is 81.9%. In the future, such flexible and functional tattoo-like patches will have great potential in intelligent speech recognition and voice synthesis, which is of great importance to help patients who have lost their voice to express their intentions by an HMI, such as wheelchair control, a human–robot interface, virtual reality interaction, etc. The device also offers expansion of the potential application to artificial throat and healthcare monitoring. In the future, thinner and more integrated electronics patches will show great potential in medical treatment, biomonitoring, sensing, etc.3COOH:H2O2:H2O = 1:2:10). Then, a second PI layer (2.4 μm in thickness) and silicon oxide layer  were used to cover the entire structure. Next, photolithography, reactive ion etching (RIE), and oxygen plasma etching were conducted to pattern the layers of PI in a geometry matched to the metal traces and exposed the sEMG electrodes and connection pads . The residue SiO2 mask was removed by using buffered oxide etchant . Finally, the wafer was soaked in dilute hydrochloric acid  for 30 s and cleaned by flowing water to remove the copper oxide layer.The fabrication process began with the preparation of a glass substrate to facilitate the delamination of electrode patterns. It was followed by spin-coating polydimethylsiloxane  onto the temporary substrate  and exposed to oxygen plasma to enhance the vitality of the surface. A thick layer of PI (2.4 μm in thickness) was made for the protective layer . Then, a thick layer of Cu (400 nm in thickness) was deposited by electron beam evaporation onto the PI. The electrode and interconnect structure were defined by photolithography and etching (CHf(t) can yield the corresponding discrete signal f(n) . The wavelet transform is defined asWf is the wavelet coefficient. The wavelet transform is implemented by the Mallat algorithm as follows:h denotes the low-pass and high-pass filters corresponding to the scaling function, g denotes the low-pass and high-pass filters corresponding to the wavelet function Ψ (x), and “*” implies conjugation.Continuous sampling of the continuous signal All experiments were approved by the human protection program at Soochow University.Supplementary informationAugmented reality interactionBluetooth speaker controlling (Online)Intelligent car controlling (Online)


We performed subgroup analyses of the AFTER I-O study to clarify the association of time-to-treatment failure (TTF) and discontinuation reason of prior immune-oncology (I-O) therapy, and molecular targeted therapy (TT) regimen with the outcomes of TT after I-O.The data of Japanese metastatic renal cell carcinoma patients treated with TT after nivolumab (NIVO) (CheckMate 025) or NIVO + ipilimumab (IPI) (CheckMate 214) were retrospectively analyzed. The objective response rates (ORRs), progression-free survival (PFS) and overall survival (OS) of TT after I-O were analyzed by subgroups: TTF (<6 or ≥6 months) and discontinuation reason of prior I-O (progression or adverse events), and TT regimen (sunitinib or axitinib). We also analyzed PFS2 of prior I-O and OS from first-line therapy.The ORR and median PFS of TT after NIVO and NIVO+IPI among the subgroups was 17–36% and 20–44%, and 7.1–11.6 months and 16.3-not reached (NR), respectively. The median OS of TT after NIVO was longer in patients with longer TTF of NIVO and treated with axitinib. Conversely, median OS of TT after NIVO+IPI was similar among subgroups. The median PFS2 of NIVO and NIVO+IPI was 36.7 and 32.0 months, respectively. The median OS from first-line therapy was 70.5 months for patients treated with NIVO and NR with NIVO+IPI. The safety profile of each TT after each I-O was similar to previous reports.The efficacy of TT after NIVO or NIVO+IPI was favorable regardless of the TTF and discontinuation reason of prior I-O, and TT regimen. Efficacy of molecular targeted therapy after immune-oncology therapy was favorable without new safety signals, regardless of time to treatment failure and reason for discontinuation of prior I-O, and TT regimen. The prognosis of patients with metastatic renal cell carcinoma (mRCC) has dramatically improved in the immuno-oncology (I-O) era than in the cytokine  and moleMost of the outcomes of subsequent therapy observed in pivotal clinical trials are insufficient, and long-term follow-ups and observational studies of subsequent therapy in real-world settings are needed for decision-making regarding treatment strategies. Consistent with previous reports on the outcomes of subsequent therapy after NIVO or immuno-oncology (I-O) combination therapy , we haveet al. , reason for discontinuation of NIVO or NIVO+IPI, and first TT regimen after NIVO or NIVO+IPI (sunitinib or axitinib). Moreover, we made additional analyses on progression-free survival 2 (PFS2) after NIVO and NIVO+IPI and overall survival (OS) from first-line therapy to clarify the long-term benefit of NIVO and NIVO+IPI.The ‘AFTER I-O study’ was a multicenter, retrospective, observational study conducted in Japan. This study analyzed patients that participated in the CheckMate 025 or CheckMate 214 trials and were treated with TT as a subsequent therapy before 31 March 2019, and after the discontinuation of NIVO or NIVO+IPI. The primary endpoints were the objective response rates (ORRs) to the first TT after discontinuation of NIVO or NIVO+IPI. The secondary endpoints included the efficacy of TT after NIVO or NIVO+IPI, such as PFS, OS and safety. Additionally, we analyzed PFS2 after NIVO and NIVO+IPI and OS from first-line therapy. PFS was defined as the time from the first TT dose after NIVO or NIVO+IPI to disease progression (PD) or death. PFS2 was defined as the time from the first dose of NIVO or NIVO+IPI to PD or death during subsequent therapy with the first TT after NIVO or NIVO+IPI. The OS of TT was defined as the time from the first TT dose after NIVO or NIVO+IPI to death and the OS of first-line therapy as the time from first-line therapy to death.The AFTER I-O study was approved by the Ethics Committee of Niigata University  and other independent institutional review boards and was conducted according to the Declaration of Helsinki and Ethical Guidelines for Medical and Health Research Involving Human Subjects. This study is registered in the University hospital Medical Information Network under number UMIN000036063. This retrospective study used medical records for analysis, and thus, informed consent from patients was not required. This paper does not disclose any personally identifiable information of any of the participants in any form. Hence, consent for publication is not applicable.OS, PFS and PFS2 were estimated by the Kaplan–Meier method, and the 95% confidence intervals for each subgroup were determined using hierarchical Bayesian survival analysis and Cox’s proportional hazards model. SAS  was used for all analyses. The efficacy of the first TT after discontinuation of NIVO or NIVO+IPI was analyzed in the next subgroups: TTF of NIVO or NIVO+IPI, cutoff at 6 months; reason for discontinuation of NIVO or NIVO+IPI, PD or adverse event; regimen of TT after discontinuation of NIVO or NIVO+IPI, sunitinib or axitinib, and safety were analyzed in subgroups of TT regimens, sunitinib or axitinib. Statistical differences were not tested between any subgroups due to the small size of the study.The patient characteristics are summarized in The ORR and BOR of all the patients and their subgroups are summarized in The ORR of TT after NIVO varied from 17 to 36% , while tFigs 3c and The safety data are summarized in This subgroup analysis of the AFTER I-O study revealed that the efficacy of TT after NIVO or NIVO+IPI was promising, regardless of the TTF of NIVO or NIVO+IPI, reason for discontinuation of I-O therapy, or TT regimen, sunitinib or axitinib.et al. (median OS: 27.0 months)  .As for TT-TT sequential therapy, many studies have reported patients who discontinued TT due to PD had poorer PFS and OS than those that discontinued due to adverse events . Such a et al. (et al. (Ishihara et al.  reported (et al.  also repAlthough the median OS of sunitinib was shorter than that of axitinib after NIVO (22.1 vs. 37.9 months, The PFS2 and OS from the first-line therapies of the RECORD-3, SWICH, SWICH II and CROSS-J-RCC trials were previously reported for TT sequential therapy . The JAVThe safety profile of sunitinib or axitinib after NIVO and NIVO+IPI was consistent with previous reports and without new safety signals.The AFTER I-O study had some limitations: first the nature of the retrospective study, and second, the small sample size; as each subgroup was too small, comparisons between subgroups should be performed with caution.In conclusion, the efficacy of TT after NIVO or NIVO+IPI was favorable independent of the TTF and the reason for discontinuation of NIVO or NIVO+IPI, and TT regimen.The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.Tomita, Kaneko, and Tajima have full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.Study concept and design: Tomita, Kaneko, and Tajima.Provision of study materials or patients: Tomita, Kimura, Fukasawa, Numakura, Sugiyama, Yamana, Naito, and Oya.Collection and assembly of data: Tomita, Kaneko, and Tajima.Data analysis and interpretation: All authors.Drafting of the manuscript: Tomita, Kaneko, and Tajima.Critical revision of the manuscript for important intellectual content: All authors.Final approval of manuscript: All authors.Supplemetary_Tables_and_Figures_hyab114Click here for additional data file.


Generalised pseudo-values have been suggested to evaluate the impact of allogeneic stem cell transplantation on childhood leukaemia. The approach compares long-term survival of two cohorts defined by the availability or non-availability of suitable donors for stem cell transplantation. A patient's cohort membership becomes known only after completed donor search with or without an identified donor. If a patient suffers an event during donor search, stem cell transplantation will no longer be indicated. In such a case, donor search will be ceased and cohort membership will remain unknown. The generalised pseudo-values approach considers donor identification as binary time-dependent covariate and uses inverse-probability-of-censoring weighting to adjust for non-identified donors. The approach leads to time-consuming computations due to multiple redefinitions of the risk set for pseudo-value calculation and an explicit adjustment for waiting-time bias. Here, the problem is looked at from a different angle. By considering the probability that a donor would have been identified after ceasing of donor search, weights for common pseudo-values are defined. This leads to a faster alternative approach as only a single risk set is necessary. Extensive computer simulations show that both, the generalised and the new weighted pseudo-values approach, provide approximately unbiased estimates. Confidence interval coverage is satisfactory for typical clinical scenarios. In situations, where donor identification takes considerably longer than usual, the weighted pseudo-values approach is preferable. Both approaches complement each other as they have different potential in addressing further aspects of the underlying medical question. Childhood leukaemia studies that compare allogeneic stem cell transplantation (SCT) with conventional chemotherapy usually exhibit specific features that result in statistically challenging data analyses. After being considered eligible for SCT, a patient is included in the study, conventional chemotherapy is administered, and donor search is started in international donor registries if no suitable related donor has been identified. These registries contain pre-typed blood sample data of volunteers willing to become stem cell donors. If a potential donor is pre-selected and his/her willingness could be re-confirmed, then a new blood sample will be exactly typed. If a match is achieved, chemotherapy can be stopped and SCT can be performed. Chemotherapy is the sole treatment for those patients, for whom no matched donor can be identified during the search period. According to their donor availability status, patients belong to either of two cohorts, that is, with and without available donor. After successful donor identification, SCT will be performed unless contraindications prevent it. Therefore, in order to avoid selection bias, it is crucial that statistical approaches consider donor identification rather than SCT applied.It may happen that a patient suffers death, relapse, or other primary disease-specific problems during the donor search period. Consequently, the indication for SCT will be lost, donor search will be ceased, and donor availability status will remain unknown for this patient. Note that donor availability status can, nonetheless, be considered as an external covariate as it exists beyond patient survival or disease progression.24 This approach mimics the intention-to-treat principle of randomised trials by comparing the long-term survival of patients with available donor (SCT possible) and without available donor (SCT impossible). Unfortunately, missing donor availability status makes it often impossible to apply genetic randomisation and alternative approaches have to be considered.Ideally, the so-called genetic randomisation approach would be used to evaluate SCT trials.6 Landmark analysis and dynamic prediction by landmarking are other popular approaches;710 however, their results can be affected by the arbitrarily chosen landmark time. Pötschger et al. discuss all these and other approaches in more detail and suggest a new approach based on so-called generalised pseudo-values (GPVs) which considers long-term survival, mimics the intention-to-treat principle, yet overcomes the missing donor availability and the non-proportional hazards problem.The prevailing Cox model with a binary time-dependent covariate is hampered by non-proportional hazards. The benefits of an SCT are expected to fully unfold on the long run; on the short run, an increase in treatment-related events is commonly observed. As the Cox model considers relative instantaneous risks, it cannot be used to assess cumulative survival effects in a non-proportional hazard situation. Meanwhile, a programming error in the original implementation of the procedure was discovered. The error has, by coincidence, resulted in reasonable confidence intervals for the cases considered; however, after error recovery, it became apparent that the intervals are in fact too wide leading to unacceptably high coverage rates. As no workable alternative solution is available, the ad-hoc parametric bootstrap procedure will not be pursued any further for the GPV approach.Unfortunately, the practical application of GPVs is computationally intensive and time-consuming. This is, among others, especially problematic during study design, when the required sample size or statistical power has to be assessed by means of computer simulation. Furthermore, suboptimal confidence interval coverage rates were observed in certain cases, and an ad-hoc parametric bootstrap procedure was developed to overcome this issue.Here, the new approach of weighted pseudo-values (WPVs) is proposed as alternative to GPVs; both estimating cohort survival probabilities at a pre-specified time point and the associated cumulative hazard ratio . WPVs are based on an individually adapted probability weighting of common pseudo-values and can be efficiently computed in a single step. In the following, GPVs and WPVs will be introduced in the section ‘Methods’. They will be compared by means of a simulation study in the section ‘Results’. Further issues and additional aspects will be summarised and discussed in the section ‘Discussion’.In the following, the term survival is linked to the outcome-related events of interest, like death, or a composite endpoint that additionally includes relapse or other disease-related events. Furthermore, the term donor search-ceasing events comprise all events that permanently contraindicate SCT and thus lead to stop of donor search. Note that donor search-ceasing events do not have to be identical with outcome-related events. For example, if overall survival is studied, then death of patient will cease donor search as well as define the outcome of interest, whereas a relapse will only cease donor search. Since donor availability is an external covariate, it is independent of these donor search-ceasing events.The survival probability at time of patients with a donor available, , is to be compared with the survival probability of those without an available donor, . Here, is a pre-specified time point used to indicate long-term survival or cure of the patients.The maximum donor search time is used to determine the donor availability status see . That isW, , as waiting time in the initial state 0 until a donor is identified and the patient moves to state 1. Let and denote the hazard function and the density of the distribution of W, respectively. Then the survival probability at for patients with an available donor ist since the patient entered the study  as well as the time since a donor was identified and the patient moved to state 1.Define the random variable The survival probability at for patients without donor available is state 2 .Note that the hazard for the direct transition from the initial state 0 to the event state 2 is equal for both populations up to ; thereafter there will be, by definition, no patients anymore in state 0 of the donor available population.t* for the comparison of patients with and without an available donor is .The cHR at time n patients, the common pseudo-value at time for the ith patient isith patient.Given 14 However, i.i.d. observations and independent right censoring have to be assumed; and the risk set at time has to be sufficiently large.As common pseudo-values are asymptotically conditionally unbiased given covariates, they can be used as a response variable in a regression model.m out of n patients a transition to state 1 has been observed, and denote the observed transition times . The GPV approach of Pötschger et al. now defines GPVs, .Assume that for the first Here , , are common pseudo-values with denoting the Kaplan-Meier estimate at for the risk of a direct transition from state 0 to state 2; where patients with an available donor are censored at their observed transition times .m GPVs are , with , . has just been introduced above; and is the Kaplan-Meier estimate at based on all patients still at risk at .The remaining n patients where both, donor search-ceasing events and censoring, are considered as events; whereas observed 0 → 1 transitions are considered as censored at . That is, , ; note that .Finally, weights have to be defined for . Trivially, for . In contrast, are needed to adjust for unobserved 0 → 1 transitions due to donor search-ceasing events and censoring. This is achieved by inverse probability weighting with , the Kaplan-Meier estimate of all Now, and are consistent estimators of and , respectively.t* for the comparison of patients with and without an available donor.GPVs can be used as response variable in a weighted generalised linear model with log-minus-log link function , a normal response probability distribution, and a robust sandwich variance estimator. Let with for and otherwise. With the linear predictor , the parameter estimates correspond to and , so that and are the estimates for and , respectively. Finally, provides a consistent estimate of the cHR at time m patients are those with an identified donor; and the remaining patients are those where donor search was ceased and group membership is unknown.The novel WPV approach proportionally allocates a patient with uncertain group membership into the two groups with and without donor according to its probability that a donor might still be found until . There are patients ; for notith patient by , so that, consequently, is the probability of belonging to the group without donor . A natural estimator of is provided by ; where is the Kaplan-Meier estimate for time to donor identification. Note that here all donor search-ceasing events as well as censoring are considered as censoring events, which are non-informative with regard to time to donor identification.For the latter patients, let denote the probability that a donor will be identified until , given that no donor has been found until , the time when donor search was ceased. Now, , where is the probability that no donor has been found for the Consequently, the probability of no donor available is estimated by , . Note that if – for some reason – a donor is found after donor search has already been ceased, then it would be sensible to include this knowledge by setting for the patient concerned.Now, for all patients common pseudo-values , , (see equation ) are cal.The WPV approach defines a vector with of these common pseudo-values , where the pseudo-values of the patients of the group, , occur twice. The corresponding weight vector is with for , for , and for 16Let indicate group membership with for and and otherwise. Then and are consistent estimators of and , respectively.The vector can be used as response variable in a weighted generalised linear model with log-minus-log link , a normal response probability distribution, and a robust sandwich variance estimator. Using the linear predictor , then, in analogy to the GPV approach, the parameter estimates correspond to and , respectively, and is a consistent estimator of the cHR at time for the comparison of patients with and without an available donor.18An overview of the weights of both approaches and their contribution to the estimation of and can be found in  are used to enable a straightforward comparison of the GPV with the WPV approach. In short, survival times were generated using the inversion method, which was extended by using a parametric mixture cure model to allow for a plateau of the survival curve that represents cured patients. Uniform censoring times between 0 to 6 years and 0 to 11 years were superimposed in the simulation scenarios of simulation studies 1 and 2, respectively. For each scenario, sample sizes of 400 and 1000 were generated for 1000 simulation runs.The two simulation studies of Pötschger et al. then the WPV results are compared to the original GPV results .At first, the WPV approach is applied to the original simulated data sets of Pötschger et al., results  to 5. ReSupplemental Figures S2 to S7) are labelled , and , although they actually show the bias of the corresponding parameter estimates of the particular generalised linear models; that is, , and for the GPV, and , and for the WPV approach, respectively.For the sake of convenience, the bias distributions  marks the area between the 0.025 and the 0.975 quantile of a binomial distribution with parameters 1000  and 0.95 . That is, after 1000 simulation runs, the observed coverage rate of a CI with a true confidence level is contained in this band with a probability of 0.95 . Hence, an observed coverage rate below or above this band may be interpreted as indication that the considered CI actually is too liberal or too conservative, respectively.The grey horizontal band in the confidence interval (CI) coverage plots .  The realistic situations represent the most common departures from proportional hazards: differences in long-term survival only (A), crossing survival curves , and a situation where only differences in short-term survival (D) are observed. The theoretical settings consider a proportional hazards model (E), a no-effect model (F), and a scenario with unrealistically long waiting times (G); see Figure S1 in Supplemental Materials, Section C. The proportions of available donors are 0.25 for scenario A, 0.4 for scenarios B–F and 0.45 for scenario G, respectively. The outcome is evaluated at 5 years , and the donor search period is set to 5 years , too.This simulation study is performed to assess unbiasedness of the parameter estimates and CI coverage of both approaches in four realistic settings from paediatric oncology and three theoretical settings.n = 1000. This, however, seems to be a simulation artefact as the performance for n = 400 is adequate. WPV shows acceptable coverage in all situations for both, and the cumulative hazard ratio ; however, the coverage rates of GPV are only acceptable for scenarios A–F. Analogous to simulation study 1, GPV shows a too low coverage for when donor identification takes considerably longer (scenario G); this is accompanied by a slightly conservative coverage for when n = 1000.Coverage rates of 95% CIs are provided in Section D of Supplemental Materials, where the proportion of available donors and have been varied. Again, the general unbiasedness of both approaches turns out .Additional extensive simulation results can be found in Supplemental Figures S8 to S13 confirm the results of Supplemental Figures S8 to S13).The CI coverage rates for and in Supplemental Figures S8 to S13).Both approaches show adequate CI coverage rates for in scenarios A–F. For the extreme scenario G, in particular, when , too high coverage rates may occur in both approaches . For 325 of 542 patients, a donor could be identified, so that they could switch from chemotherapy to SCT after a median waiting time of 5.1 months. The remaining 217 patients were treated with chemotherapy only. Here we assume that donor identification leads to SCT in a timely manner. The Cox model with a binary time-dependent covariate (indicating SCT after donor identification) gives a hazard ratio (HR) of 0.91 in favour of SCT .Below, the WPV result is compared to the results of a Cox model and the GPV approach using real data from an international study in 542 children with newly diagnosed Philadelphia chromosome-positive (PH+) acute lymphoblastic leukaemia.2224 As expected, SCT initially results in an increased hazard  with a maximum at about 0.5 years and decreasing risk thereafter. At about 1 year instantaneous hazards in both groups are equal (HR = 1), nevertheless, cumulated risks until 1 year are still to the disadvantage of SCT. However, it can neither be seen from the (non-significant) constant nor from the (significant) time-flexible HRs (This result is questionable as it assumes a constant SCT effect on DFS. The problem is exemplified in ible HRs  whether p = 0.027), the easier to calculate WPV approach gives a similar cHR of 0.76 . Hence, it can be concluded that the long-term benefit of SCT outweighs its short-term risk (The 5-year DFS estimates with and without donor are 41.7% (95% CI: 36.7%–46.5%) and 32.1% (25.4%–38.9%) for the GPV approach, and 41.7% (36.6%–46.7%) and 31.6% (24.6%–38.7%) for the WPV approach, respectively. The GPV approach yields a 5-year cHR of 0.77 favouring SCT . The WPV runtime advantage over GPV increases with the proportion of identified donors as more computationally time-consuming -values have to be calculated. The smaller runtime advantage in scenario G compared to scenarios A–F confirms that the proportion of identified rather than available donors is crucial , as the considerably longer waiting times of scenario G lead to less identified donors and, consequently, less -calculations in the GPV approach.With regard to ease of software implementation and computational speed, WPV clearly outperforms GPV. The former approach requires the computation of common pseudo-values only, whereas the latter approach requires different rounds of computations with different starting times and patient risk sets. In the considered simulation scenarios of When it comes to interpretation, both approaches provide the same primary message in terms of long-term survival estimation and group difference testing; however, both approaches may give different additional insights. Consider the real data example above (PH+ acute lymphoblastic leukaemia patients); here the WPV approach enables to directly conclude that an extremely fast donor search might have identified up to about 38 additional donors. Nonetheless, there are no donors available for around 33% of all patients; a number that can only be reduced by increasing the number of potential stem cell donors. In contrast, the GPV approach might be used to investigate other  distributions of the time to donor identification by adapting the inverse probability weights. By doing so, effects of accelerated or deferred donor identification on patients' survival could be directly studied. suggested to impute the disease status (case or control) of censored subjects according to the probability that the subject is a case or a control. The weights of this “direct estimation by imputation”—approach share the same underlying idea as the WPV-weights.Finally, consider the completely different setting of a diagnostic study with survival time outcome. To enable the computation of common diagnostic measures  at a pre-specified time point, Antolini and Valsecchi From a practical point of view, the WPV approach is computationally faster and easier to implement than the GPV approach. Previous SCT studies that have been analysed within the Cox model framework may be reanalysed with the new approach to reassess treatment effects and resulting treatment recommendations.When donor availability status is unknown due to donor search-ceasing events or censoring, then both, the WPV and the GPV approach, are able to successfully deal with the time-dependent nature of donor identification and partially unobserved donor availability, thereby mimicking the genetic randomization approach for SCT trials in paediatric oncology.