Dataset Information

Identification and classification of a new TRPM3 variant (? subtype).

ABSTRACT: TRPM3 is a non-selective cation channel that is activated by neural steroids such as pregnenolone sulfate, nifedipine, and clotrimazole. Despite the number of TRPM3 variants, few reports have described functional analyses of these different TRPM3 types. Here we identified a new TRPM variant from mouse dorsal root ganglion, termed TRPM3?3. We classified TRPM3?3 and another known variant (variant 6) into the ? subtype, and analyzed the TRPM3? variants. mRNA expression of TRPM3? was higher than that of TRPM3? variants in the mouse dorsal root ganglion. In Ca²⁺-imaging of HEK293 cells expressing either the TRPM3? variants or TRPM3?2, increases in cytosolic Ca²⁺ concentrations ([Ca²⁺]_i) induced by pregnenolone sulfate or nifedipine were smaller in cells expressing the TRPM3? variants compared to those expressing TRPM3?2. On the other hand, co-expression of TRPM3? variants had no effect on [Ca²⁺]_i increases induced by pregnenolone sulfate or nifedipine treatment of HEK293 cells expressing TRPM3?2. In Xenopus oocytes, small responses of TRPM3? variants to chemical agonists compared to TRPM3?2 were also observed. Interestingly, Xenopus oocytes expressing TRPM3?2 displayed heat-evoked currents with clear thresholds of about 40 °C that were larger than those evoked in oocytes expressing TRPM3? variants. Overall, these findings indicate that TRPM3? variants have low channel activity compared to TRPM3?.

SUBMITTER: Uchida K

PROVIDER: S-EPMC6583685 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Identification and classification of a new TRPM3 variant (γ subtype).

Uchida Kunitoshi K Fukuta Naomi N Yamazaki Jun J Tominaga Makoto M

The journal of physiological sciences : JPS 20190422 4

TRPM3 is a non-selective cation channel that is activated by neural steroids such as pregnenolone sulfate, nifedipine, and clotrimazole. Despite the number of TRPM3 variants, few reports have described functional analyses of these different TRPM3 types. Here we identified a new TRPM variant from mouse dorsal root ganglion, termed TRPM3γ3. We classified TRPM3γ3 and another known variant (variant 6) into the γ subtype, and analyzed the TRPM3γ variants. mRNA expression of TRPM3γ was higher than tha ...[more]

PMID: 31011981

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Project description:ImportanceMost patients with primary aldosteronism, a major cause of secondary hypertension, are not identified or appropriately treated because of difficulties in diagnosis and subtype classification. Applications of artificial intelligence combined with mass spectrometry-based steroid profiling could address this problem.ObjectiveTo assess whether plasma steroid profiling combined with machine learning might facilitate diagnosis and treatment stratification of primary aldosteronism, particularly for patients with unilateral adenomas due to pathogenic KCNJ5 sequence variants.Design, setting, and participantsThis diagnostic study was conducted at multiple tertiary care referral centers. Steroid profiles were measured from June 2013 to March 2017 in 462 patients tested for primary aldosteronism and 201 patients with hypertension. Data analyses were performed from September 2018 to August 2019.Main outcomes and measuresThe aldosterone to renin ratio and saline infusion tests were used to diagnose primary aldosteronism. Subtyping was done by adrenal venous sampling and follow-up of patients who underwent adrenalectomy. Statistical tests and machine-learning algorithms were applied to plasma steroid profiles. Areas under receiver operating characteristic curves, sensitivity, specificity, and other diagnostic performance measures were calculated.ResultsPrimary aldosteronism was confirmed in 273 patients (165 men [60%]; mean [SD] age, 51 [10] years), including 134 with bilateral disease and 139 with unilateral adenomas (58 with and 81 without somatic KCNJ5 sequence variants). Plasma steroid profiles varied according to disease subtype and were particularly distinctive in patients with adenomas due to KCNJ5 variants, who showed better rates of biochemical cure after adrenalectomy than other patients. Among patients tested for primary aldosteronism, a selection of 8 steroids in combination with the aldosterone to renin ratio showed improved effectiveness for diagnosis over either strategy alone. In contrast, the steroid profile alone showed superior performance over the aldosterone to renin ratio for identifying unilateral disease, particularly adenomas due to KCNJ5 variants. Among 632 patients included in the analysis, machine learning-designed combinatorial marker profiles of 7 steroids alone both predicted primary aldosteronism in 1 step and subtyped patients with unilateral adenomas due to KCNJ5 variants at diagnostic sensitivities of 69% (95% CI, 68%-71%) and 85% (95% CI, 81%-88%), respectively, and at specificities of 94% (95% CI, 93%-94%) and 97% (95% CI, 97%-98%), respectively. The validation series yielded comparable diagnostic performance.Conclusions and relevanceMachine learning-designed combinatorial plasma steroid profiles may facilitate both screening for primary aldosteronism and identification of patients with unilateral adenomas due to pathogenic KCNJ5 variants, who are most likely to show benefit from surgical intervention.

Project description:Consensus molecular subtyping is an RNA expression-based classification system for colorectal cancer (CRC). Genomic alterations accumulate during CRC pathogenesis, including the premalignant adenoma stage, leading to changes in RNA expression. Only a minority of adenomas progress to malignancies, a transition that is associated with specific DNA copy number aberrations or microsatellite instability (MSI). We aimed to investigate whether colorectal adenomas can already be stratified into consensus molecular subtype (CMS) classes, and whether specific CMS classes are related to the presence of specific DNA copy number aberrations associated with progression to malignancy. RNA sequencing was performed on 62 adenomas and 59 CRCs. MSI status was determined with polymerase chain reaction-based methodology. DNA copy number was assessed by low-coverage DNA sequencing (n?=?30) or array-comparative genomic hybridisation (n?=?32). Adenomas were classified into CMS classes together with CRCs from the study cohort and from The Cancer Genome Atlas (n?=?556), by use of the established CMS classifier. As a result, 54 of 62 (87%) adenomas were classified according to the CMS. The CMS3 'metabolic subtype', which was least common among CRCs, was most prevalent among adenomas (n?=?45; 73%). One of the two adenomas showing MSI was classified as CMS1 (2%), the 'MSI immune' subtype. Eight adenomas (13%) were classified as the 'canonical' CMS2. No adenomas were classified as the 'mesenchymal' CMS4, consistent with the fact that adenomas lack invasion-associated stroma. The distribution of the CMS classes among adenomas was confirmed in an independent series. CMS3 was enriched with adenomas at low risk of progressing to CRC, whereas relatively more high-risk adenomas were observed in CMS2. We conclude that adenomas can be stratified into the CMS classes. Considering that CMS1 and CMS2 expression signatures may mark adenomas at increased risk of progression, the distribution of the CMS classes among adenomas is consistent with the proportion of adenomas expected to progress to CRC. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Dataset Information

Identification and classification of a new TRPM3 variant (? subtype).

Publications

Identification and classification of a new TRPM3 variant (γ subtype).

Similar Datasets

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