RESUMEN
Triple-negative breast cancers (TNBCs) are a subset of breast cancers that have remained difficult to treat. A proportion of TNBCs arising in non-carriers of BRCA pathogenic variants have genomic features that are similar to BRCA carriers and may also benefit from PARP inhibitor treatment. Using genomic data from 129 TNBC samples from the Malaysian Breast Cancer (MyBrCa) cohort, we developed a gene expression-based machine learning classifier for homologous recombination deficiency (HRD) in TNBCs. The classifier identified samples with HRD mutational signature at an AUROC of 0.93 in MyBrCa validation datasets and 0.84 in TCGA TNBCs. Additionally, the classifier strongly segregated HRD-associated genomic features in TNBCs from TCGA, METABRIC, and ICGC. Thus, our gene expression classifier may identify triple-negative breast cancer patients with homologous recombination deficiency, suggesting an alternative method to identify individuals who may benefit from treatment with PARP inhibitors or platinum chemotherapy.
RESUMEN
B cells and T cells are important components of the adaptive immune system and mediate anticancer immunity. The T cell landscape in cancer is well characterized, but the contribution of B cells to anticancer immunosurveillance is less well explored. Here we show an integrative analysis of the B cell and T cell receptor repertoire from individuals with metastatic breast cancer and individuals with early breast cancer during neoadjuvant therapy. Using immune receptor, RNA and whole-exome sequencing, we show that both B cell and T cell responses seem to coevolve with the metastatic cancer genomes and mirror tumor mutational and neoantigen architecture. B cell clones associated with metastatic immunosurveillance and temporal persistence were more expanded and distinct from site-specific clones. B cell clonal immunosurveillance and temporal persistence are predictable from the clonal structure, with higher-centrality B cell antigen receptors more likely to be detected across multiple metastases or across time. This predictability was generalizable across other immune-mediated disorders. This work lays a foundation for prioritizing antibody sequences for therapeutic targeting in cancer.
Asunto(s)
Linfocitos B , Neoplasias de la Mama , Vigilancia Inmunológica , Humanos , Femenino , Neoplasias de la Mama/inmunología , Linfocitos B/inmunología , Receptores de Antígenos de Linfocitos T/genética , Receptores de Antígenos de Linfocitos T/inmunología , Receptores de Antígenos de Linfocitos T/metabolismo , Receptores de Antígenos de Linfocitos B/metabolismo , Receptores de Antígenos de Linfocitos B/genética , Receptores de Antígenos de Linfocitos B/inmunología , Linfocitos T/inmunología , Monitorización Inmunológica , Secuenciación del Exoma , Antígenos de Neoplasias/inmunología , Metástasis de la Neoplasia , Células ClonalesRESUMEN
The Integrative Cluster subtypes (IntClusts) provide a framework for the classification of breast cancer tumors into 10 distinct groups based on copy number and gene expression, each with unique biological drivers of disease and clinical prognoses. Gene expression data is often lacking, and accurate classification of samples into IntClusts with copy number data alone is essential. Current classification methods achieve low accuracy when gene expression data are absent, warranting the development of new approaches to IntClust classification. Copy number data from 1980 breast cancer samples from METABRIC was used to train multiclass XGBoost machine learning algorithms (CopyClust). A piecewise constant fit was applied to the average copy number profile of each IntClust and unique breakpoints across the 10 profiles were identified and converted into ~ 500 genomic regions used as features for CopyClust. These models consisted of two approaches: a 10-class model with the final IntClust label predicted by a single multiclass model and a 6-class model with binary reclassification in which four pairs of IntClusts were combined for initial multiclass classification. Performance was validated on the TCGA dataset, with copy number data generated from both SNP arrays and WES platforms. CopyClust achieved 81% and 79% overall accuracy with the TCGA SNP and WES datasets, respectively, a nine-percentage point or greater improvement in overall IntClust subtype classification accuracy. CopyClust achieves a significant improvement over current methods in classification accuracy of IntClust subtypes for samples without available gene expression data and is an easily implementable algorithm for IntClust classification of breast cancer samples with copy number data.
Asunto(s)
Algoritmos , Neoplasias de la Mama , Variaciones en el Número de Copia de ADN , Aprendizaje Automático , Humanos , Neoplasias de la Mama/genética , Neoplasias de la Mama/clasificación , Femenino , Variaciones en el Número de Copia de ADN/genética , Análisis por Conglomerados , Perfilación de la Expresión Génica/métodosRESUMEN
Breast cancer exhibits significant heterogeneity, manifesting in various subtypes that are critical in guiding treatment decisions. This study aimed to investigate the existence of distinct subtypes of breast cancer within the Asian population, by analysing the transcriptomic profiles of 934 breast cancer patients from a Malaysian cohort. Our findings reveal that the HR + /HER2- breast cancer samples display a distinct clustering pattern based on immune phenotypes, rather than conforming to the conventional luminal A-luminal B paradigm previously reported in breast cancers from women of European descent. This suggests that the activation of the immune system may play a more important role in Asian HR + /HER2- breast cancer than has been previously recognized. Analysis of somatic mutations by whole exome sequencing showed that counter-intuitively, the cluster of HR + /HER2- samples exhibiting higher immune scores was associated with lower tumour mutational burden, lower homologous recombination deficiency scores, and fewer copy number aberrations, implicating the involvement of non-canonical tumour immune pathways. Further investigations are warranted to determine the underlying mechanisms of these pathways, with the potential to develop innovative immunotherapeutic approaches tailored to this specific patient population.
Asunto(s)
Neoplasias de la Mama , Mutación , Fenotipo , Receptor ErbB-2 , Adulto , Anciano , Femenino , Humanos , Persona de Mediana Edad , Pueblo Asiatico/genética , Biomarcadores de Tumor/genética , Neoplasias de la Mama/genética , Neoplasias de la Mama/inmunología , Neoplasias de la Mama/patología , Análisis por Conglomerados , Estudios de Cohortes , Variaciones en el Número de Copia de ADN , Secuenciación del Exoma , Perfilación de la Expresión Génica , Malasia/epidemiología , Receptor ErbB-2/genética , Receptor ErbB-2/metabolismo , Receptores de Estrógenos/metabolismo , Receptores de Estrógenos/genética , Receptores de Progesterona/metabolismo , Receptores de Progesterona/genética , TranscriptomaRESUMEN
INTRODUCTION: Translation of genome-wide association study (GWAS) ï¬ndings into preventive approaches is challenged by the identification of the causal risk variants and the understanding of the biological mechanisms by which they act. We present using allelic expression (AE) ratios to perform quantitative case-control analysis as a novel approach to identify risk associations, causal regulatory variants, and target genes. METHODS: Using the breast cancer (BC) risk locus 17q22 to validate this approach, we measured AE ratios in normal breast tissue samples from controls and cases, as well as from unmatched blood samples. Then we used in-silico and in-vitro analysis to map and functionally characterised candidate causal variants. RESULTS: We found a significant shift in the AE patterns of STXBP4 (rs2628315) and COX11 (rs17817901) in the normal breast tissue of cases and healthy controls. Preferential expression of the G-rs2628315 and A-rs17817901 alleles, more often observed in cases, was associated with an increased risk for BC. Analysis of blood samples from cases and controls found a similar association. Furthermore, we identified two putative cis-regulatory variants - rs17817901 and rs8066588 - that affect a miRNA and a transcription factor binding site, respectively. CONCLUSION: We propose causal variants and target genes for the 17q22 BC risk locus and show that using AE ratios in case-control association studies is helpful in identifying risk and mapping causal variants.
Asunto(s)
Neoplasias de la Mama , Estudio de Asociación del Genoma Completo , Alelos , Neoplasias de la Mama/genética , Proteínas Transportadoras de Cobre , Proteínas del Complejo de Cadena de Transporte de Electrón , Femenino , Predisposición Genética a la Enfermedad , Células Germinativas , Humanos , Proteínas Mitocondriales , Polimorfismo de Nucleótido Simple , Sitios de Carácter Cuantitativo , Proteínas de Transporte Vesicular/genéticaRESUMEN
PIK3CA mutations are the most common in breast cancer, particularly in the estrogen receptor-positive cohort, but the benefit of PI3K inhibitors has had limited success compared with approaches targeting other less common mutations. We found a frequent allelic expression imbalance between the missense mutant and wild-type PIK3CA alleles in breast tumors from the METABRIC (70.2%) and the TCGA (60.1%) projects. When considering the mechanisms controlling allelic expression, 27.7% and 11.8% of tumors showed imbalance due to regulatory variants in cis, in the two studies respectively. Furthermore, preferential expression of the mutant allele due to cis-regulatory variation is associated with poor prognosis in the METABRIC tumors (P = 0.031). Interestingly, ER-, PR-, and HER2+ tumors showed significant preferential expression of the mutated allele in both datasets. Our work provides compelling evidence to support the clinical utility of PIK3CA allelic expression in breast cancer in identifying patients of poorer prognosis, and those with low expression of the mutated allele, who will unlikely benefit from PI3K inhibitors. Furthermore, our work proposes a model of differential regulation of a critical cancer-promoting gene in breast cancer.
RESUMEN
The functions of the tumor microenvironment (TME) are orchestrated by precise spatial organization of specialized cells, yet little is known about the multicellular structures that form within the TME. Here we systematically mapped TME structures in situ using imaging mass cytometry and multitiered spatial analysis of 693 breast tumors linked to genomic and clinical data. We identified ten recurrent TME structures that varied by vascular content, stromal quiescence versus activation, and leukocyte composition. These TME structures had distinct enrichment patterns among breast cancer subtypes, and some were associated with genomic profiles indicative of immune escape. Regulatory and dysfunctional T cells co-occurred in large 'suppressed expansion' structures. These structures were characterized by high cellular diversity, proliferating cells and enrichment for BRCA1 and CASP8 mutations and predicted poor outcome in estrogen-receptor-positive disease. The multicellular structures revealed here link conserved spatial organization to local TME function and could improve patient stratification.
Asunto(s)
Neoplasias de la Mama , Microambiente Tumoral , Neoplasias de la Mama/patología , Femenino , Genoma , Genómica , Humanos , Microambiente Tumoral/genéticaRESUMEN
Breast cancers are complex ecosystems of malignant cells and the tumour microenvironment1. The composition of these tumour ecosystems and interactions within them contribute to responses to cytotoxic therapy2. Efforts to build response predictors have not incorporated this knowledge. We collected clinical, digital pathology, genomic and transcriptomic profiles of pre-treatment biopsies of breast tumours from 168 patients treated with chemotherapy with or without HER2 (encoded by ERBB2)-targeted therapy before surgery. Pathology end points (complete response or residual disease) at surgery3 were then correlated with multi-omic features in these diagnostic biopsies. Here we show that response to treatment is modulated by the pre-treated tumour ecosystem, and its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T cell dysfunction and exclusion. Combining these features into a multi-omic machine learning model predicted a pathological complete response in an external validation cohort (75 patients) with an area under the curve of 0.87. In conclusion, response to therapy is determined by the baseline characteristics of the totality of the tumour ecosystem captured through data integration and machine learning. This approach could be used to develop predictors for other cancers.
Asunto(s)
Neoplasias de la Mama , Ecosistema , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/genética , Femenino , Genómica , Humanos , Aprendizaje Automático , Terapia Neoadyuvante , Microambiente TumoralRESUMEN
Hyperpolarized 13C-MRI is an emerging tool for probing tissue metabolism by measuring 13C-label exchange between intravenously injected hyperpolarized [1-13C]pyruvate and endogenous tissue lactate. Here, we demonstrate that hyperpolarized 13C-MRI can be used to detect early response to neoadjuvant therapy in breast cancer. Seven patients underwent multiparametric 1H-MRI and hyperpolarized 13C-MRI before and 7-11 days after commencing treatment. An increase in the lactate-to-pyruvate ratio of approximately 20% identified three patients who, following 5-6 cycles of treatment, showed pathological complete response. This ratio correlated with gene expression of the pyruvate transporter MCT1 and lactate dehydrogenase A (LDHA), the enzyme catalyzing label exchange between pyruvate and lactate. Analysis of approximately 2,000 breast tumors showed that overexpression of LDHA and the hypoxia marker CAIX was associated with reduced relapse-free and overall survival. Hyperpolarized 13C-MRI represents a promising method for monitoring very early treatment response in breast cancer and has demonstrated prognostic potential. SIGNIFICANCE: Hyperpolarized carbon-13 MRI allows response assessment in patients with breast cancer after 7-11 days of neoadjuvant chemotherapy and outperformed state-of-the-art and research quantitative proton MRI techniques.
Asunto(s)
Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Neoplasias de la Mama/patología , Isótopos de Carbono/análisis , Imagen por Resonancia Magnética/métodos , Terapia Neoadyuvante/métodos , Recurrencia Local de Neoplasia/patología , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/metabolismo , Femenino , Estudios de Seguimiento , Humanos , Recurrencia Local de Neoplasia/tratamiento farmacológico , Recurrencia Local de Neoplasia/metabolismo , Pronóstico , Tasa de SupervivenciaRESUMEN
DNA methylation is aberrant in cancer, but the dynamics, regulatory role and clinical implications of such epigenetic changes are still poorly understood. Here, reduced representation bisulfite sequencing (RRBS) profiles of 1538 breast tumors and 244 normal breast tissues from the METABRIC cohort are reported, facilitating detailed analysis of DNA methylation within a rich context of genomic, transcriptional, and clinical data. Tumor methylation from immune and stromal signatures are deconvoluted leading to the discovery of a tumor replication-linked clock with genome-wide methylation loss in non-CpG island sites. Unexpectedly, methylation in most tumor CpG islands follows two replication-independent processes of gain (MG) or loss (ML) that we term epigenomic instability. Epigenomic instability is correlated with tumor grade and stage, TP53 mutations and poorer prognosis. After controlling for these global trans-acting trends, as well as for X-linked dosage compensation effects, cis-specific methylation and expression correlations are uncovered at hundreds of promoters and over a thousand distal elements. Some of these targeted known tumor suppressors and oncogenes. In conclusion, this study demonstrates that global epigenetic instability can erode cancer methylomes and expose them to localized methylation aberrations in-cis resulting in transcriptional changes seen in tumors.
Asunto(s)
Neoplasias de la Mama/genética , Metilación de ADN , Epigénesis Genética , Epigenómica/métodos , Regulación Neoplásica de la Expresión Génica , Estudios de Cohortes , Islas de CpG/genética , Replicación del ADN/genética , Femenino , Genoma Humano/genética , Inestabilidad Genómica/genética , Genómica/métodos , Humanos , Células MCF-7 , Mutación , Regiones Promotoras Genéticas/genética , Análisis de SupervivenciaRESUMEN
The biology of breast cancer response to neoadjuvant therapy is underrepresented in the literature and provides a window-of-opportunity to explore the genomic and microenvironment modulation of tumours exposed to therapy. Here, we characterised the mutational, gene expression, pathway enrichment and tumour-infiltrating lymphocytes (TILs) dynamics across different timepoints of 35 HER2-negative primary breast cancer patients receiving neoadjuvant eribulin therapy (SOLTI-1007 NEOERIBULIN-NCT01669252). Whole-exome data (N = 88 samples) generated mutational profiles and candidate neoantigens and were analysed along with RNA-Nanostring 545-gene expression (N = 96 samples) and stromal TILs (N = 105 samples). Tumour mutation burden varied across patients at baseline but not across the sampling timepoints for each patient. Mutational signatures were not always conserved across tumours. There was a trend towards higher odds of response and less hazard to relapse when the percentage of subclonal mutations was low, suggesting that more homogenous tumours might have better responses to neoadjuvant therapy. Few driver mutations (5.1%) generated putative neoantigens. Mutation and neoantigen load were positively correlated (R2 = 0.94, p = <0.001); neoantigen load was weakly correlated with stromal TILs (R2 = 0.16, p = 0.02). An enrichment in pathways linked to immune infiltration and reduced programmed cell death expression were seen after 12 weeks of eribulin in good responders. VEGF was downregulated over time in the good responder group and FABP5, an inductor of epithelial mesenchymal transition (EMT), was upregulated in cases that recurred (p < 0.05). Mutational heterogeneity, subclonal architecture and the improvement of immune microenvironment along with remodelling of hypoxia and EMT may influence the response to neoadjuvant treatment.
RESUMEN
Rare protein-truncating variants (PTVs) in PALB2 confer increased risk to breast cancer, but relatively few studies have reported the characteristics of tumours with PALB2 PTVs. In this study, we describe molecular characteristics of tumours with either germline or somatic alterations in PALB2. DNA from fresh frozen tumour tissues and matched peripheral blood lymphocytes for 560 breast cancer patients was subjected for whole-exome sequencing (WES), and RNA from tumour tissues was subjected to RNA sequencing (RNA-seq). We found six cases with germline and three with somatic protein-truncating variants in PALB2. The characteristics of tumours in patients with PALB2 PTVs were similar to those with BRCA1 and BRCA2 PTVs, having significantly more somatic alterations, and a high proportion of the mutational signature and genomic scar scores characteristic of deficiencies in homologous recombination (HR), compared to tumours arising in non-carriers. Unlike tumours arising in patients with BRCA1 and BRCA2 PTVs, PALB2 tumours did not have high prevalence of TP53 somatic alterations or an enriched immune microenvironment. In summary, PALB2 tumours show the homologous recombination deficiencies characteristic of BRCA1 and BRCA2 tumours, and highlight the potential clinical relevance of PALB2 mutational status in guiding therapeutic choices.
RESUMEN
The heterogeneity of breast cancer plays a major role in drug response and resistance and has been extensively characterized at the genomic level. Here, a single-cell breast cancer mass cytometry (BCMC) panel is optimized to identify cell phenotypes and their oncogenic signalling states in a biobank of patient-derived tumour xenograft (PDTX) models representing the diversity of human breast cancer. The BCMC panel identifies 13 cellular phenotypes (11 human and 2 murine), associated with both breast cancer subtypes and specific genomic features. Pre-treatment cellular phenotypic composition is a determinant of response to anticancer therapies. Single-cell profiling also reveals drug-induced cellular phenotypic dynamics, unravelling previously unnoticed intra-tumour response diversity. The comprehensive view of the landscapes of cellular phenotypic heterogeneity in PDTXs uncovered by the BCMC panel, which is mirrored in primary human tumours, has profound implications for understanding and predicting therapy response and resistance.
Asunto(s)
Benzamidas/farmacología , Neoplasias de la Mama/tratamiento farmacológico , Xenoinjertos/efectos de los fármacos , Morfolinas/farmacología , Piperazinas/farmacología , Piridinas/farmacología , Pirimidinas/farmacología , Ensayos Antitumor por Modelo de Xenoinjerto/métodos , Animales , Neoplasias de la Mama/genética , Neoplasias de la Mama/metabolismo , Línea Celular Tumoral , Resistencia a Antineoplásicos/efectos de los fármacos , Resistencia a Antineoplásicos/genética , Femenino , Xenoinjertos/metabolismo , Humanos , Células MCF-7 , Ratones Endogámicos NOD , Ratones Noqueados , Ratones SCID , Inhibidores de Proteínas Quinasas/farmacología , Resultado del TratamientoRESUMEN
A 30-kb deletion that eliminates the coding region of APOBEC3B (A3B) is >5 times more common in women of Asian descent compared to European descent. This polymorphism creates a chimera with the APOBEC3A (A3A) coding region and A3B 3'UTR, and it is associated with an increased risk for breast cancer in Asian women. Here, we explored the relationship between the A3B deletion polymorphism with tumour characteristics in Asian women. Using whole exome and whole transcriptome sequencing data of 527 breast tumours, we report that germline A3B deletion polymorphism leads to expression of the A3A-B hybrid isoform and increased APOBEC-associated somatic hypermutation. Hypermutated tumours, regardless of A3B germline status, were associated with the Her2 molecular subtype and PIK3CA mutations. Compared to nonhypermutated tumours, hypermutated tumours also had higher neoantigen burden, tumour heterogeneity and immune activation. Taken together, our results suggest that the germline A3B deletion polymorphism, via the A3A-B hybrid isoform, contributes to APOBEC mutagenesis in a significant proportion of Asian breast cancers. In addition, APOBEC somatic hypermutation, regardless of A3B background, may be an important clinical biomarker for Asian breast cancers.
RESUMEN
BACKGROUND: NRG1 gene fusions may be clinically actionable, since cancers carrying the fusion transcripts can be sensitive to tyrosine kinase inhibitors. The NRG1 gene encodes ligands for the HER2(ERBB2)-ERBB3 heterodimeric receptor tyrosine kinase, and the gene fusions are thought to lead to autocrine stimulation of the receptor. The NRG1 fusion expressed in the breast cancer cell line MDA-MB-175 serves as a model example of such fusions, showing the proposed autocrine loop and exceptional drug sensitivity. However, its structure has not been properly characterised, its oncogenic activity has not been fully explained, and there is limited data on such fusions in breast cancer. METHODS: We analysed genomic rearrangements and transcripts of NRG1 in MDA-MB-175 and a panel of 571 breast cancers. RESULTS: We found that the MDA-MB-175 fusion-originally reported as a DOC4(TENM4)-NRG1 fusion, lacking the cytoplasmic tail of NRG1-is in reality a double fusion, PPP6R3-TENM4-NRG1, producing multiple transcripts, some of which include the cytoplasmic tail. We hypothesise that many NRG1 fusions may be oncogenic not for lacking the cytoplasmic domain but because they do not encode NRG1's nuclear-localised form. The fusion in MDA-MB-175 is the result of a very complex genomic rearrangement, which we partially characterised, that creates additional expressed gene fusions, RSF1-TENM4, TPCN2-RSF1, and MRPL48-GAB2. We searched for NRG1 rearrangements in 571 breast cancers subjected to genome sequencing and transcriptome sequencing and found four cases (0.7%) with fusions, WRN-NRG1, FAM91A1-NRG1, ARHGEF39-NRG1, and ZNF704-NRG1, all splicing into NRG1 at the same exon as in MDA-MB-175. However, the WRN-NRG1 and ARHGEF39-NRG1 fusions were out of frame. We identified rearrangements of NRG1 in many more (8% of) cases that seemed more likely to inactivate than to create activating fusions, or whose outcome could not be predicted because they were complex, or both. This is not surprising because NRG1 can be pro-apoptotic and is inactivated in some breast cancers. CONCLUSIONS: Our results highlight the complexity of rearrangements of NRG1 in breast cancers and confirm that some do not activate but inactivate. Careful interpretation of NRG1 rearrangements will therefore be necessary for appropriate patient management.
Asunto(s)
Biomarcadores de Tumor , Neoplasias de la Mama/genética , Neurregulina-1/genética , Proteínas de Fusión Oncogénica/genética , Empalme Alternativo , Neoplasias de la Mama/metabolismo , Neoplasias de la Mama/patología , Línea Celular Tumoral , Femenino , Regulación Neoplásica de la Expresión Génica , Reordenamiento Génico , Sitios Genéticos , Humanos , Neurregulina-1/química , Neurregulina-1/metabolismo , Proteínas de Fusión Oncogénica/metabolismo , Transducción de Señal , Translocación GenéticaRESUMEN
Molecular profiling of breast cancer has enabled the development of more robust molecular prognostic signatures and therapeutic options for breast cancer patients. However, non-Caucasian populations remain understudied. Here, we present the mutational, transcriptional, and copy number profiles of 560 Malaysian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to breast tumours in Caucasian women, we show an increased prevalence of HER2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. We also observe elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst HER2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.
Asunto(s)
Pueblo Asiatico/genética , Neoplasias de la Mama/genética , Genética de Población , Neoplasias de la Mama/inmunología , Neoplasias de la Mama/patología , Femenino , Genoma Humano , Humanos , Mutación/genética , Receptor ErbB-2/genética , Receptor ErbB-2/metabolismo , Receptores de Estrógenos/metabolismo , Análisis de Supervivencia , Microambiente Tumoral/inmunología , Proteína p53 Supresora de Tumor/genética , Población Blanca/genéticaRESUMEN
As the catalog of oncogenic driver mutations is expanding, it becomes clear that alterations in a given gene might have different functions and should not be lumped into one class. The transcription factor GATA3 is a paradigm of this. We investigated the functions of the most common GATA3 mutation (X308_Splice) and five additional mutations, which converge into a neoprotein that we called "neoGATA3," associated with excellent prognosis in patients. Analysis of available molecular data from >3000 breast cancer patients revealed a dysregulation of the ER-dependent transcriptional response in tumors carrying neoGATA3-generating mutations. Mechanistic studies in vitro showed that neoGATA3 interferes with the transcriptional programs controlled by estrogen and progesterone receptors, without fully abrogating them. ChIP-Seq analysis indicated that ER binding is reduced in neoGATA3-expressing cells, especially at distal regions, suggesting that neoGATA3 interferes with the fine tuning of ER-dependent gene expression. This has opposite outputs in distinct hormonal context, having pro- or anti-proliferative effects, depending on the estrogen/progesterone ratio. Our data call for functional analyses of putative cancer drivers to guide clinical application.
Asunto(s)
Neoplasias de la Mama/genética , Factor de Transcripción GATA3/genética , Neoplasias de la Mama/inmunología , Neoplasias de la Mama/metabolismo , Neoplasias de la Mama/patología , Ciclo Celular/fisiología , Femenino , Factor de Transcripción GATA3/inmunología , Factor de Transcripción GATA3/metabolismo , Humanos , Mutación , Oncogenes , Empalme del ARN , ARN Mensajero/genética , ARN Mensajero/inmunología , ARN Mensajero/metabolismo , Receptores de Estrógenos/inmunología , Receptores de Estrógenos/metabolismo , Receptores de Progesterona/inmunología , Receptores de Progesterona/metabolismo , Linfocitos T/inmunología , Linfocitos T/patologíaRESUMEN
TP53 gene mutations are very common in human cancer. While such mutations abrogate the tumor suppressive activities of the wild-type (wt) p53 protein, some of them also endow the mutant (mut) protein with oncogenic gain of function (GOF), facilitating cancer progression. Yet, p53 may acquire altered functionality even without being mutated; in particular, experiments with cultured cells revealed that wtp53 can be rewired to adopt mut-like features in response to growth factors or cancer-mimicking genetic manipulations. To assess whether such rewiring also occurs in human tumors, we interrogated gene expression profiles and pathway deregulation patterns in the METABRIC breast cancer (BC) dataset as a function of TP53 gene mutation status. Harnessing the power of machine learning, we optimized a gene expression classifier for ER+Her2- patients that distinguishes tumors carrying TP53 mutations from those retaining wt TP53. Interestingly, a small subset of wt TP53 tumors displayed gene expression and pathway deregulation patterns markedly similar to those of TP53-mutated tumors. Moreover, similar to TP53-mutated tumors, these 'pseudomutant' cases displayed a signature for enhanced proliferation and had worse prognosis than typical wtp53 tumors. Notably, these tumors revealed upregulation of genes which, in BC cell lines, were reported to be positively regulated by p53 GOF mutants. Thus, such tumors may benefit from mut p53-associated activities without having to accrue TP53 mutations.
Asunto(s)
Neoplasias de la Mama/genética , Perfilación de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Proteínas Mutantes/genética , Proteína p53 Supresora de Tumor/genética , Femenino , Humanos , Antígeno Ki-67/metabolismo , Proteínas Mutantes/metabolismo , Mutación/genética , Receptor ErbB-2/metabolismo , Receptores de Estrógenos/metabolismoRESUMEN
Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships1,2. Here we present a human 'all-by-all' reference interactome map of human binary protein interactions, or 'HuRI'. With approximately 53,000 protein-protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome3, transcriptome4 and proteome5 data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein-protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes.
Asunto(s)
Proteoma/metabolismo , Espacio Extracelular/metabolismo , Humanos , Especificidad de Órganos , Mapeo de Interacción de ProteínasRESUMEN
Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.