Ensemble-based classification using microRNA expression identifies a breast cancer patient subgroup with an ultralow long-term risk of metastases.

BACKGROUND: Current clinical markers overestimate the recurrence risk in many lymph node negative (LNN) breast cancer (BC) patients such that a majority of these low-risk patients unnecessarily receive systemic treatments. We tested if differential microRNA expression in primary tumors allows reliable identification of indolent LNN BC patients to provide an improved classification tool for overtreatment reduction in this patient group. METHODS: We collected freshly frozen primary tumors of 80 LNN BC patients with recurrence and 80 recurrence-free patients (mean follow-up: 20.9 years). The study comprises solely systemically untreated patients to exclude that administered treatments confound the metastasis status. Samples were pairwise matched for clinical-pathological characteristics to minimize dependence of current markers. Patients were classified into risk-subgroups according to the differential microRNA expression of their tumors via classification model building with cross-validation using seven classification methods and a voting scheme. The methodology was validated using available data of two independent cohorts (n = 123, n = 339). RESULTS: Of the 80 indolent patients (who would all likely receive systemic treatments today) our ultralow-risk classifier correctly identified 37 while keeping a sensitivity of 100% in the recurrence group. Multivariable logistic regression analysis confirmed independence of voting results from current clinical markers. Application of the method in two validation cohorts confirmed successful classification of ultralow-risk BC patients with significantly prolonged recurrence-free survival. CONCLUSION: Profiles of differential microRNAs expression can identify LNN BC patients who could spare systemic treatments demanded by currently applied classifications. However, further validation studies are required for clinical implementation of the applied methodology.

Comparison of the Metastasis Predictive Potential of mRNA and Long Non-Coding RNA Profiling in Systemically Untreated Breast Cancer.

Several gene expression signatures based on mRNAs and a few based on long non-coding RNAs (lncRNAs) have been developed to provide prognostic information beyond clinical evaluation in breast cancer (BC). However, the comparison of such signatures for predicting recurrence is very scarce. Therefore, we compared the prognostic utility of mRNAs and lncRNAs in low-risk BC patients using two different classification strategies. Frozen primary tumor samples from 160 lymph node negative and systemically untreated BC patients were included; 80 developed recurrence-i.e., regional or distant metastasis while 80 remained recurrence-free (mean follow-up of 20.9 years). Patients were pairwise matched for clinicopathological characteristics. Classification based on differential mRNA or lncRNA expression using seven individual machine learning methods and a voting scheme classified patients into risk-subgroups. Classification by the seven methods with a fixed sensitivity of ≥90% resulted in specificities ranging from 16-40% for mRNA and 38-58% for lncRNA, and after voting, specificities of 38% and 60% respectively. Classifier performance based on an alternative classification approach of balanced accuracy optimization also provided higher specificities for lncRNA than mRNA at comparable sensitivities. Thus, our results suggested that classification followed by voting improved prognostic power using lncRNAs compared to mRNAs regardless of classification strategy.

ZTTK syndrome: Clinical and molecular findings of 15 cases and a review of the literature.

Zhu-Tokita-Takenouchi-Kim (ZTTK) syndrome is caused by de novo loss-of-function variants in the SON gene (MIM #617140). This multisystemic disorder is characterized by intellectual disability, seizures, abnormal brain imaging, variable dysmorphic features, and various congenital anomalies. The wide application and increasing accessibility of whole exome sequencing (WES) has helped to identify new cases of ZTTK syndrome over the last few years. To date, there have been approximately 45 cases reported in the literature. Here, we describe 15 additional individuals with variants in the SON gene, including those with missense variants bringing the total number of known cases to 60. We have reviewed the clinical and molecular data of these new cases and all previously reported cases to further delineate the most common as well as emerging clinical findings related to this syndrome. Furthermore, we aim to delineate any genotype-phenotype correlations specifically for a recurring pathogenic four base pair deletion (c.5753_5756del) along with discussing the impact of missense variants seen in the SON gene.

Novel phenotype of syndromic premature ovarian insufficiency associated with TP63 molecular defect.

There is growing evidence that TP63 is associated with isolated as well as syndromic premature ovarian insufficiency (POI). We report two adolescent sisters diagnosed with undetectable ovaries, uterine hypoplasia, and mammary gland hypoplasia. A novel paternally inherited nonsense variant in TP63 [NM_003722.4 c.1927C > T,p.(Arg643*)] in exon 14 was identified by exome sequencing. One of the syndromes linked to TP63 is limb mammary syndrome (LMS), an autosomal dominant inherited disorder characterized by ectrodactyly, hypoplasia of mammary-gland and nipple, lacrimal duct stenosis, nail dysplasia, dental anomalies, cleft palate and/or cleft lip and absence of skin and hair defects. The TP63 variant segregated with symptoms of LMS in the family, however, no affected individual had limb defects. The phenotype reported here represents a novel syndromic phenotype associated with TP63. Reported cases with TP63 associated POI are reviewed.

De Novo Missense Variants in FBXW11 Cause Diverse Developmental Phenotypes Including Brain, Eye, and Digit Anomalies.

The identification of genetic variants implicated in human developmental disorders has been revolutionized by second-generation sequencing combined with international pooling of cases. Here, we describe seven individuals who have diverse yet overlapping developmental anomalies, and who all have de novo missense FBXW11 variants identified by whole exome or whole genome sequencing and not reported in the gnomAD database. Their phenotypes include striking neurodevelopmental, digital, jaw, and eye anomalies, and in one individual, features resembling Noonan syndrome, a condition caused by dysregulated RAS signaling. FBXW11 encodes an F-box protein, part of the Skp1-cullin-F-box (SCF) ubiquitin ligase complex, involved in ubiquitination and proteasomal degradation and thus fundamental to many protein regulatory processes. FBXW11 targets include ß-catenin and GLI transcription factors, key mediators of Wnt and Hh signaling, respectively, critical to digital, neurological, and eye development. Structural analyses indicate affected residues cluster at the surface of the loops of the substrate-binding domain of FBXW11, and the variants are predicted to destabilize the protein and/or its interactions. In situ hybridization studies on human and zebrafish embryonic tissues demonstrate FBXW11 is expressed in the developing eye, brain, mandibular processes, and limb buds or pectoral fins. Knockdown of the zebrafish FBXW11 orthologs fbxw11a and fbxw11b resulted in embryos with smaller, misshapen, and underdeveloped eyes and abnormal jaw and pectoral fin development. Our findings support the role of FBXW11 in multiple developmental processes, including those involving the brain, eye, digits, and jaw.

Mosaic MECP2 variants in males with classical Rett syndrome features, including stereotypical hand movements.

Rett syndrome is rarely suspected in males because of the X-linked dominant inheritance. In the literature, only six male patients have been reported with methyl-CpG-binding protein 2 (MECP2) mosaicism. Next-generation sequencing (NGS) methods have enabled better detection of somatic mosaicism compared to conventional Sanger sequencing; however, mosaics can still be difficult to detect. We present clinical and molecular findings in two males mosaic for a pathogenic MECP2 variant. Both have been reexamined using deep sequencing of DNA isolated from four different cell tissues (blood, muscle, fibroblasts and oral mucosa). Deep sequencing of the different tissues revealed that the variants were present in all tissues. In one patient, the molecular diagnosis could only be established by reexamination after a normal whole exome sequencing, and the other case is an example of reverse genetic diagnostics. Rett syndrome should be considered in males with neurodevelopmental delay and stereotypical hand movements. Subsequent to clinical diagnosis males should be investigated with NGS-based technologies of MECP2 with high read depth and a low threshold for variant calls. If the initial analysis on full blood derived DNA fails to confirm the suspicion, we recommend repeating the analysis on another tissue, preferentially fibroblasts to increase the diagnostic yield.

Association of miR-548c-5p, miR-7-5p, miR-210-3p, miR-128-3p with recurrence in systemically untreated breast cancer.

Current prognostic markers allocate the majority of lymph node (LN) negative and estrogen receptor (ER) positive breast cancer patients into the high-risk group. Accordingly, most patients receive systemic treatments although approximately 40% of these patients may have been cured by surgery and radiotherapy alone. Two studies identified seven prognostic microRNAs in systemically untreated, LN negative and ER positive breast cancer patients which may allow more precise patient classification. However, six of the seven microRNAs were analyzed in both studies but only found to be prognostic in one study. To validate their prognostic potential, we analyzed microRNA expression in an independent cohort (n = 110) using a pair-matched study design minimizing dependence of classical markers. The expression of hsa-miR-548c-5p was significantly associated with abridged disease-free survival (hazard ratio [HR]:1.96, p = 0.027). Contradicting published results, high hsa-miR-516-3p expression was associated with favorable outcome (HR:0.29, p = 0.0068). The association is probably time-dependent indicating later relapse. Additionally, re-analysis of previously published expression data of two matching cohorts (n = 100, n = 255) supports an association of hsa-miR-128-3p with shortened disease-free survival (HR:2.48, p = 0.0033) and an upregulation of miR-7-5p (p = 0.0038; p = 0.039) and miR-210-3p (p = 0.031) in primary tumors of patients who experienced metastases. Further analysis may verify the prognostic potential of these microRNAs.

De Novo Variants in GRIA4 Lead to Intellectual Disability with or without Seizures and Gait Abnormalities.

Using trio whole-exome sequencing, we have identified de novo heterozygous pathogenic variants in GRIA4 in five unrelated individuals with intellectual disability and other symptoms. GRIA4 encodes an AMPA receptor subunit known as GluR4, which is found on excitatory glutamatergic synapses and is important for learning and memory. Four of the variants are located in the highly conserved SYTANLAAF motif in the transmembrane protein M3, and the fifth is in an extra-cellular domain. Molecular modeling of the altered protein showed that three of the variants in the SYTANLAAF motif orient toward the center of the pore region and most likely lead to disturbance of the gating mechanism. The fourth variant in the SYTANLAAF motif most likely results in reduced permeability. The variant in the extracellular domain potentially interferes with the binding between the monomers. On the basis of clinical information and genetic results, and the fact that other subunits of the AMPA receptor have already been associated with neurodevelopmental disorders, we suggest that pathogenic de novo variants in GRIA4 lead to intellectual disability with or without seizures, gait abnormalities, problems of social behavior, and other variable features.

Long non-coding RNA expression profiles predict metastasis in lymph node-negative breast cancer independently of traditional prognostic markers.

INTRODUCTION: Patients with clinically and pathologically similar breast tumors often have very different outcomes and treatment responses. Current prognostic markers allocate the majority of breast cancer patients to the high-risk group, yielding high sensitivities in expense of specificities below 20%, leading to considerable overtreatment, especially in lymph node-negative patients. Seventy percent would be cured by surgery and radiotherapy alone in this group. Thus, precise and early indicators of metastasis are highly desirable to reduce overtreatment. Previous prognostic RNA-profiling studies have only focused on the protein-coding part of the genome, however the human genome contains thousands of long non-coding RNAs (lncRNAs) and this unexplored field possesses large potential for identification of novel prognostic markers. METHODS: We evaluated lncRNA microarray data from 164 primary breast tumors from adjuvant naïve patients with a mean follow-up of 18 years. Eighty two patients who developed detectable distant metastasis were compared to 82 patients where no metastases were diagnosed. For validation, we determined the prognostic value of the lncRNA profiles by comparing the ability of the profiles to predict metastasis in two additional, previously-published, cohorts. RESULTS: We showed that lncRNA profiles could distinguish metastatic patients from non-metastatic patients with sensitivities above 90% and specificities of 64-65%. Furthermore; classifications were independent of traditional prognostic markers and time to metastasis. CONCLUSIONS: To our knowledge, this is the first study investigating the prognostic potential of lncRNA profiles. Our study suggest that lncRNA profiles provide additional prognostic information and may contribute to the identification of early breast cancer patients eligible for adjuvant therapy, as well as early breast cancer patients that could avoid unnecessary systemic adjuvant therapy. This study emphasizes the potential role of lncRNAs in breast cancer prognosis.

Microarray-based RNA profiling of breast cancer: batch effect removal improves cross-platform consistency.

Microarray is a powerful technique used extensively for gene expression analysis. Different technologies are available, but lack of standardization makes it challenging to compare and integrate data. Furthermore, batch-related biases within datasets are common but often not tackled. We have analyzed the same 234 breast cancers on two different microarray platforms. One dataset contained known batch-effects associated with the fabrication procedure used. The aim was to assess the significance of correcting for systematic batch-effects when integrating data from different platforms. We here demonstrate the importance of detecting batch-effects and how tools, such as ComBat, can be used to successfully overcome such systematic variations in order to unmask essential biological signals. Batch adjustment was found to be particularly valuable in the detection of more delicate differences in gene expression. Furthermore, our results show that prober adjustment is essential for integration of gene expression data obtained from multiple sources. We show that high-variance genes are highly reproducibly expressed across platforms making them particularly well suited as biomarkers and for building gene signatures, exemplified by prediction of estrogen-receptor status and molecular subtypes. In conclusion, the study emphasizes the importance of utilizing proper batch adjustment methods when integrating data across different batches and platforms.

RNA profiling reveals familial aggregation of molecular subtypes in non-BRCA1/2 breast cancer families.

BACKGROUND: In more than 70% of families with a strong history of breast and ovarian cancers, pathogenic mutation in BRCA1 or BRCA2 cannot be identified, even though hereditary factors are expected to be involved. It has been proposed that tumors with similar molecular phenotypes also share similar underlying pathophysiological mechanisms. In the current study, the aim was to investigate if global RNA profiling can be used to identify functional subgroups within breast tumors from families tested negative for BRCA1/2 germline mutations and how these subgroupings relate to different breast cancer patients within the same family. METHODS: In the current study we analyzed a collection of 70 frozen breast tumor biopsies from a total of 58 families by global RNA profiling and promoter methylation analysis. RESULTS: We show that distinct functional subgroupings, similar to the intrinsic molecular breast cancer subtypes, exist among non-BRCA1/2 breast cancers. The distribution of subtypes was markedly different from the distribution found among BRCA1/2 mutation carriers. From 11 breast cancer families, breast tumor biopsies from more than one affected family member were included in the study. Notably, in 8 of these families we found that patients from the same family shared the same tumor subtype, showing a tendency of familial aggregation of tumor subtypes (p-value = 1.7e-3). Using our previously developed BRCA1/2-signatures, we identified 7 non-BRCA1/2 tumors with a BRCA1-like molecular phenotype and provide evidence for epigenetic inactivation of BRCA1 in three of the tumors. In addition, 7 BRCA2-like tumors were found. CONCLUSIONS: Our finding indicates involvement of hereditary factors in non-BRCA1/2 breast cancer families in which family members may carry genetic susceptibility not just to breast cancer but to a particular subtype of breast cancer. This is the first study to provide a biological link between breast cancers from family members of high-risk non-BRCA1/2 families in a systematic manner, suggesting that future genetic analysis may benefit from subgrouping families into molecularly homogeneous subtypes in order to search for new high penetrance susceptibility genes.

Long non-coding RNA HOTAIR is an independent prognostic marker of metastasis in estrogen receptor-positive primary breast cancer.

Expression of HOX transcript antisense intergenic RNA (HOTAIR)--a long non-coding RNA--has been examined in a variety of human cancers, and overexpression of HOTAIR is correlated with poor survival among breast, colon, and liver cancer patients. In this retrospective study, we examine HOTAIR expression in 164 primary breast tumors, from patients who do not receive adjuvant treatment, in a design that is paired with respect to the traditional prognostic markers. We show that HOTAIR expression differs between patients with or without a metastatic endpoint, respectively. Survival analysis shows that high HOTAIR expression in primary tumors is significantly associated with worse prognosis independent of prognostic markers (P = 0.012, hazard ratio (HR) 1.747). This association is even stronger when looking only at estrogen receptor (ER)-positive tumor samples (P = 0.0086, HR 1.985). In ER-negative tumor samples, we are not able to detect a prognostic value of HOTAIR expression, probably due to the limited sample size. These results are successfully validated in an independent dataset with similar associations (P = 0.018, HR 1.825). In conclusion, our findings suggest that HOTAIR expression may serve as an independent biomarker for the prediction of the risk of metastasis in ER-positive breast cancer patients.

Classifications within molecular subtypes enables identification of BRCA1/BRCA2 mutation carriers by RNA tumor profiling.

Pathogenic germline mutations in BRCA1 or BRCA2 are detected in less than one third of families with a strong history of breast cancer. It is therefore expected that mutations still remain undetected by currently used screening methods. In addition, a growing number of BRCA1/2 sequence variants of unclear pathogen significance are found in the families, constituting an increasing clinical challenge. New methods are therefore needed to improve the detection rate and aid the interpretation of the clinically uncertain variants. In this study we analyzed a series of 33 BRCA1, 22 BRCA2, and 128 sporadic tumors by RNA profiling to investigate the classification potential of RNA profiles to predict BRCA1/2 mutation status. We found that breast tumors from BRCA1 and BRCA2 mutation carriers display characteristic RNA expression patterns, allowing them to be distinguished from sporadic tumors. The majority of BRCA1 tumors were basal-like while BRCA2 tumors were mainly luminal B. Using RNA profiles, we were able to distinguish BRCA1 tumors from sporadic tumors among basal-like tumors with 83% accuracy and BRCA2 from sporadic tumors among luminal B tumors with 89% accuracy. Furthermore, subtype-specific BRCA1/2 gene signatures were successfully validated in two independent data sets with high accuracies. Although additional validation studies are required, indication of BRCA1/2 involvement ("BRCAness") by RNA profiling could potentially be valuable as a tool for distinguishing pathogenic mutations from benign variants, for identification of undetected mutation carriers, and for selecting patients sensitive to new therapeutics such as PARP inhibitors.