Classification of germline variants in the TP53 gene: from uncertainty to clinical action

Abstract Purpose This work aimed to evaluate genotype-phenotype associations in individuals carrying germline variants of transmembrane protein 127 gene (TMEM127), a poorly known gene that confers susceptibility to pheochromocytoma (PHEO) and paraganglioma (PGL). Design Data were collected from a registry of probands with TMEM127 variants, published reports, and public databases. Main Outcome Analysis Clinical, genetic, and functional associations were determined. Results The cohort comprised 110 index patients (111 variants) with a mean age of 45 years (range, 21-84 years). Females were predominant (76 vs 34, P < .001). Most patients had PHEO (n = 94; 85.5%), although PGL (n = 10; 9%) and renal cell carcinoma (RCC, n = 6; 5.4%) were also detected, either alone or in combination with PHEO. One-third of the cases had multiple tumors, and known family history was reported in 15.4%. Metastatic PHEO/PGL was rare (2.8%). Epinephrine alone, or combined with norepinephrine, accounted for 82% of the catecholamine profiles of PHEO/PGLs. Most variants (n = 63) occurred only once and 13 were recurrent (2-12 times). Although nontruncating variants were less frequent than truncating changes overall, they were predominant in non-PHEO clinical presentations (36% PHEO-only vs 69% other, P < .001) and clustered disproportionately within transmembrane regions (P < .01), underscoring the relevance of these domains for TMEM127 function. Integration of clinical and previous experimental data supported classification of variants into 4 groups based on mutation type, localization, and predicted disruption. Conclusions Patients with TMEM127 variants often resemble sporadic nonmetastatic PHEOs. PGL and RCC may also co-occur, although their causal link requires further evaluation. We propose a new classification to predict variant pathogenicity and assist with carrier surveillance.

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Acromegaly Disease Activity According to ACRODAT®, in Spain: ACROVAL Study

10.21203/rs.3.rs-627625/v1 ◽

2021 ◽

Author(s):

Monica Marazuela ◽

Concepción Blanco ◽

Ignacio Bernabeu ◽

Edelmiro Menendez ◽

Rocío Villar ◽

...

Keyword(s):

Disease Activity ◽

Clinical Evaluation ◽

Cross Sectional Study ◽

Patient Centered ◽

Cross Sectional ◽

Mild Disease ◽

Clinical Action ◽

The Relationship

Abstract Objectives: To evaluate disease activity status using the Acromegaly Disease Activity Tool (ACRODAT®) in a cohort of Spanish acromegaly patients, to assess the relationship between the level of disease activity according to both ACRODAT® and the physicians’ clinical evaluation, and to study the potential discrepancies in the perception of symptoms between physicians and patients.Design: Multicenter, observational, descriptive and cross-sectional study. Methods: Disease activity was assessed in adult patients with acromegaly under pharmacological treatment during at least 6 months using ACRODAT®.Results: According to ACRODAT®, 48.2%, 31.8% and 20.0% of a total of 111 patients were classified as having a stable disease (S), mild disease activity (M-DA) and significant disease activity (S-DA) respectively. ACRODAT® classification of disease activity significantly correlated with physicians’ opinion, with a moderate inter-rater agreement and a specificity of 92.45% (PPV=86.21%). No correlation was found between IGF-1 levels and severity of symptoms or quality of life (QoL). A decision to take clinical action was significantly more frequent in S-DA and M-DA patients than S patients but no action was taken on 5 (22.7%) and 27 (77.1%) S-DA and M-DA patients, respectivelyConclusions: ACRODAT® detected disease activity in 51.8% of patients. Interestingly, although M-DA and S-DA patients were likely to be in the process of being controlled, action was not always taken on these patients. ACRODAT® is a validated and highly specific tool that may be useful to routinely monitor acromegaly and to identify patients with non-obvious disease activity by incorporating “patient-centered” parameters like symptoms and QoL to the clinical evaluation of acromegaly.

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Determining mutational burden and signature using RNA-seq from tumor-only samples

10.21203/rs.2.21641/v1 ◽

2020 ◽

Author(s):

Erik Jessen ◽

Yuanhang Liu ◽

Jaime Davila ◽

Jean-Pierre Kocher ◽

Chen Wang

Keyword(s):

Uterine Cancer ◽

Natural Aging ◽

Tumor Type ◽

Rna Seq ◽

Mutational Signatures ◽

Germline Variants ◽

Normal Pair ◽

Driving Mechanisms ◽

Mutational Burden

Abstract Background: Traditionally, mutational burden and mutational signatures have been assessed by tumor-normal pair DNA sequencing. The requirement of having both normal and tumor samples is not always feasible from a clinical perspective, and led us to investigate the efficacy of using RNA sequencing of only the tumor sample to determine the mutational burden and signatures, and subsequently molecular cause of the cancer. The potential advantages include reducing the cost of testing, and simultaneously providing information on the gene expression profile and gene fusions present in the tumor.Results: In this study, we devised supervised and unsupervised learning methods to determine mutational signatures from tumor RNA-seq data. As applications, we applied the methods to a training set of 587 TCGA uterine cancer RNAseq samples, and examined in an independent testing set of xxx TCGA colorectal cancer RNAseq samples. Both diseases are known associated with microsatellite instable high (MSI-H) and driver defects in DNA polymerase ɛ (POLɛ). From RNAseq called variants, we found majority (>95%) are likely germline variants, leading to C>T enriched germline variants (dbSNP) widely applicable in tumor and normal RNAseq samples. We found significant associations between RNA-derived mutational burdens and MSI/POLɛ status, and insignificant relationship between RNAseq total coverage and derived mutational burdens. Additionally we found that over 80% of variants could be explained by using the COSMIC mutational signature-5, -6 and -10, which are implicated in natural aging, MSI-H, and POLɛ, respectively. For classifying tumor type, within UCEC we achieved a recall of 0.56 and 0.78, and specificity of 0.66 and 0.99 for MSI and POLɛ respectively. By applying learnt RNA signatures from UCEC to COAD, we were able to improve our classification of both MSI and POLɛ. Conclusions: Taken together, our work provides a novel method to detect RNAseq derived mutational signatures with effective procedures to remove likely germline variants. It can leads to accurate classification of underlying driving mechanisms of DNA damage deficiency.

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Functional characterisation guides classification of novel BAP1 germline variants

npj Genomic Medicine ◽

10.1038/s41525-020-00157-6 ◽

2020 ◽

Vol 5 (1) ◽

Author(s):

Jing Han Hong ◽

Siao Ting Chong ◽

Po-Hsien Lee ◽

Jing Tan ◽

Hong Lee Heng ◽

...

Keyword(s):

Epithelial Mesenchymal Transition ◽

Cancer Risks ◽

Germline Variants ◽

Mesenchymal Transition ◽

Functional Assays ◽

Functional Characterisation ◽

Genetics And Genomics ◽

Potential Cancer ◽

Emt Markers

AbstractWe have identified six patients harbouring distinct germline BAP1 mutations. In this study, we functionally characterise known BAP1 pathogenic and likely benign germline variants out of these six patients to aid in the evaluation and classification of unknown BAP1 germline variants. We found that pathogenic germline variants tend to encode truncated proteins, show diminished expression of epithelial-mesenchymal transition (EMT) markers, are localised in the cytosol and have reduced deubiquitinase capabilities. We show that these functional assays are useful for BAP1 variant curation and may be added in the American College of Medical Genetics and Genomics (ACMG) criteria for BAP1 variant classification. This will allow clinicians to distinguish between BAP1 pathogenic and likely benign variants reliably and may aid to quickly benchmark newly identified BAP1 germline variants. Classification of novel BAP1 germline variants allows clinicians to inform predisposed patients and relevant family members regarding potential cancer risks, with appropriate clinical interventions implemented if required.

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Determining mutational burden and signature using RNA-seq from tumor-only samples

10.21203/rs.2.21641/v3 ◽

2021 ◽

Author(s):

Erik Jessen ◽

Yuanhang Liu ◽

Jaime Davila ◽

Jean-Pierre Kocher ◽

Chen Wang

Keyword(s):

Uterine Cancer ◽

Natural Aging ◽

Tumor Type ◽

Rna Seq ◽

Mutational Signatures ◽

Germline Variants ◽

Normal Pair ◽

Driving Mechanisms ◽

Mutational Burden

Abstract Background: Traditionally, mutational burden and mutational signatures have been assessed by tumor-normal pair DNA sequencing. The requirement of having both normal and tumor samples is not always feasible from a clinical perspective, and led us to investigate the efficacy of using RNA sequencing of only the tumor sample to determine the mutational burden and signatures, and subsequently molecular cause of the cancer. The potential advantages include reducing the cost of testing, and simultaneously providing information on the gene expression profile and gene fusions present in the tumor. Results: In this study, we devised supervised and unsupervised learning methods to determine mutational signatures from tumor RNA-seq data. As applications, we applied the methods to a training set of 587 TCGA uterine cancer RNA-seq samples, and examined in an independent testing set of 521 TCGA colorectal cancer RNA-seq samples. Both diseases are known associated with microsatellite instable high (MSI-H) and driver defects in DNA polymerase ɛ (POLɛ). From RNA-seq called variants, we found majority (>95%) are likely germline variants, leading to C>T enriched germline variants (dbSNP) widely applicable in tumor and normal RNA-seq samples. We found significant associations between RNA-derived mutational burdens and MSI/POLɛ status, and insignificant relationship between RNA-seq total coverage and derived mutational burdens. Additionally we found that over 80% of variants could be explained by using the COSMIC mutational signature-5, -6 and -10, which are implicated in natural aging, MSI-H, and POLɛ, respectively. For classifying tumor type, within UCEC we achieved a recall of 0.56 and 0.78, and specificity of 0.66 and 0.99 for MSI and POLɛ respectively. By applying learnt RNA signatures from UCEC to COAD, we were able to improve our classification of both MSI and POLɛ. Conclusions: Taken together, our work provides a novel method to detect RNA-seq derived mutational signatures with effective procedures to remove likely germline variants. It can leads to accurate classification of underlying driving mechanisms of DNA damage deficiency.

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Determining mutational burden and signature using RNA-seq from tumor-only samples

BMC Medical Genomics ◽

10.1186/s12920-021-00898-y ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Erik Jessen ◽

Yuanhang Liu ◽

Jaime Davila ◽

Jean-Pierre Kocher ◽

Chen Wang

Keyword(s):

Uterine Cancer ◽

Natural Aging ◽

Tumor Type ◽

Rna Seq ◽

Mutational Signatures ◽

Germline Variants ◽

Normal Pair ◽

Driving Mechanisms ◽

Mutational Burden

Abstract Background Traditionally, mutational burden and mutational signatures have been assessed by tumor-normal pair DNA sequencing. The requirement of having both normal and tumor samples is not always feasible from a clinical perspective, and led us to investigate the efficacy of using RNA sequencing of only the tumor sample to determine the mutational burden and signatures, and subsequently molecular cause of the cancer. The potential advantages include reducing the cost of testing, and simultaneously providing information on the gene expression profile and gene fusions present in the tumor. Results In this study, we devised supervised and unsupervised learning methods to determine mutational signatures from tumor RNA-seq data. As applications, we applied the methods to a training set of 587 TCGA uterine cancer RNA-seq samples, and examined in an independent testing set of 521 TCGA colorectal cancer RNA-seq samples. Both diseases are known associated with microsatellite instable high (MSI-H) and driver defects in DNA polymerase ɛ (POLɛ). From RNA-seq called variants, we found majority (> 95%) are likely germline variants, leading to C > T enriched germline variants (dbSNP) widely applicable in tumor and normal RNA-seq samples. We found significant associations between RNA-derived mutational burdens and MSI/POLɛ status, and insignificant relationship between RNA-seq total coverage and derived mutational burdens. Additionally we found that over 80% of variants could be explained by using the COSMIC mutational signature-5, -6 and -10, which are implicated in natural aging, MSI-H, and POLɛ, respectively. For classifying tumor type, within UCEC we achieved a recall of 0.56 and 0.78, and specificity of 0.66 and 0.99 for MSI and POLɛ respectively. By applying learnt RNA signatures from UCEC to COAD, we were able to improve our classification of both MSI and POLɛ. Conclusions Taken together, our work provides a novel method to detect RNA-seq derived mutational signatures with effective procedures to remove likely germline variants. It can leads to accurate classification of underlying driving mechanisms of DNA damage deficiency.

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Determining mutational burden and signature using RNA-seq from tumor-only samples

10.21203/rs.2.21641/v2 ◽

2020 ◽

Author(s):

Erik Jessen ◽

Yuanhang Liu ◽

Jaime Davila ◽

Jean-Pierre Kocher ◽

Chen Wang

Keyword(s):

Uterine Cancer ◽

Natural Aging ◽

Tumor Type ◽

Rna Seq ◽

Mutational Signatures ◽

Germline Variants ◽

Normal Pair ◽

Driving Mechanisms ◽

Mutational Burden

Abstract Background: Traditionally, mutational burden and mutational signatures have been assessed by tumor-normal pair DNA sequencing. The requirement of having both normal and tumor samples is not always feasible from a clinical perspective, and led us to investigate the efficacy of using RNA sequencing of only the tumor sample to determine the mutational burden and signatures, and subsequently molecular cause of the cancer. The potential advantages include reducing the cost of testing, and simultaneously providing information on the gene expression profile and gene fusions present in the tumor. Results: In this study, we devised supervised and unsupervised learning methods to determine mutational signatures from tumor RNA-seq data. As applications, we applied the methods to a training set of 587 TCGA uterine cancer RNA-seq samples, and examined in an independent testing set of 521 TCGA colorectal cancer RNA-seq samples. Both diseases are known associated with microsatellite instable high (MSI-H) and driver defects in DNA polymerase ɛ (POLɛ).From RNA-seq called variants, we found majority (>95%) are likely germline variants, leading to C>T enriched germline variants (dbSNP) widely applicable in tumor and normal RNA-seq samples. We found significant associations between RNA-derived mutational burdens and MSI/POLɛ status, and insignificant relationship between RNA-seq total coverage and derived mutational burdens. Additionally we found that over 80% of variants could be explained by using the COSMIC mutational signature-5, -6 and -10, which are implicated in natural aging, MSI-H, and POLɛ, respectively. For classifying tumor type, within UCEC we achieved a recall of 0.56 and 0.78, and specificity of 0.66 and 0.99 for MSI and POLɛ respectively. By applying learnt RNA signatures from UCEC to COAD, we were able to improve our classification of both MSI and POLɛ. Conclusions: Taken together, our work provides a novel method to detect RNA-seq derived mutational signatures with effective procedures to remove likely germline variants. It can leads to accurate classification of underlying driving mechanisms of DNA damage deficiency.

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Acromegaly disease activity according to ACRODAT®, a cross-sectional study in Spain: ACROVAL study

Endocrine ◽

10.1007/s12020-021-02900-0 ◽

2021 ◽

Author(s):

Mónica Marazuela ◽

Concepción Blanco ◽

Ignacio Bernabeu ◽

Edelmiro Menendez ◽

Rocío Villar ◽

...

Keyword(s):

Disease Activity ◽

Clinical Evaluation ◽

Cross Sectional Study ◽

Sectional Study ◽

Cross Sectional ◽

Mild Disease ◽

Clinical Action ◽

The Relationship

Abstract Objectives To evaluate disease activity status using the Acromegaly Disease Activity Tool (ACRODAT®) in a cohort of Spanish acromegaly patients, to assess the relationship between the level of disease activity according to both ACRODAT® and the physicians’ clinical evaluation, and to study the potential discrepancies in the perception of symptoms between physicians and patients. Design Multicenter, observational, descriptive and cross-sectional study. Methods Disease activity was assessed in adult patients with acromegaly under pharmacological treatment during at least 6 months using ACRODAT®. Results According to ACRODAT®, 48.2%, 31.8% and 20.0% of a total of 111 patients were classified as having a stable disease (S), mild disease activity (M-DA) and significant disease activity (S-DA) respectively. ACRODAT® classification of disease activity significantly correlated with physicians’ opinion, with a moderate inter-rater agreement and a specificity of 92.45% (PPV = 86.21%). No correlation was found between IGF-I levels and severity of symptoms or quality of life (QoL). A decision to take clinical action was significantly more frequent in S-DA and M-DA patients than S patients but no action was taken on 5 (22.7%) and 27 (77.1%) S-DA and M-DA patients, respectively Conclusions ACRODAT® detected disease activity in 51.8% of patients. Interestingly, although M-DA and S-DA patients were likely to be in the process of being controlled, action was not always taken on these patients. ACRODAT® is a validated and highly specific tool that may be useful to routinely monitor acromegaly and to identify patients with non-obvious disease activity by incorporating “patient-centred” parameters like symptoms and QoL to the clinical evaluation of acromegaly.

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Note on the spectral classification of carbon stars in the photographic infrared region

Symposium - International Astronomical Union ◽

10.1017/s0074180900053080 ◽

1966 ◽

Vol 24 ◽

pp. 21-23

Author(s):

Y. Fujita

Keyword(s):

Infrared Region ◽

Spectral Classification ◽

Carbon Stars

We have investigated the spectrograms (dispersion: 8Å/mm) in the photographic infrared region fromλ7500 toλ9000 of some carbon stars obtained by the coudé spectrograph of the 74-inch reflector attached to the Okayama Astrophysical Observatory. The names of the stars investigated are listed in Table 1.

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Diagnostic Value of Electron Microscopy in Soft Tissue Tumors

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100068096 ◽

1970 ◽

Vol 28 ◽

pp. 220-221

Author(s):

Gerald Fine ◽

Azorides R. Morales

Keyword(s):

Cardiac Myxoma ◽

Osteogenic Sarcoma ◽

Diagnostic Value ◽

Soft Tissue Tumors ◽

Amelanotic Melanoma ◽

Growth Patterns ◽

Light Microscopic Level ◽

Mesenchymal Tumors ◽

Good Agreement

For years the separation of carcinoma and sarcoma and the subclassification of sarcomas has been based on the appearance of the tumor cells and their microscopic growth pattern and information derived from certain histochemical and special stains. Although this method of study has produced good agreement among pathologists in the separation of carcinoma from sarcoma, it has given less uniform results in the subclassification of sarcomas. There remain examples of neoplasms of different histogenesis, the classification of which is questionable because of similar cytologic and growth patterns at the light microscopic level; i.e. amelanotic melanoma versus carcinoma and occasionally sarcoma, sarcomas with an epithelial pattern of growth simulating carcinoma, histologically similar mesenchymal tumors of different histogenesis (histiocytoma versus rhabdomyosarcoma, lytic osteogenic sarcoma versus rhabdomyosarcoma), and myxomatous mesenchymal tumors of diverse histogenesis (myxoid rhabdo and liposarcomas, cardiac myxoma, myxoid neurofibroma, etc.)

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