Integrating imaging and genomic data for the discovery of distinct glioblastoma subtypes: a joint learning approach.

Glioblastoma is a highly heterogeneous disease, with variations observed at both phenotypical and molecular levels. Personalized therapies would be facilitated by non-invasive in vivo approaches for characterizing this heterogeneity. In this study, we developed unsupervised joint machine learning between radiomic and genomic data, thereby identifying distinct glioblastoma subtypes. A retrospective cohort of 571 IDH-wildtype glioblastoma patients were included in the study, and pre-operative multi-parametric MRI scans and targeted next-generation sequencing (NGS) data were collected. L21-norm minimization was used to select a subset of 12 radiomic features from the MRI scans, and 13 key driver genes from the five main signal pathways most affected in glioblastoma were selected from the genomic data. Subtypes were identified using a joint learning approach called Anchor-based Partial Multi-modal Clustering on both radiomic and genomic modalities. Kaplan-Meier analysis identified three distinct glioblastoma subtypes: high-risk, medium-risk, and low-risk, based on overall survival outcome (p < 0.05, log-rank test; Hazard Ratio = 1.64, 95% CI 1.17-2.31, Cox proportional hazard model on high-risk and low-risk subtypes). The three subtypes displayed different phenotypical and molecular characteristics in terms of imaging histogram, co-occurrence of genes, and correlation between the two modalities. Our findings demonstrate the synergistic value of integrated radiomic signatures and molecular characteristics for glioblastoma subtyping. Joint learning on both modalities can aid in better understanding the molecular basis of phenotypical signatures of glioblastoma, and provide insights into the biological underpinnings of tumor formation and progression.

Clinical measures, radiomics, and genomics offer synergistic value in AI-based prediction of overall survival in patients with glioblastoma.

Multi-omic data, i.e., clinical measures, radiomic, and genetic data, capture multi-faceted tumor characteristics, contributing to a comprehensive patient risk assessment. Here, we investigate the additive value and independent reproducibility of integrated diagnostics in prediction of overall survival (OS) in isocitrate dehydrogenase (IDH)-wildtype GBM patients, by combining conventional and deep learning methods. Conventional radiomics and deep learning features were extracted from pre-operative multi-parametric MRI of 516 GBM patients. Support vector machine (SVM) classifiers were trained on the radiomic features in the discovery cohort (n = 404) to categorize patient groups of high-risk (OS < 6 months) vs all, and low-risk (OS ≥ 18 months) vs all. The trained radiomic model was independently tested in the replication cohort (n = 112) and a patient-wise survival prediction index was produced. Multivariate Cox-PH models were generated for the replication cohort, first based on clinical measures solely, and then by layering on radiomics and molecular information. Evaluation of the high-risk and low-risk classifiers in the discovery/replication cohorts revealed area under the ROC curves (AUCs) of 0.78 (95% CI 0.70-0.85)/0.75 (95% CI 0.64-0.79) and 0.75 (95% CI 0.65-0.84)/0.63 (95% CI 0.52-0.71), respectively. Cox-PH modeling showed a concordance index of 0.65 (95% CI 0.6-0.7) for clinical data improving to 0.75 (95% CI 0.72-0.79) for the combination of all omics. This study signifies the value of integrated diagnostics for improved prediction of OS in GBM.

Effects of systemic inflammation on relapse in early breast cancer.

Chronic inflammation has been a proposed mechanism of resistance to aromatase inhibitors in breast cancer. Stratifying by HER2 status, a matched case-control study from the Wellness After Breast Cancer-II cohort was performed to assess whether or not elevated serum inflammatory biomarkers (C-Reactive protein [CRP], interleukin-6 [IL-6], and serum amyloid A [SAA]) and/or the presence of a high-risk IL-6 promoter genotype were associated with recurrence of hormone receptor positive (HR+) early breast cancer. Estrogen levels were also measured and correlated with biomarkers and disease outcomes. CRP and SAA were significantly associated with an increased risk of recurrence in the HR+/HER2- group, but not the HR+/HER2+ group. Mean serum estrogen levels were non-significantly elevated in patients who relapsed vs. non-relapsed patients. Surprisingly, high-risk IL-6 promoter polymorphisms were strongly associated with HER2+ breast cancer relapse, which has potential therapeutic implications, as elevated intracellular IL-6 has been associated with trastuzumab resistance in pre-clinical models.

Molecular diagnosis of somatic overgrowth conditions: A single-center experience.

BACKGROUND: Somatic overgrowth conditions, including Proteus syndrome, Sturge-Weber syndrome, and PIK3CA-related overgrowth spectrum, are caused by post-zygotic pathogenic variants, result in segmental mosaicism, and give rise to neural, cutaneous and/or lipomatous overgrowth. These variants occur in growth-promoting pathways leading to cellular proliferation and expansion of tissues that arise from the affected cellular lineage. METHODS: We report on 80 serial patients evaluated for somatic overgrowth conditions in a diagnostic laboratory setting, including three prenatal patients. In total, 166 tissues from these 80 patients were subjected to targeted sequencing of an 8-gene panel capturing 10.2 kb of sequence containing known pathogenic variants associated with somatic overgrowth conditions. Deep next-generation sequencing was performed with the IonTorrent PGM platform at an average depth typically >5,000×. RESULTS: Likely pathogenic or pathogenic variants were identified in 36 individuals and variants of unknown significance in four. The overall molecular diagnostic yield was 45% but was highly influenced by both submitted tissue type and phenotype. In the prenatal setting, two patients had pathogenic variants identified in cultured amniocytes but in a third patient, the pathogenic variant was only present in post-natal tissues. Finally, expanding the test to include full gene sequencing of PIK3CA in contrast to targeted sequencing identified likely pathogenic variants in 3 of 7 patients that tested negative on the original panel. CONCLUSION: Next-generation sequencing has enabled sensitive detection of somatic pathogenic variants associated with overgrowth conditions. However, as the pathogenic variant allele frequency varies by tissue type within an individual, submission of affected tissue(s) greatly increases the chances of a molecular diagnosis.

Use of Spectroscopic Techniques to Reveal the Nature of the Interactions of Two Sialic Acid Specific Lectins with Gold Nanoparticles.

From UV-vis absorption, steady state and time resolved fluorescence measurements coupled with circular dichroism (CD) spectral studies, it was revealed that among the two lectins: Sambucus nigra agglutinin (SNA) and Saraca indica (saracin II), SNA forms stronger binding complex in the ground state with gold nanoparticles (GNPs). From the measurements of Stern-Volmer (SV) constants Ksv, and binding constants K(A) and number of binding sites two important inferences could be drawn. Firstly, the fluorescence quenching is primarily due to static quenching and secondly SNA forms stronger binding with GNPs relative to the other lectin saracin II. Synchronous fluorescence spectral measurements further substantiate this proposition of exhibiting the fully exposed tryptophan residue in case of SNA. It appears that the lectin SNA adopted a relatively looser conformation with the extended polypeptide structures leading to the exposure of the hydrophobic cavities which favoured stronger binding with GNPs. CD measurements demonstrate that gold nanoparticles when interact with the lectins (glycoproteins), no significant distortion in the structural pattern of the later occurs. The unaltered identity in the secondary structural pattern of both SNA and saracin II in presence of gold nanoparticles hints that GNPs may be used as useful drug or drug delivery systems.

Improved Methods to Generate Spheroid Cultures from Tumor Cells, Tumor Cells & Fibroblasts or Tumor-Fragments: Microenvironment, Microvesicles and MiRNA.

Diagnostic and prognostic indicators are key components to achieve the goal of personalized cancer therapy. Two distinct approaches to this goal include predicting response by genetic analysis and direct testing of possible therapies using cultures derived from biopsy specimens. Optimally, the latter method requires a rapid assessment, but growing xenograft tumors or developing patient-derived cell lines can involve a great deal of time and expense. Furthermore, tumor cells have much different responses when grown in 2D versus 3D tissue environments. Using a modification of existing methods, we show that it is possible to make tumor-fragment (TF) spheroids in only 2-3 days. TF spheroids appear to closely model characteristics of the original tumor and may be used to assess critical therapy-modulating features of the microenvironment such as hypoxia. A similar method allows the reproducible development of spheroids from mixed tumor cells and fibroblasts (mixed-cell spheroids). Prior literature reports have shown highly variable development and properties of mixed-cell spheroids and this has hampered the detailed study of how individual tumor-cell components interact. In this study, we illustrate this approach and describe similarities and differences using two tumor models (U87 glioma and SQ20B squamous-cell carcinoma) with supporting data from additional cell lines. We show that U87 and SQ20B spheroids predict a key microenvironmental factor in tumors (hypoxia) and that SQ20B cells and spheroids generate similar numbers of microvesicles. We also present pilot data for miRNA expression under conditions of cells, tumors, and TF spheroids.

Evaluation of Mutational Testing of Preneoplastic Barrett's Mucosa by Next-Generation Sequencing of Formalin-Fixed, Paraffin-Embedded Endoscopic Samples for Detection of Concurrent Dysplasia and Adenocarcinoma in Barrett's Esophagus.

Barrett's intestinal metaplasia (BIM) may harbor genomic mutations before the histologic appearance of dysplasia and cancer and requires frequent surveillance. We explored next-generation sequencing to detect mutations with the analytical sensitivity required to predict concurrent high-grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) in patients with Barrett's esophagus by testing nonneoplastic BIM. Formalin-fixed, paraffin-embedded (FFPE) routine biopsy or endoscopic mucosal resection samples from 32 patients were tested: nonprogressors to HGD or EAC (BIM-NP) with BIM, who never had a diagnosis of dysplasia or EAC (N = 13); progressors to HGD or EAC (BIM-P) with BIM and a worse diagnosis of HGD or EAC (N = 15); and four BIM-negative samples. No mutations were detected in the BIM-NP (0 of 13) or BIM-negative samples, whereas the BIM-P samples had mutations in 6 (75%) of 8 cases in TP53, APC, and CDKN2A (P = 0.0005), detected in samples with as low as 20% BIM. We found that next-generation sequencing from routine FFPE nonneoplastic Barrett's esophagus samples can detect multiple mutations in minute areas of BIM with high analytical sensitivity. Next-generation sequencing panels for detection of TP53 and possibly combined mutations in other genes, such as APC and CDKN2A, may be useful in the clinical setting to improve dysplasia and cancer surveillance in patients with Barrett's esophagus.

Chromosome 3 status combined with BAP1 and EIF1AX mutation profiles are associated with metastasis in uveal melanoma.

PURPOSE: Somatic mutations in GNAQ, GNA11, SF3B1, EIF1AX, and BAP1 have been identified in uveal melanoma (UM). The aim of this study was to determine whether mutations in these genes in primary tumors were associated with metastases in individuals diagnosed with UM. METHODS: A total of 63 UM cases who developed a metastasis within 48 months of primary treatment and 53 UM controls who were metastasis-free over a similar time period were selected for the study. Primary UM cases were screened for mutations in GNAQ, GNA11, SF3B1, EIF1AX, and BAP1. The association of these mutations with tumor characteristics, chromosome 3 copy number, and metastatic status was analyzed by logistic regression to estimate the odds of developing metastasis within 48 months. RESULTS: As expected, tumor diameter, thickness, cilio-choroidal location, and chromosome 3 monosomy were all significantly (P < 0.02) associated with the presence of metastasis. In univariate analysis, GNA11 (odds ratio [OR] 2.5, 95% confidence interval [CI] 1.1-5.5) and BAP1 (OR 6.3, 95% CI 2.7-14.4) mutations were positively associated and EIF1AX mutation (OR 0.13, 95% CI 0.034-0.47) was inversely associated with metastatic status at 48 months after UM treatment. After adjustment for covariates, a chromosome 3 monosomy/BAP1-mutation/EIF1AX-wild-type (WT) mutation profile was strongly associated (OR 37.5, 95% CI 4.3-414) with the presence of metastasis compared with a chromosome 3 disomy/BAP1-WT/EIF1AX mutation profile. CONCLUSIONS: The results suggest that knowledge of mutations in BAP1 and EIF1AX can enhance prognostication of UM beyond that determined by chromosome 3 and tumor characteristics. Tumors with chromosome 3 disomy/BAP1-WT/EIF1AX-WT have a 10-fold increased risk of metastasis at 48 months compared with disomy-3/BAP1-WT/EIF1AX mutant tumors.

Absence of WNT4 gene mutation in a patient with MURCS association.

MURCS (Mullerian duct aplasia, Renal anomalies, and Cervicothoracic Somite dysplasia) association is a group of congenital genito-urinary and skeletal malformations. We report an adolescent girl with the cardinal features of MURCS association, obesity, and clinical findings of hyperandrogenism who did not show any exonic mutation of the WNT4 gene. Our finding excludes WNT4 gene as a candidate for MURCS association and suggests the need for further genetic studies.

Enhanced sensitivity for detection of low-level germline mosaic RB1 mutations in sporadic retinoblastoma cases using deep semiconductor sequencing.

Sporadic retinoblastoma (RB) is caused by de novo mutations in the RB1 gene. Often, these mutations are present as mosaic mutations that cannot be detected by Sanger sequencing. Next-generation deep sequencing allows unambiguous detection of the mosaic mutations in lymphocyte DNA. Deep sequencing of the RB1 gene on lymphocyte DNA from 20 bilateral and 70 unilateral RB cases was performed, where Sanger sequencing excluded the presence of mutations. The individual exons of the RB1 gene from each sample were amplified, pooled, ligated to barcoded adapters, and sequenced using semiconductor sequencing on an Ion Torrent Personal Genome Machine. Six low-level mosaic mutations were identified in bilateral RB and four in unilateral RB cases. The incidence of low-level mosaic mutation was estimated to be 30% and 6%, respectively, in sporadic bilateral and unilateral RB cases, previously classified as mutation negative. The frequency of point mutations detectable in lymphocyte DNA increased from 96% to 97% for bilateral RB and from 13% to 18% for unilateral RB. The use of deep sequencing technology increased the sensitivity of the detection of low-level germline mosaic mutations in the RB1 gene. This finding has significant implications for improved clinical diagnosis, genetic counseling, surveillance, and management of RB.

Detailed spectroscopic investigations to reveal the nature of interaction of anionic porphyrin with calf thymus DNA.

The interaction between anionic form of meso-tetrakis(4-carboxyphenyl) porphyrin (TCPP) and calf thymus deoxyribonucleic acid (CT DNA) is investigated by measuring UV-vis absorption, steady-state fluorescence, steady-state fluorescence anisotropy, time-resolved fluorescence, resonance light scattering (RLS), FT-IR and circular dichroism (CD) spectra along with the help of atomic force microscopy (AFM) under Tris-Borate-EDTA (TBE) buffer solution of pH 8.3. The static mode of fluorescence quenching of porphyrin by calf thymus deoxyribonucleic acid indicates the formation of a ground-state complex. The formation of ground-state complex is a spontaneous molecular interaction procedure in which outside groove binding through hydrogen bond or van der Waals force plays a major role. For biomedical application this investigation is very important as here TCPP, i.e. the anionic porphyrin does not bring any changes in the original structure of the CT DNA to selectively cleaving the nucleic acid to destroy the cancer or tumor cells whereas cationic porphyrin makes change in the protein structure significantly during the same process.