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Clear cell ovarian carcinoma (CCOC) is an aggressive malignancy affecting younger women. Despite ovarian cancer subtypes having diverse molecular and clinical characteristics, the mainstay of treatment for advanced stage disease remains cytotoxic chemotherapy. Late stage CCOC is resistant to conventional chemotherapy, which means a suboptimal outcome for patients affected. Despite detailed genomic, epigenomic, transcriptomic, and proteomic characterisation, subtype-specific treatment for CCOC has shown little progress. The unique glycogen accumulation defining CCOC suggests altered metabolic pathway activity and dependency. This study presents the first metabolomic landscape of ovarian cancer subtypes, including 42 CCOC, 20 high-grade serous and 21 endometrioid ovarian carcinomas, together comprising the three most common ovarian carcinoma subtypes. We describe a distinct metabolomic landscape of CCOC compared with other ovarian cancer subtypes, including alterations in energy utilisation and cysteine metabolism. In addition, we identify CCOC-specific alterations in metabolic pathways including serine biosynthesis and ROS-associated pathways that could serve as potential therapeutic targets. Our study provides the first in-depth study into the metabolome of ovarian cancers and a rich resource to support ongoing research efforts to identify subtype-specific therapeutic targets that could improve the dismal outcome for patients with this devastating malignancy. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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Low-grade serous ovarian carcinoma (LGSC) is a rare and lethal subtype of ovarian cancer. LGSC is pathologically, biologically, and clinically distinct from the more common high-grade serous ovarian carcinoma (HGSC). LGSC arises from serous borderline ovarian tumours (SBTs). The mechanism of transformation for SBTs to LGSC remains poorly understood. To better understand the biology of LGSC, we performed whole proteome profiling of formalin-fixed, paraffin-embedded tissue blocks of LGSC (n = 11), HGSC (n = 19), and SBTs (n = 26). We identified that the whole proteome is able to distinguish between histotypes of the ovarian epithelial tumours. Proteins associated with the tumour microenvironment were differentially expressed between LGSC and SBTs. Fibroblast activation protein (FAP), a protein expressed in cancer-associated fibroblasts, is the most differentially abundant protein in LGSC compared with SBT. Multiplex immunohistochemistry (IHC) for immune markers (CD20, CD79a, CD3, CD8, and CD68) was performed to determine the presence of B cells, T cells, and macrophages. The LGSC FAP+ stroma was associated with greater abundance of Tregs and M2 macrophages, features not present in SBTs. Our proteomics cohort reveals that there are changes in the tumour microenvironment in LGSC compared with its putative precursor lesion, SBT. These changes suggest that the tumour microenvironment provides a supportive environment for LGSC tumourigenesis and progression. Thus, targeting the tumour microenvironment of LGSC may be a viable therapeutic strategy. © 2024 The Pathological Society of Great Britain and Ireland.
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Investigation of histopathology slides by pathologists is an indispensable component of the routine diagnosis of cancer. Artificial intelligence (AI) has the potential to enhance diagnostic accuracy, improve efficiency, and patient outcomes in clinical pathology. However, variations in tissue preparation, staining protocols, and histopathology slide digitization could result in over-fitting of deep learning models when trained on the data from only one center, thereby underscoring the necessity to generalize deep learning networks for multi-center use. Several techniques, including the use of grayscale images, color normalization techniques, and Adversarial Domain Adaptation (ADA) have been suggested to generalize deep learning algorithms, but there are limitations to their effectiveness and discriminability. Convolutional Neural Networks (CNNs) exhibit higher sensitivity to variations in the amplitude spectrum, whereas humans predominantly rely on phase-related components for object recognition. As such, we propose Adversarial fourIer-based Domain Adaptation (AIDA) which applies the advantages of a Fourier transform in adversarial domain adaptation. We conducted a comprehensive examination of subtype classification tasks in four cancers, incorporating cases from multiple medical centers. Specifically, the datasets included multi-center data for 1113 ovarian cancer cases, 247 pleural cancer cases, 422 bladder cancer cases, and 482 breast cancer cases. Our proposed approach significantly improved performance, achieving superior classification results in the target domain, surpassing the baseline, color augmentation and normalization techniques, and ADA. Furthermore, extensive pathologist reviews suggested that our proposed approach, AIDA, successfully identifies known histotype-specific features. This superior performance highlights AIDA's potential in addressing generalization challenges in deep learning models for multi-center histopathology datasets.
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Endometrial cancer (EC) has four molecular subtypes with strong prognostic value and therapeutic implications. The most common subtype (NSMP; No Specific Molecular Profile) is assigned after exclusion of the defining features of the other three molecular subtypes and includes patients with heterogeneous clinical outcomes. In this study, we employ artificial intelligence (AI)-powered histopathology image analysis to differentiate between p53abn and NSMP EC subtypes and consequently identify a sub-group of NSMP EC patients that has markedly inferior progression-free and disease-specific survival (termed 'p53abn-like NSMP'), in a discovery cohort of 368 patients and two independent validation cohorts of 290 and 614 from other centers. Shallow whole genome sequencing reveals a higher burden of copy number abnormalities in the 'p53abn-like NSMP' group compared to NSMP, suggesting that this group is biologically distinct compared to other NSMP ECs. Our work demonstrates the power of AI to detect prognostically different and otherwise unrecognizable subsets of EC where conventional and standard molecular or pathologic criteria fall short, refining image-based tumor classification. This study's findings are applicable exclusively to females.
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Inteligencia Artificial , Neoplasias Endometriales , Humanos , Femenino , Neoplasias Endometriales/patología , Neoplasias Endometriales/genética , Persona de Mediana Edad , Anciano , Procesamiento de Imagen Asistido por Computador/métodos , Pronóstico , Variaciones en el Número de Copia de ADN , Secuenciación Completa del Genoma , Proteína p53 Supresora de Tumor/genética , Estudios de CohortesRESUMEN
OBJECTIVE: Biomarkers reflecting real-time response to therapy and recurrence are lacking. We assessed the clinical value of detecting cell-free circulating tumor DNA (ctDNA) mutations in endometrial cancer (EC) and ovarian cancer (OC) patients. METHODS: EC/OC patients undergoing primary surgery were consented for tissue banking and 2-year serial blood draws. Tumor tissue DNA and plasma ctDNA underwent next generation sequencing using a targeted gene panel to identify somatic mutations. RESULTS: Of 44 patients (24 EC, 17 OC, 2 synchronous endometrial and ovarian carcinomas [SEOC] and 1 endocervical adenocarcinoma [EA]) at least one somatic mutation was identified in tumor tissue in 40 (91%, 20/24 EC, all OC/SEOC/EA), and in preoperative plasma ctDNA in 12 (27%) patients (6/24 [25%] EC and 6/17 [35%] OC). Detection of preoperative ctDNA mutations was associated with advanced stage, higher preoperative CA125, and disease recurrence. In 5/12 (42%) patients with preoperative ctDNA mutations, examination/imaging suggested clinical stage I however final pathology revealed stage II/III. In 11 patients where serial timepoints were assessed during treatment for ctDNA and CA125, ctDNA clearance preceded normalization of CA125. Thirteen patients developed recurrent disease (4 EC, 8 OC, 1 EA); 8 in whom ctDNA mutations were detected postoperatively, and 4 followed through time of recurrence with ctDNA mutations identified 2-5 months prior to clinical/radiologic/biomarker progression in 3. CONCLUSION: ctDNA can reflect larger tumor volume/metastases, treatment response and recurrence in EC and OC. Careful patient selection is critical to direct resources to patients most likely to benefit, considering disease burden and risk group.
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PURPOSE: Shallow whole-genome sequencing (sWGS) can detect copy-number (CN) aberrations. In high-grade serous ovarian cancer (HGSOC) sWGS identified CN signatures such as homologous recombination deficiency (HRD) to direct therapy. We applied sWGS with targeted sequencing to p53abn endometrial cancers to identify additional prognostic stratification and therapeutic opportunities. EXPERIMENTAL DESIGN: sWGS and targeted panel sequencing was performed on formalin-fixed, paraffin-embedded p53abn endometrial cancers. CN alterations, mutational data and CN signatures were derived, and associations to clinicopathologic and outcomes data were assessed. RESULTS: In 187 p53abn endometrial cancers, 5 distinct CN signatures were identified. Signature 5 was associated with BRCA1/2 CN loss with features similar to HGSOC HRD signature. Twenty-two percent of potential HRD cases were identified, 35 patients with signature 5, and 8 patients with BRCA1/2 somatic mutations. Signatures 3 and 4 were associated with a high ploidy state, and CCNE1, ERBB2, and MYC amplifications, with mutations in PIK3CA enriched in signature 3. We observed improved overall survival (OS) for patients with signature 2 and worse OS for signatures 1 and 3. Twenty-eight percent of patients had CCNE1 amplification and this subset was enriched with carcinosarcoma histotype. Thirty-four percent of patients, across all histotypes, had ERBB2 amplification and/or HER2 overexpression on IHC, which was associated with worse outcomes. Mutations in PPP2R1A (29%) and FBXW7 (16%) were among the top 5 most common mutations. CONCLUSIONS: sWGS and targeted sequencing identified therapeutic opportunities in 75% of patients with p53abn endometrial cancer. Further research is needed to determine the efficacy of treatments targeting these identified pathways within p53abn endometrial cancers.
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Variaciones en el Número de Copia de ADN , Neoplasias Endometriales , Proteína 7 que Contiene Repeticiones F-Box-WD , Mutación , Proteína p53 Supresora de Tumor , Secuenciación Completa del Genoma , Humanos , Femenino , Neoplasias Endometriales/genética , Neoplasias Endometriales/patología , Neoplasias Endometriales/mortalidad , Neoplasias Endometriales/terapia , Proteína p53 Supresora de Tumor/genética , Proteína 7 que Contiene Repeticiones F-Box-WD/genética , Persona de Mediana Edad , Anciano , Proteína BRCA2/genética , Proteína BRCA1/genética , Pronóstico , Fosfatidilinositol 3-Quinasa Clase I/genética , Ciclina E/genética , Adulto , Ubiquitina-Proteína Ligasas/genética , Biomarcadores de Tumor/genética , Cistadenocarcinoma Seroso/genética , Cistadenocarcinoma Seroso/patología , Cistadenocarcinoma Seroso/mortalidad , Cistadenocarcinoma Seroso/tratamiento farmacológico , Cistadenocarcinoma Seroso/terapia , Anciano de 80 o más Años , Proteínas OncogénicasRESUMEN
We performed a deep proteogenomic analysis of bulk tumor and laser microdissection enriched tumor cell populations from high-grade serous ovarian cancer (HGSOC) tissue specimens spanning a broad spectrum of purity. We identified patients with longer progression-free survival had increased immune-related signatures and validated proteins correlating with tumor-infiltrating lymphocytes in 65 tumors from an independent cohort of HGSOC patients, as well as with overall survival in an additional 126 HGSOC patient cohort. We identified that homologous recombination deficient (HRD) tumors are enriched in pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells are uniquely sensitive to BMI-1 inhibition.
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Survival from ovarian cancer depends on the resection status after primary surgery. We performed genome-wide association analyses for resection status of 7705 ovarian cancer patients, including 4954 with high-grade serous carcinoma (HGSOC), to identify variants associated with residual disease. The most significant association with resection status was observed for rs72845444, upstream of MGMT, in HGSOC (p = 3.9 × 10-8). In gene-based analyses, PPP2R5C was the most strongly associated gene in HGSOC after stage adjustment. In an independent set of 378 ovarian tumours from the AGO-OVAR 11 study, variants near MGMT and PPP2R5C correlated with methylation and transcript levels, and PPP2R5C mRNA levels predicted progression-free survival in patients with residual disease. MGMT encodes a DNA repair enzyme, and PPP2R5C encodes the B56γ subunit of the PP2A tumour suppressor. Our results link heritable variation at these two loci with resection status in HGSOC.
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Clear cell ovarian carcinoma (CCOC) and endometrioid ovarian carcinoma (ENOC) are ovarian carcinoma histotypes, which are both thought to arise from ectopic endometrial (or endometrial-like) cells through an endometriosis intermediate. How the same cell type of origin gives rise to two morphologically and biologically different histotypes has been perplexing, particularly given that recurrent genetic mutations are common to both and present in nonmalignant precursors. We used RNA transcription analysis to show that the expression profiles of CCOC and ENOC resemble those of normal endometrium at secretory and proliferative phases of the menstrual cycle, respectively. DNA methylation at the promoter of the estrogen receptor (ER) gene (ESR1) was enriched in CCOC, which could potentially lock the cells in the secretory state. Compared with normal secretory-type endometrium, CCOC was further defined by increased expression of cysteine and glutathione synthesis pathway genes and downregulation of the iron antiporter, suggesting iron addiction and highlighting ferroptosis as a potential therapeutic target. Overall, these findings suggest that while CCOC and ENOC arise from the same cell type, these histotypes likely originate from different cell states. This "cell state of origin" model may help to explain the presence of histologic and molecular cancer subtypes arising in other organs. SIGNIFICANCE: Two cancer histotypes diverge from a common cell of origin epigenetically locked in different cell states, highlighting the importance of considering cell state to better understand the cell of origin of cancer.
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Adenocarcinoma de Células Claras , Carcinoma Endometrioide , Endometriosis , Neoplasias Ováricas , Femenino , Humanos , Endometriosis/genética , Endometriosis/metabolismo , Neoplasias Ováricas/patología , Carcinoma Endometrioide/genética , Carcinoma Endometrioide/patología , Carcinoma Epitelial de Ovario , Adenocarcinoma de Células Claras/genética , Adenocarcinoma de Células Claras/metabolismo , HierroRESUMEN
Epithelial ovarian cancer (EOC) is a heterogeneous group of malignancies, including high-grade serous ovarian cancer (HGSC). HGSC is often diagnosed at advanced stages and is linked to TP53 variants. While BRCA variants elevate risk, most HGSC cases occur in individuals without known genetic variants, necessitating prevention strategies for people without known high-risk genetic variants. Effective prevention programs are also needed due to the lack of traditional screening options. An emerging primary prevention strategy is opportunistic salpingectomy, which involves removing fallopian tubes during another planned pelvic surgery. Opportunistic salpingectomy offers a safe and cost-effective preventative option that is gaining global adoption. With the publication of the first cohort study of patients who underwent salpingectomy, specifically for cancer prevention, attention has turned to broadening opportunities for salpingectomy in addition to more targeted approaches. Prevention opportunities are promising with increasing adoption of salpingectomy and the increased understanding of the etiology of the distinct histotypes of ovarian cancer. Yet, further research on targeted risk-reducing salpingectomy with thoughtful consideration of equity is necessary to reduce death and suffering from ovarian cancer.
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Neoplasias de las Trompas Uterinas , Neoplasias Ováricas , Humanos , Femenino , Neoplasias de las Trompas Uterinas/patología , Estudios de Cohortes , Neoplasias Ováricas/genética , Neoplasias Ováricas/prevención & control , Neoplasias Ováricas/patología , Trompas Uterinas/patología , SalpingectomíaRESUMEN
OBJECTIVES: Opportunistic salpingectomy (OS) is the removal of fallopian tubes during another pelvic surgery for the purpose of ovarian cancer prevention. Herein, we describe the rates of OS at the time of hysterectomy and tubal sterilization between 2017 and 2020. METHODS: This study uses the Canadian Institute of Health Information's Discharge Abstract Database and National Ambulatory Care Reporting System for all Canadian provinces and territories except for Quebec between the fiscal years 2017 and 2020. A descriptive analysis on all people aged 15 years and older who had hysterectomies or tubal sterilizations was conducted to determine the proportion of hysterectomies that included bilateral salpingectomy (OS) and the proportion of tubal sterilizations that were OS compared to tubal ligation. RESULTS: There were 174 006 people included in the study. The proportion of hysterectomies that included OS increased from 31.7% in 2017 to 39.9% by 2020. With respect to tubal sterilizations, rates of OS increased from 26.3% of all tubal sterilizations in 2017 to 42.5% in 2020. British Columbia remained the jurisdiction with the highest rates of OS, but rates increased significantly in many jurisdictions, particularly at the time of tubal sterilization. CONCLUSION: The rates of OS have continued to increase in all Canadian jurisdictions following the official Society of Obstetricians and Gynaecologists of Canada recommendation to consider OS in 2015. Assuming that all tubal ligations could have been OS and 75% of hysterectomies with ovarian conservation could have included OS, our data indicate 76 932 missed opportunities for ovarian cancer prevention.
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Background: Recent developments in artificial intelligence suggest that radiomics may represent a promising non-invasive biomarker to predict response to immune checkpoint inhibitors (ICIs). Nevertheless, validation of radiomics algorithms in independent cohorts remains a challenge due to variations in image acquisition and reconstruction. Using radiomics, we investigated the importance of scan normalization as part of a broader machine learning framework to enable model external generalizability to predict ICI response in non-small cell lung cancer (NSCLC) patients across different centers. Methods: Radiomics features were extracted and compared from 642 advanced NSCLC patients on pre-ICI scans using established open-source PyRadiomics and a proprietary DeepRadiomics deep learning technology. The population was separated into two groups: a discovery cohort of 512 NSCLC patients from three academic centers and a validation cohort that included 130 NSCLC patients from a fourth center. We harmonized images to account for variations in reconstruction kernel, slice thicknesses, and device manufacturers. Multivariable models, evaluated using cross-validation, were used to estimate the predictive value of clinical variables, PD-L1 expression, and PyRadiomics or DeepRadiomics for progression-free survival at 6 months (PFS-6). Results: The best prognostic factor for PFS-6, excluding radiomics features, was obtained with the combination of Clinical + PD-L1 expression (AUC = 0.66 in the discovery and 0.62 in the validation cohort). Without image harmonization, combining Clinical + PyRadiomics or DeepRadiomics delivered an AUC = 0.69 and 0.69, respectively, in the discovery cohort, but dropped to 0.57 and 0.52, in the validation cohort. This lack of generalizability was consistent with observations in principal component analysis clustered by CT scan parameters. Subsequently, image harmonization eliminated these clusters. The combination of Clinical + DeepRadiomics reached an AUC = 0.67 and 0.63 in the discovery and validation cohort, respectively. Conversely, the combination of Clinical + PyRadiomics failed generalizability validations, with AUC = 0.66 and 0.59. Conclusion: We demonstrated that a risk prediction model combining Clinical + DeepRadiomics was generalizable following CT scan harmonization and machine learning generalization methods. These results had similar performances to routine oncology practice using Clinical + PD-L1. This study supports the strong potential of radiomics as a future non-invasive strategy to predict ICI response in advanced NSCLC.
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DICER1 is an RNase III enzyme essential for miRNA biogenesis through cleaving precursor-miRNA hairpins. Germline loss-of-function DICER1 mutations underline the development of DICER1 syndrome, a rare genetic disorder that predisposes children to cancer development in organs such as lung, gynecologic tract, kidney, and brain. Unlike classical tumor suppressors, the somatic "second hit" in DICER1 syndrome-associated cancers does not fully inactivate DICER1 but impairs its RNase IIIb activity only, suggesting a noncanonical two-hit hypothesis. Here, we developed a genetically engineered conditional compound heterozygous Dicer1 mutant mouse strain that fully recapitulates the biallelic DICER1 mutations in DICER1 syndrome-associated human cancers. Crossing this tool strain with tissue-specific Cre strains that activate Dicer1 mutations in gynecologic tract cells at two distinct developmental stages revealed that embryonic biallelic Dicer1 mutations caused infertility in females by disrupting oviduct and endometrium development and ultimately drove cancer development. These multicystic tubal and intrauterine tumors histologically resembled a subset of DICER1 syndrome-associated human cancers. Molecular analysis uncovered accumulation of additional oncogenic events (e.g., aberrant p53 expression, Kras mutation, and Myc activation) in murine Dicer1 mutant tumors and validated miRNA biogenesis defects in 5P miRNA strand production, of which, loss of let-7 family miRNAs was identified as a putative key player in transcriptomic rewiring and tumor development. Thus, this DICER1 syndrome-associated cancer model recapitulates the biology of human cancer and provides a unique tool for future investigation and therapeutic development. SIGNIFICANCE: Generation of a Dicer1 mutant mouse model establishes the oncogenicity of missense mutations in the DICER1 RNase IIIb domain and provides a faithful model of DICER1 syndrome-associated cancer for further investigation.
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MicroARNs , Síndromes Neoplásicos Hereditarios , Niño , Humanos , Femenino , Animales , Ratones , Ribonucleasa III/genética , Ribonucleasa III/metabolismo , MicroARNs/genética , Mutación , Mutación Missense , ARN Helicasas DEAD-box/genéticaRESUMEN
This study explores household-level evacuation decision-making in response to Hurricane Laura, in a context where hurricane risk reduction measures contradicted COVID-19 risk reduction measures. Data were collected using a mail-based survey approach from households along the coast of Texas and Louisiana to explore drivers of and barriers to evacuation, including COVID-19 measures such as negative affect, risk perceptions, protective actions, and exposure. Testing for direct and indirect effects among the drivers of and barriers to evacuation, we find that many of our COVID-19 measures did not have a direct effect on evacuation but did have indirect effects through other factors. We also found evidence of both direct and indirect relationships with regards to more conventional drivers of evacuation found in the literature. We close with a discussion of the limitations and implications of this study.
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OBJECTIVES: Despite recommendations for integrating molecular classification of endometrial cancers (EC) into pathology reporting and clinical management, uptake is inconsistent. To assign ProMisE subtype, all molecular components must be available (POLE mutation status, mismatch repair (MMR) and p53 immunohistochemistry (IHC)) and often these are assessed at different stages of care and/or at different centres resulting in delays in treatment. We assessed a single-test DNA-based targeted next generation sequencing (NGS) molecular classifier (ProMisE NGS), comparing concordance and prognostic value to the original ProMisE classifier. METHODS: DNA was extracted from formalin-fixed paraffin embedded (FFPE) ECs that had previously undergone ProMisE molecular classification (POLE sequencing, IHC for p53 and MMR). DNA was sequenced using the clinically validated Imagia Canexia Health Find It™ amplicon-based NGS gene panel assay to assess for pathogenic POLE mutations (unchanged from original ProMisE), TP53 mutations (in lieu of p53 IHC), and microsatellite instability (MSI) (in lieu of MMR IHC),with the same order of segregation as original ProMisE used for subtype assignment. Molecular subtype assignment of both classifiers was compared by concordance metrics and Kaplan-Meier survival statistics. RESULTS: The new DNA-based NGS molecular classifier (ProMisE NGS) was used to determine the molecular subtype in 164 ECs previously classified with ProMisE. 159/164 cases were concordant with a kappa statistic of 0.96 and an overall accuracy of 0.97. Prognostic differences in progression-free, disease-specific and overall survival between the four molecular subtypes were observed for the new NGS classifier, recapitulating the survival curves of the original ProMisE classifier. ProMisE NGS was 100% concordant between matched biopsy and hysterectomy samples. CONCLUSION: ProMisE NGS is feasible on standard FFPE material, demonstrates high concordance with the original ProMisE classifier and maintains prognostic value in EC. This test has the potential to facilitate implementation of molecular classification of EC at the time of first diagnosis.
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Neoplasias Endometriales , Proteína p53 Supresora de Tumor , Femenino , Humanos , Proteína p53 Supresora de Tumor/genética , Neoplasias Endometriales/diagnóstico , Neoplasias Endometriales/genética , Neoplasias Endometriales/patología , Pronóstico , Mutación , Secuenciación de Nucleótidos de Alto Rendimiento , Inestabilidad de Microsatélites , Reparación de la Incompatibilidad de ADN/genéticaRESUMEN
SMARCA4 (BRG1) and SMARCA2 (BRM) are the two paralogous ATPases of the SWI/SNF chromatin remodeling complexes frequently inactivated in cancers. Cells deficient in either ATPase have been shown to depend on the remaining counterpart for survival. Contrary to this paralog synthetic lethality, concomitant loss of SMARCA4/2 occurs in a subset of cancers associated with very poor outcomes. Here, we uncover that SMARCA4/2-loss represses expression of the glucose transporter GLUT1, causing reduced glucose uptake and glycolysis accompanied with increased dependency on oxidative phosphorylation (OXPHOS); adapting to this, these SMARCA4/2-deficient cells rely on elevated SLC38A2, an amino acid transporter, to increase glutamine import for fueling OXPHOS. Consequently, SMARCA4/2-deficient cells and tumors are highly sensitive to inhibitors targeting OXPHOS or glutamine metabolism. Furthermore, supplementation of alanine, also imported by SLC38A2, restricts glutamine uptake through competition and selectively induces death in SMARCA4/2-deficient cancer cells. At a clinically relevant dose, alanine supplementation synergizes with OXPHOS inhibition or conventional chemotherapy eliciting marked antitumor activity in patient-derived xenografts. Our findings reveal multiple druggable vulnerabilities of SMARCA4/2-loss exploiting a GLUT1/SLC38A2-mediated metabolic shift. Particularly, unlike dietary deprivation approaches, alanine supplementation can be readily applied to current regimens for better treatment of these aggressive cancers.
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Glutamina , Neoplasias , Humanos , Transportador de Glucosa de Tipo 1 , Adenosina Trifosfatasas/metabolismo , Neoplasias/tratamiento farmacológico , Neoplasias/genética , Suplementos Dietéticos , ADN Helicasas/metabolismo , Proteínas Nucleares/genética , Proteínas Nucleares/metabolismo , Factores de Transcripción/genética , Factores de Transcripción/metabolismoRESUMEN
DICER1 syndrome is a tumor predisposition syndrome that is associated with up to 30 different neoplastic lesions, usually affecting children and adolescents. Here we identify a group of mesenchymal tumors which is highly associated with DICER1 syndrome, and molecularly distinct from other DICER1-associated tumors. This group of DICER1-associated mesenchymal tumors encompasses multiple well-established clinicopathological tumor entities and can be further divided into three clinically meaningful classes designated "low-grade mesenchymal tumor with DICER1 alteration" (LGMT DICER1), "sarcoma with DICER1 alteration" (SARC DICER1), and primary intracranial sarcoma with DICER1 alteration (PIS DICER1). Our study not only provides a combined approach to classify DICER1-associated neoplasms for improved clinical management but also suggests a role for global hypomethylation and other recurrent molecular events in sarcomatous differentiation in mesenchymal tumors with DICER1 alteration. Our results will facilitate future investigations into prognostication and therapeutic approaches for affected patients.
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Síndromes Neoplásicos Hereditarios , Sarcoma , Niño , Adolescente , Humanos , Mutación de Línea Germinal , Sarcoma/genética , Síndromes Neoplásicos Hereditarios/genética , Genómica , Ribonucleasa III/genética , Predisposición Genética a la Enfermedad , Enfermedades Raras , Mutación , ARN Helicasas DEAD-box/genéticaRESUMEN
Abnormal p53 (p53abn) immunohistochemical (IHC) staining patterns can be found in vulvar squamous cell carcinoma (VSCC) and differentiated vulvar intraepithelial neoplasia (dVIN). They can also be found in the adjacent skin that shows morphology that falls short of the traditional diagnostic threshold for dVIN. Vulvectomy specimens containing human papillomavirus-independent p53abn VSCC with margins originally reported as negative for invasive and in situ disease were identified. Sections showing the closest approach by invasive or in situ neoplasia to margins were stained with p53 IHC stains. We evaluated the following: (1) detection of morphologically occult p53abn in situ neoplasia, (2) rates of margin status change after p53 IHC staining, and (3) effect of p53abn IHC staining at margins on the 2-year local recurrence rates. Seventy-three human papillomavirus-independent p53abn VSCCs were included. Half (35/73, 48%) had documented an in situ lesion in the original report. The use of p53 IHC staining identified 21 additional cases (29%) with the p53abn in situ lesions that were originally unrecognized. The histology of in situ lesions in the p53abn "field" varied and became more subtle (morphologically occult) farther away from the VSCC. Fifteen (21%) cases had a morphologically occult and previously unrecognized p53abn in situ lesion present at a resection margin, which conferred an increased risk of local recurrence (5/7 [71.4%] vs 6/22 [27.3%], P = .036). The p53abn in situ lesions at a margin were confirmed to have TP53 mutations by sequencing. p53 IHC staining identified morphologically occult p53abn in situ lesions surrounding human papillomavirus-independent VSCC. p53abn IHC staining at a margin was associated with a 3-fold increased risk of local recurrence.