Characteristics, aetiology and implications for management of multiple primary renal tumours: a systematic review

In a subset of patients with renal tumours, multiple primary lesions may occur. Predisposition to multiple primary renal tumours (MPRT) is a well-recognised feature of some inherited renal cancer syndromes. The diagnosis of MPRT should therefore provoke a thorough assessment for clinical and genetic evidence of disorders associated with predisposition to renal tumourigenesis. To better define the clinical and genetic characteristics of MPRT, a systematic literature review was performed for publications up to 3 April 2024. A total of 7689 patients from 467 articles were identified with MPRT. Compared to all patients with renal cell carcinoma (RCC), patients with MPRT were more likely to be male (71.8% versus 63%) and have an earlier age at diagnosis (<46 years, 32.4% versus 19%). In 61.1% of cases MPRT were synchronous. The proportion of cases with similar histology and the proportion of cases with multiple papillary renal cell carcinoma (RCC) (16.1%) were higher than expected. In total, 14.9% of patients with MPRT had a family history of cancer or were diagnosed with a hereditary RCC associated syndrome with von Hippel-Lindau (VHL) disease being the most common one (69.7%), followed by Birt-Hogg-Dubé (BHD) syndrome (14.2%). Individuals with a known or likely genetic cause were, on average, younger (43.9 years versus 57.1 years). In rare cases intrarenal metastatic RCC can phenocopy MPRT. We review potential genetic causes of MPRT and their implications for management, suggest an approach to genetic testing for individuals presenting with MPRT and considerations in cases in which routine germline genetic testing does not provide a diagnosis

Detection and characterization of male sex chromosome abnormalities in the UK Biobank study

Purpose: The study aimed to systematically ascertain male sex chromosome abnormalities, 47,XXY (Klinefelter syndrome [KS]) and 47,XYY, and characterize their risks of adverse health outcomes. Methods: We analyzed genotyping array or exome sequence data in 207,067 men of European ancestry aged 40 to 70 years from the UK Biobank and related these to extensive routine health record data. Results: Only 49 of 213 (23%) of men whom we identified with KS and only 1 of 143 (0.7%) with 47,XYY had a diagnosis of abnormal karyotype on their medical records or self-report. We observed expected associations for KS with reproductive dysfunction (late puberty: risk ratio [RR] = 2.7; childlessness: RR = 4.2; testosterone concentration: RR = -3.8 nmol/L, all P < 2 x 10(-8)), whereas XYY men appeared to have normal reproductive function. Despite this difference, we identified several higher disease risks shared across both KS and 47,XYY, including type 2 diabetes (RR = 3.0 and 2.6, respectively), venous thrombosis (RR = 6.4 and 7.4, respectively), pulmonary embolism (RR = 3.3 and 3.7, respectively), and chronic obstructive pulmonary disease (RR = 4.4 and 4.6, respectively) (all P Conclusion: KS and 47,XYY were mostly unrecognized but conferred substantially higher risks for metabolic, vascular, and respiratory diseases, which were only partially explained by higher levels of body mass index, deprivation, and smoking. (C) 2022 The Authors. Published by Elsevier Inc. on behalf of American College of Medical Genetics and Genomics.Peer reviewe

Frequency of pathogenic germline variants in cancer susceptibility genes in 1336 renal cell carcinoma cases

Background Renal cell carcinoma (RCC) occurs in a number of cancer predisposition syndromes but the genetic architecture of susceptibility to RCC is not well defined. We investigated the frequency of pathogenic germline variants in cancer susceptibility genes (CSGs) within a large series of unselected RCC participants. Methods Whole genome sequencing data on 1336 RCC participants and 5834 controls recruited to the UK 100000 Genomes Project, a nationwide multicentre study, was analysed to identify rare pathogenic or likely pathogenic (P/LP) short variants (SNVs and INDELs) and structural variants in 121 CSGs. Results Among 1336 RCC participants (mean 61.3 years [±12SD], range 13–88 years; 64% male), 85 participants (6.4%; 95% CI [5.1, 7.8]) had one or more P/LP germline variant in a wider range of CSGs than previously recognised. A further 64 intragenic variants in CSGs previously associated with RCC were classified as a variant of uncertain significance (VUS) (24 ‘hot VUSs’) and were considered to be of potential clinical relevance as further evaluation might result in their reclassification. Most patients with pathogenic variants in well-established RCC-CSGs were aged < 50 years. Burden test analysis for filtered variants in CSGs demonstrated a significant excess of CHEK2 variants RCC European participants compared to the healthy European controls (P = 0.0019). Conclusions Approximately 6% of patients with RCC unselected for family history have a germline variant requiring additional follow-up analysis. To improve diagnostic yield we suggest expanding the panel of RCC-CSGs tested to include CHEK2 and all SDHx subunits and raising the eligibility criteria for age-based testing

Identification of the Potential Genes Regulating Seed Germination Speed in Maize

Seed germination is the crucial stage in plant life cycle. Rapid and uniform germination plays an essential role in plant development and grain yield improvement. However, the molecular mechanism underlying seed germination speed is largely unknown due to the complexity of the dynamic process and the difficulty in phenotyping. Here, we conducted a time-series comparative transcriptome study of two elite maize inbred lines, 72-3 and F9721, with striking difference in seed germination speed, and identified a major locus underlying maize germination speed through genome-wide association analysis (GWAS) of an F2 segregation population. Comparative transcriptome study identified 12 h after imbibition (HAI) as the critical stage responsible for the variation in germination speed. The differentially expressed genes (DEGs) between 72-3 and F9721 were mainly enriched in metabolic pathways, biosynthesis of secondary metabolites, oxidoreductase activity pathways, hormone signal transduction, and amino acid transporter activity pathways. GWAS revealed that germination speed was controlled by a major locus on chromosome 1 with the leading SNP as AX-91332814, explaining 10.63% of phenotypic variation. A total of 87 proposed protein-coding genes surrounding the locus were integrated with DEGs. Combined with evidence from the gene expression database and gene synteny with other model species, we finally anchored three genes as the likely candidates regulating germination speed in maize. This study provides clues for the further exploration of genes controlling the maize seed germination speed, thus facilitating breeding of rapid germinated elite lines through marker assistant selection

Transcriptome Analysis Provides Insight into the Molecular Mechanisms Underlying gametophyte factor 2-Mediated Cross-Incompatibility in Maize

In maize (Zea mays L.), unilateral cross-incompatibility (UCI) is controlled by Gametophyte factors (Ga), including Ga1, Ga2, and Tcb1; however, the molecular mechanisms underpinning this process remain unexplored. Here, we report the pollination phenotype of an inbred line, 511L, which carries a near-dominant Ga2-S allele. We performed a high-throughput RNA sequencing (RNA-Seq) analysis of the compatible and incompatible crosses between 511L and B73, to identify the transcriptomic differences associated with Ga2-mediated UCI. An in vivo kinetics analysis revealed that the growth of non-self pollen tubes was blocked at the early stages after pollination in 511L, maintaining the UCI barrier in Ga2. In total, 25,759 genes were expressed, of which, 2063 differentially expressed genes (DEGs) were induced by pollination (G_GG, G_GB, B_BB, B_BG). A gene ontology (GO) enrichment analysis revealed that these genes were specifically enriched in functions involved in cell wall strength and pectic product modification. Moreover, 1839, 4382, and 5041 genes were detected to differentially express under same pollination treatments, including B_G, BG_GG, and BB_GB, respectively. A total of 1467 DEGs were constitutively expressed between the two inbred lines following pollination treatments, which were enriched in metabolic processes, flavonoid biosynthesis, cysteine biosynthesis, and vacuole functions. Furthermore, we confirmed 14 DEGs related to cell wall modification and stress by qRT-PCR, which might be involved in Ga2-S-mediated UCI. Our results provide a comprehensive foundation for the molecular mechanisms involved in silks of UCI mediated by Ga2-S

Methods for analysing lineage tracing datasets.

A single population of progenitor cells maintains many epithelial tissues. Transgenic mouse cell tracking has frequently been used to study the growth dynamics of competing clones in these tissues. A mathematical model (the 'single-progenitor model') has been argued to reproduce the observed progenitor dynamics accurately. This requires three parameters to describe the growth dynamics observed in transgenic mouse cell tracking-a division rate, a stratification rate and the probability of dividing symmetrically. Deriving these parameters is a time intensive and complex process. We compare the alternative strategies for analysing this source of experimental data, identifying an approximate Bayesian computation-based approach as the best in terms of efficiency and appropriate error estimation. We support our findings by explicitly modelling biological variation and consider the impact of different sampling regimes. All tested solutions are made available to allow new datasets to be analysed following our workflows. Based on our findings, we make recommendations for future experimental design

Characteristics, aetiology and implications for management of multiple primary renal tumours: a systematic review.

Funder: Cancer Research UK (CRUK); doi: https://doi.org/10.13039/501100000289Funder: NIHR Cambridge Biomedical Research CentreIn a subset of patients with renal tumours, multiple primary lesions may occur. Predisposition to multiple primary renal tumours (MPRT) is a well-recognised feature of some inherited renal cancer syndromes. The diagnosis of MPRT should therefore provoke a thorough assessment for clinical and genetic evidence of disorders associated with predisposition to renal tumourigenesis. To better define the clinical and genetic characteristics of MPRT, a systematic literature review was performed for publications up to 3 April 2024. A total of 7689 patients from 467 articles were identified with MPRT. Compared to all patients with renal cell carcinoma (RCC), patients with MPRT were more likely to be male (71.8% versus 63%) and have an earlier age at diagnosis (<46 years, 32.4% versus 19%). In 61.1% of cases MPRT were synchronous. The proportion of cases with similar histology and the proportion of cases with multiple papillary renal cell carcinoma (RCC) (16.1%) were higher than expected. In total, 14.9% of patients with MPRT had a family history of cancer or were diagnosed with a hereditary RCC associated syndrome with von Hippel-Lindau (VHL) disease being the most common one (69.7%), followed by Birt-Hogg-Dubé (BHD) syndrome (14.2%). Individuals with a known or likely genetic cause were, on average, younger (43.9 years versus 57.1 years). In rare cases intrarenal metastatic RCC can phenocopy MPRT. We review potential genetic causes of MPRT and their implications for management, suggest an approach to genetic testing for individuals presenting with MPRT and considerations in cases in which routine germline genetic testing does not provide a diagnosis

Methods for analysing lineage tracing datasets

A single population of progenitor cells maintains many epithelial tissues. Transgenic mouse cell tracking has frequently been used to study the growth dynamics of competing clones in these tissues. A mathematical model (the ‘single-progenitor model’) has been argued to reproduce the observed progenitor dynamics accurately. This requires three parameters to describe the growth dynamics observed in transgenic mouse cell tracking—a division rate, a stratification rate and the probability of dividing symmetrically. Deriving these parameters is a time intensive and complex process. We compare the alternative strategies for analysing this source of experimental data, identifying an approximate Bayesian computation-based approach as the best in terms of efficiency and appropriate error estimation. We support our findings by explicitly modelling biological variation and consider the impact of different sampling regimes. All tested solutions are made available to allow new datasets to be analysed following our workflows. Based on our findings, we make recommendations for future experimental design

Methods for analysing lineage tracing datasets.

A single population of progenitor cells maintains many epithelial tissues. Transgenic mouse cell tracking has frequently been used to study the growth dynamics of competing clones in these tissues. A mathematical model (the 'single-progenitor model') has been argued to reproduce the observed progenitor dynamics accurately. This requires three parameters to describe the growth dynamics observed in transgenic mouse cell tracking-a division rate, a stratification rate and the probability of dividing symmetrically. Deriving these parameters is a time intensive and complex process. We compare the alternative strategies for analysing this source of experimental data, identifying an approximate Bayesian computation-based approach as the best in terms of efficiency and appropriate error estimation. We support our findings by explicitly modelling biological variation and consider the impact of different sampling regimes. All tested solutions are made available to allow new datasets to be analysed following our workflows. Based on our findings, we make recommendations for future experimental design