Altered splicing machinery in lung carcinoids unveils NOVA1, PRPF8 and SRSF10 as novel candidates to understand tumor biology and expand biomarker discovery.

BACKGROUND: Lung neuroendocrine neoplasms (LungNENs) comprise a heterogeneous group of tumors ranging from indolent lesions with good prognosis to highly aggressive cancers. Carcinoids are the rarest LungNENs, display low to intermediate malignancy and may be surgically managed, but show resistance to radiotherapy/chemotherapy in case of metastasis. Molecular profiling is providing new information to understand lung carcinoids, but its clinical value is still limited. Altered alternative splicing is emerging as a novel cancer hallmark unveiling a highly informative layer. METHODS: We primarily examined the status of the splicing machinery in lung carcinoids, by assessing the expression profile of the core spliceosome components and selected splicing factors in a cohort of 25 carcinoids using a microfluidic array. Results were validated in an external set of 51 samples. Dysregulation of splicing variants was further explored in silico in a separate set of 18 atypical carcinoids. Selected altered factors were tested by immunohistochemistry, their associations with clinical features were assessed and their putative functional roles were evaluated in vitro in two lung carcinoid-derived cell lines. RESULTS: The expression profile of the splicing machinery was profoundly dysregulated. Clustering and classification analyses highlighted five splicing factors: NOVA1, SRSF1, SRSF10, SRSF9 and PRPF8. Anatomopathological analysis showed protein differences in the presence of NOVA1, PRPF8 and SRSF10 in tumor versus non-tumor tissue. Expression levels of each of these factors were differentially related to distinct number and profiles of splicing events, and were associated to both common and disparate functional pathways. Accordingly, modulating the expression of NOVA1, PRPF8 and SRSF10 in vitro predictably influenced cell proliferation and colony formation, supporting their functional relevance and potential as actionable targets. CONCLUSIONS: These results provide primary evidence for dysregulation of the splicing machinery in lung carcinoids and suggest a plausible functional role and therapeutic targetability of NOVA1, PRPF8 and SRSF10.

Impact of diabetes and chronic kidney disease on active surveillance outcomes for small renal masses: A cohort study.

Introduction: The American Cancer Society estimates 79,000 individuals will be diagnosed with kidney cancer in 2022, most of which are initially found as small renal masses (SRMs). Proper management of SRM patients includes careful evaluation of risk factors such as medical comorbidities and renal function. To investigate the importance of these risk factors, we examined their effect on crossover to delayed intervention (DI) and overall survival (OS) in patients undergoing active surveillance (AS) for SRMs. Methods: This is an Institutional Review Board-approved retrospective analysis of AS patients presented at kidney tumor conferences with SRMs between 2007 and 2017. Univariable and multivariable logistic regression analyses were performed to determine how factors including estimated glomerular filtration rate (eGFR), diabetes, and chronic kidney disease are associated with DI and OS. Results: A total of 111 cases were reviewed. In general, AS patients were elderly and had significant comorbidities. On univariate analysis, intervention was more likely to occur in patients with a younger age (P = 0.01), better kidney function (P = 0.01), and higher tumor growth rates (GRs) (P = 0.02). Higher eGFR was associated with better survival (P = 0.03), while higher tumor GRs (P = 0.014), greater Charlson Comorbidity Index (P = 0.01), and larger tumors (P = 0.01) were associated with worse OS. Of the comorbidities, diabetes was found to be an independent predictor of worse OS (P = 0.01). Conclusions: Patient-level factors - such as diabetes and eGFR - are associated with the rate of DI and OS among SRM patients. Consideration of these factors may facilitate better AS protocols and improve patient outcomes for those with SRMs.

Differential Orthopedia Homeobox expression in pulmonary carcinoids is associated with changes in DNA methylation.

Limited number of tumor types have been examined for Orthopedia Homeobox (OTP) expression. In pulmonary carcinoids, loss of expression is a strong indicator of poor prognosis. Here, we investigated OTP expression in 37 different tumor types, and the association between OTP expression and DNA methylation levels in lung neuroendocrine neoplasms. We analyzed publicly available multi-omics data (whole-exome-, whole-genome-, RNA sequencing and Epic 850K-methylation array) of 58 typical carcinoids, 27 atypical carcinoids, 69 large cell neuroendocrine carcinoma and 51 small cell lung cancer patients and TCGA (The Cancer Genome Atlas) data of 33 tumor types. 850K-methylation analysis was cross-validated using targeted pyrosequencing on 35 carcinoids. We report bimodality of OTP expression in carcinoids (OTPhigh vs OTPlow group, likelihood-ratio test P = 1.5 × 10-2 ), with the OTPhigh group specific to pulmonary carcinoids while absent from all other cohorts analyzed. Significantly different DNA methylation levels were observed between OTPhigh and OTPlow carcinoids in 12/34 OTP infinium probes (FDR < 0.05 and ß-value effect size > .2). OTPlow carcinoids harbor high DNA methylation levels as compared to OTPhigh carcinoids. OTPlow carcinoids showed a significantly worse overall survival (log-rank test P = .0052). Gene set enrichment analysis for somatically mutated genes associated with hallmarks of cancer showed robust enrichment of three hallmarks in the OTPlow group, that is, sustaining proliferative signaling, evading growth suppressor and genome instability and mutation. Together our data suggest that high OTP expression is a unique feature of pulmonary carcinoids with a favorable prognosis and that in poor prognostic patients, OTP expression is lost, most likely due to changes in DNA methylation levels.

Coalescent Theory of Migration Network Motifs.

Natural populations display a variety of spatial arrangements, each potentially with a distinctive impact on genetic diversity and genetic differentiation among subpopulations. Although the spatial arrangement of populations can lead to intricate migration networks, theoretical developments have focused mainly on a small subset of such networks, emphasizing the island-migration and stepping-stone models. In this study, we investigate all small network motifs: the set of all possible migration networks among populations subdivided into at most four subpopulations. For each motif, we use coalescent theory to derive expectations for three quantities that describe genetic variation: nucleotide diversity, FST, and half-time to equilibrium diversity. We describe the impact of network properties on these quantities, finding that motifs with a high mean node degree have the largest nucleotide diversity and the longest time to equilibrium, whereas motifs with low density have the largest FST. In addition, we show that the motifs whose pattern of variation is most strongly influenced by loss of a connection or a subpopulation are those that can be split easily into disconnected components. We illustrate our results using two example data sets-sky island birds of genus Sholicola and Indian tigers-identifying disturbance scenarios that produce the greatest reduction in genetic diversity; for tigers, we also compare the benefits of two assisted gene flow scenarios. Our results have consequences for understanding the effect of geography on genetic diversity, and they can assist in designing strategies to alter population migration networks toward maximizing genetic variation in the context of conservation of endangered species.

GST' , Jost's D, and FST are similarly constrained by allele frequencies: A mathematical, simulation, and empirical study.

Statistics GST' and Jost's D have been proposed for replacing FST as measures of genetic differentiation. A principal argument in favour of these statistics is the independence of their maximal values with respect to the subpopulation heterozygosity HS , a property not shared by FST . Nevertheless, it has been unclear if these alternative differentiation measures are constrained by other aspects of the allele frequencies. Here, for biallelic markers, we study the mathematical properties of the maximal values of GST' and D, comparing them to those of FST . We show that GST' and D exhibit the same peculiar frequency-dependence phenomena as FST , including a maximal value as a function of the frequency of the most frequent allele that lies well below one. Although the functions describing GST' , D, and FST in terms of the frequency of the most frequent allele are different, the allele frequencies that maximize them are identical. Moreover, we show using coalescent simulations that when taking into account the specific maximal values of the three statistics, their behaviours become similar across a large range of migration rates. We use our results to explain two empirical patterns: the similar values of the three statistics among North American wolves, and the low D values compared to GST' and FST in Atlantic salmon. The results suggest that the three statistics are often predictably similar, so that they can make quite similar contributions to data analysis. When they are not similar, the difference can be understood in relation to features of genetic diversity.

Use of stochastic patch occupancy models in the California red-legged frog for Bayesian inference regarding past events and future persistence.

Assessing causes of population decline is critically important to management of threatened species. Stochastic patch occupancy models (SPOMs) are popular tools for examining spatial and temporal dynamics of populations when presence-absence data in multiple habitat patches are available. We developed a Bayesian Markov chain method that extends existing SPOMs by focusing on past environmental changes that may have altered occupancy patterns prior to the beginning of data collection. Using occupancy data from 3 creeks, we applied the method to assess 2 hypothesized causes of population decline-in situ die-off and residual impact of past source population loss-in the California red-legged frog. Despite having no data for the 20-30 years between the hypothetical event leading to population decline and the first data collected, we were able to discriminate among hypotheses, finding evidence that in situ die-off increased in 2 of the creeks. Although the creeks had comparable numbers of occupied segments, owing to different extinction-colonization dynamics, our model predicted an 8-fold difference in persistence probabilities of their populations to 2030. Adding a source population led to a greater predicted persistence probability than did decreasing the in situ die-off, emphasizing that reversing the deleterious impacts of a disturbance may not be the most efficient management strategy. We expect our method will be useful for studying dynamics and evaluating management strategies of many species.

Uso de Modelos Estocásticos de Ocupación de Fragmentos de la Rana Californiana de Patas Rojas para la Inferencia Bayesiana con Respecto a Eventos Pasados y su Persistencia en el Futuro Resumen La evaluación de las causas de la declinación poblacional es de importancia crítica para el manejo de especies amenazadas. Los modelos estocásticos de ocupación de parches (SPOMs, en inglés) son herramientas populares para examinar las dinámicas espaciales y temporales de las poblaciones cuando están disponibles los datos de presencia-ausencia para múltiples parches de hábitat. Desarrollamos un método bayesiano de cadena de Markov que extiende a los SPOMs existentes al enfocarse en los cambios ambientales pasados que podrían haber alterado los patrones de ocupación previos al inicio de la recolección de datos. Con los datos de ocupación de tres arroyos, aplicamos este método para evaluar dos causas hipotéticas de la declinación poblacional - muerte in situ e impacto residual de causas anteriores de pérdida de una poblacion fuente - de la rana californiana de patas rojas. A pesar de no tener datos para 20 - 30 años entre el evento hipotético que derivó en la declinación poblacional y los primeros datos recolectados, pudimos discriminar entre las hipótesis, encontrando evidencia de que la muerte in situ incrementó en dos de los arroyos. Aunque los arroyos tuvieron un número comparable de segmentos ocupados, debido a diferentes dinámicas de colonización - extinción, nuestro modelo predijo una diferencia ocho veces mayor en las probabilidades de persistencia de las poblaciones hasta el 2030. La suma de una población fuente resultó en una mayor probabilidad de persistencia pronosticada que con la reducción de la muerte in situ, enfatizando que la reversión de los impactos dañinos de una perturbación puede no ser la mejor estrategia de manejo. Esperamos que nuestro método sea útil para el estudio de las dinámicas y para la evaluación de las estrategias de manejo de muchas especies.

Intercalated cushion cells within the cardiac outflow tract are derived from the myocardial troponin T type 2 (Tnnt2) Cre lineage.

BACKGROUND: The origin of the intercalated cushions that develop into the anterior cusp of the pulmonary valve (PV) and the noncoronary cusp of the aortic valve (AV) is not well understood. RESULTS: Cre transgenes in combination with the Rosa TdTomato-EGFP reporter were used to generate three-dimensional lineage mapping of AV and PV cusps during intercalated cushion development. Tie2-Cre;EGFP was used to mark endothelial-derived mesenchymal cells, Wnt1-Cre;EGFP for cardiac neural crest and cardiac Troponin T (Tnnt2)Cre;EGFP, for myocardial lineage. The highest percentage of intercalated cushion cells at embryonic day (E) 12.5 was Tnnt2-Cre; EGFP positive; 68.0% for the PV and 50.0% AV. Neither Tnnt2 mRNA nor Tnnt2-Cre protein was expressed in the intercalated cushions; and the Tnnt2-Cre lineage intercalated cushion cells were also positive for the mesenchymal markers Sox9 and versican. Tnnt2-Cre lineage was present within the forming intercalated cushions from E11.5 and was present in the intercalated cushion derived PV and AV cusps and localized to the fibrosa layer at postnatal day 0. CONCLUSIONS: Intercalated cushions of the developing outflow tract are populated with Tnnt2-Cre derived cells, a Cre reporter previously used for tracing and excision of myocardial cells and not previously associated with mesenchymal cells. Developmental Dynamics 247:1005-1017, 2018. © 2018 Wiley Periodicals, Inc.

Host shift and cospeciation rate estimation from co-phylogenies.

Host shifts can cause novel infectious diseases, and is a key process in diversification. Disentangling the effects of host shift vs. those of cospeciation is non-trivial as both can result in phylogenic congruence. We develop a new framework based on network analysis and Approximate Bayesian Computation to quantify host shift and cospeciation rates in host-parasite systems. Our method enables estimation of the expected time to the next host shift or cospeciation event. We then apply it to avian haemosporidian parasite systems and to the pocket gophers-chewing lice system, and demonstrate that both host shift and cospeciation can be reliably estimated by our method. We confirm that host shifts have shaped the evolutionary history of avian haemosporidian parasites and have played a minor role in the gopher-chewing lice system. Our method is promising for predicting the rate of potential host shifts and thus the emergence of novel infectious diseases.

Lumican deficiency results in cardiomyocyte hypertrophy with altered collagen assembly.

The ability of the heart to adapt to increased stress is dependent on the modification of its extracellular matrix (ECM) architecture that is established during postnatal development as cardiomyocytes differentiate, a process that is poorly understood. We hypothesized that the small leucine-rich proteoglycan (SLRP) lumican (LUM), which binds collagen and facilitates collagen assembly in other tissues, may play a critical role in establishing the postnatal murine myocardial ECM. Although previous studies suggest that LUM deficient mice (lum(-/-)) exhibit skin anomalies consistent with Ehlers-Danlos syndrome, lum(-/-) hearts have not been evaluated. These studies show that LUM was immunolocalized to non-cardiomyocytes of the cardiac ventricles and its expression increased throughout development. Lumican deficiency resulted in significant (50%) perinatal death and further examination of the lum(-/-) neonatal hearts revealed an increase in myocardial tissue without a significant increase in cell proliferation. However cardiomyocytes from surviving postnatal day 0 (P0), 1 month (1 mo) and adult (4 mo) lum(-/-) hearts were significantly larger than their wild type (WT) littermates. Immunohistochemistry revealed that the increased cardiomyocyte size in the lum(-/-) hearts correlated with alteration of the cardiomyocyte pericellular ECM components collagenα1(I) and the class I SLRP decorin (DCN). Western blot analysis demonstrated that the ratio of glycosaminoglycan (GAG) decorated DCN to core DCN was reduced in P0 and 1 mo lum(-/-) hearts. There was also a reduction in the ß and γ forms of collagenα1(I) in lum(-/-) hearts. While the total insoluble collagen content was significantly reduced, the fibril size was increased in lum(-/-) hearts, indicating that LUM may play a role in collagen fiber stability and lateral fibril assembly. These results suggest that LUM controls cardiomyocyte growth by regulating the pericellular ECM and also indicates that LUM may coordinate multiple factors of collagen assembly in the murine heart. Further investigation into the role of LUM may yield novel therapeutic targets and/or biomarkers for patients with cardiovascular disease.

Genetic consequences of population expansions and contractions in the common hippopotamus (Hippopotamus amphibius) since the Late Pleistocene.

Over the past two decades, an increasing amount of phylogeographic work has substantially improved our understanding of African biogeography, in particular the role played by Pleistocene pluvial-drought cycles on terrestrial vertebrates. However, still little is known on the evolutionary history of semi-aquatic animals, which faced tremendous challenges imposed by unpredictable availability of water resources. In this study, we investigate the Late Pleistocene history of the common hippopotamus (Hippopotamus amphibius), using mitochondrial and nuclear DNA sequence variation and range-wide sampling. We documented a global demographic and spatial expansion approximately 0.1-0.3 Myr ago, most likely associated with an episode of massive drainage overflow. These events presumably enabled a historical continent-wide gene flow among hippopotamus populations, and hence, no clear continental-scale genetic structuring remains. Nevertheless, present-day hippopotamus populations are genetically disconnected, probably as a result of the mid-Holocene aridification and contemporary anthropogenic pressures. This unique pattern contrasts with the biogeographic paradigms established for savannah-adapted ungulate mammals and should be further investigated in other water-associated taxa. Our study has important consequences for the conservation of the hippo, an emblematic but threatened species that requires specific protection to curtail its long-term decline.

Turnover and accumulation of genetic diversity across large time-scale cycles of isolation and connection of populations.

Major climatic and geological events but also population history (secondary contacts) have generated cycles of population isolation and connection of long and short periods. Recent empirical and theoretical studies suggest that fast evolutionary processes might be triggered by such events, as commonly illustrated in ecology by the adaptive radiation of cichlid fishes (isolation and reconnection of lakes and watersheds) and in epidemiology by the fast adaptation of the influenza virus (isolation and reconnection in hosts). We test whether cyclic population isolation and connection provide the raw material (standing genetic variation) for species evolution and diversification. Our analytical results demonstrate that population isolation and connection can provide, to populations, a high excess of genetic diversity compared with what is expected at equilibrium. This excess is either cyclic (high allele turnover) or cumulates with time depending on the duration of the isolation and the connection periods and the mutation rate. We show that diversification rates of animal clades are associated with specific periods of climatic cycles in the Quaternary. We finally discuss the importance of our results for macroevolutionary patterns and for the inference of population history from genomic data.

On the transition of genetic differentiation from isolation to panmixia: what we can learn from GST and D.

Population genetic differentiation characterizes the repartition of alleles among populations. It is commonly thought that genetic differentiation measures, such as GST and D, should be near zero when allele frequencies are close to their expected value in panmictic populations, and close to one when they are close to their expected value in isolated populations. To analyse those properties, we first derive analytically a reference function f of known parameters that describes how important features of genetic differentiation (e.g. gene diversity, proportion of private alleles, frequency of the most common allele) are close to their expected panmictic and isolation value. We find that the behaviour of function f differs according to three distinct mutation regimes defined by the scaled mutation rate and the number of populations. Then, we compare GST and D to f, and demonstrate that their signal of differentiation strongly depends on the mutation regime. In particular, we show that D captures well the variations of genetic diversity when mutation is weak, otherwise it overestimates it when panmixia is not met. GST detects population differentiation when mutation is intermediate but has a low sensitivity to the variations of genetic diversity when mutation is weak. When mutation is strong the domain of sensitivity of both measures are altered. Finally, we also point out the importance of the number of populations on genetic differentiation measures, and provide recommendations for the use of GST and D.

Multi-omic dataset of patient-derived tumor organoids of neuroendocrine neoplasms.

BACKGROUND: Organoids are 3-dimensional experimental models that summarize the anatomical and functional structure of an organ. Although a promising experimental model for precision medicine, patient-derived tumor organoids (PDTOs) have currently been developed only for a fraction of tumor types. RESULTS: We have generated the first multi-omic dataset (whole-genome sequencing [WGS] and RNA-sequencing [RNA-seq]) of PDTOs from the rare and understudied pulmonary neuroendocrine tumors (n = 12; 6 grade 1, 6 grade 2) and provide data from other rare neuroendocrine neoplasms: small intestine (ileal) neuroendocrine tumors (n = 6; 2 grade 1 and 4 grade 2) and large-cell neuroendocrine carcinoma (n = 5; 1 pancreatic and 4 pulmonary). This dataset includes a matched sample from the parental sample (primary tumor or metastasis) for a majority of samples (21/23) and longitudinal sampling of the PDTOs (1 to 2 time points), for a total of n = 47 RNA-seq and n = 33 WGS. We here provide quality control for each technique and the raw and processed data as well as all scripts for genomic analyses to ensure an optimal reuse of the data. In addition, we report gene expression data and somatic small variant calls and describe how they were generated, in particular how we used WGS somatic calls to train a random forest classifier to detect variants in tumor-only RNA-seq. We also report all histopathological images used for medical diagnosis: hematoxylin and eosin-stained slides, brightfield images, and immunohistochemistry images of protein markers of clinical relevance. CONCLUSIONS: This dataset will be critical to future studies relying on this PDTO biobank, such as drug screens for novel therapies and experiments investigating the mechanisms of carcinogenesis in these understudied diseases.

Kidney Function and Risk of Renal Cell Carcinoma.

BACKGROUND: We evaluated the temporal association between kidney function, assessed by estimated glomerular filtration rate (eGFR), and the risk of incident renal cell carcinoma (RCC). We also evaluated whether eGFR could improve RCC risk discrimination beyond established risk factors. METHODS: We analyzed the UK Biobank cohort, including 463,178 participants of whom 1,447 were diagnosed with RCC during 5,696,963 person-years of follow-up. We evaluated the temporal association between eGFR and RCC risk using flexible parametric survival models, adjusted for C-reactive protein and RCC risk factors. eGFR was calculated from creatinine and cystatin C levels. RESULTS: Lower eGFR, an indication of poor kidney function, was associated with higher RCC risk when measured up to 5 years prior to diagnosis. The RCC HR per SD decrease in eGFR when measured 1 year before diagnosis was 1.26 [95% confidence interval (95% CI), 1.16-1.37], and 1.11 (95% CI, 1.05-1.17) when measured 5 years before diagnosis. Adding eGFR to the RCC risk model provided a small improvement in risk discrimination 1 year before diagnosis with an AUC of 0.73 (95% CI, 0.67-0.84) compared with the published model (0.69; 95% CI, 0.63-0.79). CONCLUSIONS: This study demonstrated that kidney function markers are associated with RCC risk, but the nature of these associations are consistent with reversed causality. Markers of kidney function provided limited improvements in RCC risk discrimination beyond established risk factors. IMPACT: eGFR may be of potential use to identify individuals in the extremes of the risk distribution.

Druggable growth dependencies and tumor evolution analysis in patient-derived organoids of neuroendocrine neoplasms from multiple body sites.

Neuroendocrine neoplasms (NENs) comprise well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). Treatment options for patients with NENs are limited, in part due to lack of accurate models. We establish patient-derived tumor organoids (PDTOs) from pulmonary NETs and derive PDTOs from an understudied subtype of NEC, large cell neuroendocrine carcinoma (LCNEC), arising from multiple body sites. PDTOs maintain the gene expression patterns, intra-tumoral heterogeneity, and evolutionary processes of parental tumors. Through hypothesis-driven drug sensitivity analyses, we identify ASCL1 as a potential biomarker for response of LCNEC to treatment with BCL-2 inhibitors. Additionally, we discover a dependency on EGF in pulmonary NET PDTOs. Consistent with these findings, we find that, in an independent cohort, approximately 50% of pulmonary NETs express EGFR. This study identifies an actionable vulnerability for a subset of pulmonary NETs, emphasizing the utility of these PDTO models.

Multiomic analysis of malignant pleural mesothelioma identifies molecular axes and specialized tumor profiles driving intertumor heterogeneity.

Malignant pleural mesothelioma (MPM) is an aggressive cancer with rising incidence and challenging clinical management. Through a large series of whole-genome sequencing data, integrated with transcriptomic and epigenomic data using multiomics factor analysis, we demonstrate that the current World Health Organization classification only accounts for up to 10% of interpatient molecular differences. Instead, the MESOMICS project paves the way for a morphomolecular classification of MPM based on four dimensions: ploidy, tumor cell morphology, adaptive immune response and CpG island methylator profile. We show that these four dimensions are complementary, capture major interpatient molecular differences and are delimited by extreme phenotypes that-in the case of the interdependent tumor cell morphology and adapted immune response-reflect tumor specialization. These findings unearth the interplay between MPM functional biology and its genomic history, and provide insights into the variations observed in the clinical behavior of patients with MPM.

Mathematical constraints on FST: multiallelic markers in arbitrarily many populations.

Interpretations of values of the FST measure of genetic differentiation rely on an understanding of its mathematical constraints. Previously, it has been shown that FST values computed from a biallelic locus in a set of multiple populations and FST values computed from a multiallelic locus in a pair of populations are mathematically constrained as a function of the frequency of the allele that is most frequent across populations. We generalize from these cases to report here the mathematical constraint on FST given the frequency M of the most frequent allele at a multiallelic locus in a set of multiple populations. Using coalescent simulations of an island model of migration with an infinitely-many-alleles mutation model, we argue that the joint distribution of FST and M helps in disentangling the separate influences of mutation and migration on FST. Finally, we show that our results explain a puzzling pattern of microsatellite differentiation: the lower FST in an interspecific comparison between humans and chimpanzees than in the comparison of chimpanzee populations. We discuss the implications of our results for the use of FST. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.

FSTruct: An FST -based tool for measuring ancestry variation in inference of population structure.

In model-based inference of population structure from individual-level genetic data, individuals are assigned membership coefficients in a series of statistical clusters generated by clustering algorithms. Distinct patterns of variability in membership coefficients can be produced for different groups of individuals, for example, representing different predefined populations, sampling sites or time periods. Such variability can be difficult to capture in a single numerical value; membership coefficient vectors are multivariate and potentially incommensurable across predefined groups, as the number of clusters over which individuals are distributed can vary among groups of interest. Further, two groups might share few clusters in common, so that membership coefficient vectors are concentrated on different clusters. We introduce a method for measuring the variability of membership coefficients of individuals in a predefined group, making use of an analogy between variability across individuals in membership coefficient vectors and variation across populations in allele frequency vectors. We show that in a model in which membership coefficient vectors in a population follow a Dirichlet distribution, the measure increases linearly with a parameter describing the variance of a specified component of the membership vector and does not depend on its mean. We apply the approach, which makes use of a normalized FST statistic, to data on inferred population structure in three example scenarios. We also introduce a bootstrap test for equivalence of two or more predefined groups in their level of membership coefficient variability. Our methods are implemented in the r package FSTruct.

Mohs microsurgery for localized penile carcinoma: 10 year retrospective review of local recurrence rates and surgical complications.

PURPOSE: To investigate the local recurrence rates of men treated with Mohs microsurgery (MMS) for penile carcinoma. The secondary outcome was surgical complications from the MMS procedure or the subsequent reconstructive procedures. MATERIALS AND METHODS: All patients from 2010 to 2020 with penile carcinoma at our institution were seen in a multidisciplinary setting. Patients with Ta, Tis, T1, and T2 disease were considered candidates for MMS. Clinical and pathologic data were collected for analysis. Local recurrence rates were stratified by stage and complications reported per the Clavien-Dindo Grade. RESULTS: A total of 43 patients met inclusion criteria. The median age at diagnosis was 64 years. Stage distribution was Ta in 4.7%, Tis in 58.1%, T1a in 14.0%, T1b in 7.0%, and T2 in 16.3%. No patients had a positive surgical margin after MMS. The overall local recurrence rate was 2% (n = 1) at a median of 47 months. Local recurrence rates at 1, 3, and 5 years for Ta, Tis, and T1 patients were 0%. Local recurrence rates for T2 patients were 14% at 1 year. Complications occurred in 12% (n = 5), all of which were Clavien-Dindo ≤ III. CONCLUSIONS: MMS provides effective local control for Ta, Tis, and T1 penile cancer with an overall local recurrence rate of 2% and an acceptable complication rate. A multi-disciplinary team involving urologic oncology, reconstructive urology, and MMS is essential to patient management.

A molecular phenotypic map of malignant pleural mesothelioma.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare understudied cancer associated with exposure to asbestos. So far, MPM patients have benefited marginally from the genomics medicine revolution due to the limited size or breadth of existing molecular studies. In the context of the MESOMICS project, we have performed the most comprehensive molecular characterization of MPM to date, with the underlying dataset made of the largest whole-genome sequencing series yet reported, together with transcriptome sequencing and methylation arrays for 120 MPM patients. RESULTS: We first provide comprehensive quality controls for all samples, of both raw and processed data. Due to the difficulty in collecting specimens from such rare tumors, a part of the cohort does not include matched normal material. We provide a detailed analysis of data processing of these tumor-only samples, showing that all somatic alteration calls match very stringent criteria of precision and recall. Finally, integrating our data with previously published multiomic MPM datasets (n = 374 in total), we provide an extensive molecular phenotype map of MPM based on the multitask theory. The generated map can be interactively explored and interrogated on the UCSC TumorMap portal (https://tumormap.ucsc.edu/?p=RCG_MESOMICS/MPM_Archetypes ). CONCLUSIONS: This new high-quality MPM multiomics dataset, together with the state-of-art bioinformatics and interactive visualization tools we provide, will support the development of precision medicine in MPM that is particularly challenging to implement in rare cancers due to limited molecular studies.