A Thpok-Directed Transcriptional Circuitry Promotes Bcl6 and Maf Expression to Orchestrate T Follicular Helper Differentiation.

The generation of high-affinity neutralizing antibodies, the objective of most vaccine strategies, occurs in B cells within germinal centers (GCs) and requires rate-limiting "help" from follicular helper CD4+ T (Tfh) cells. Although Tfh differentiation is an attribute of MHC II-restricted CD4+ T cells, the transcription factors driving Tfh differentiation, notably Bcl6, are not restricted to CD4+ T cells. Here, we identified a requirement for the CD4+-specific transcription factor Thpok during Tfh cell differentiation, GC formation, and antibody maturation. Thpok promoted Bcl6 expression and bound to a Thpok-responsive region in the first intron of Bcl6. Thpok also promoted the expression of Bcl6-independent genes, including the transcription factor Maf, which cooperated with Bcl6 to mediate the effect of Thpok on Tfh cell differentiation. Our findings identify a transcriptional program that links the CD4+ lineage with Tfh differentiation, a limiting factor for efficient B cell responses, and suggest avenues to optimize vaccine generation.

IKKα-deficient lung adenocarcinomas generate an immunosuppressive microenvironment by overproducing Treg-inducing cytokines.

The tumor microenvironment (TME) provides potential targets for cancer therapy. However, how signals originating in cancer cells affect tumor-directed immunity is largely unknown. Deletions in the CHUK locus, coding for IκB kinase α (IKKα), correlate with reduced lung adenocarcinoma (ADC) patient survival and promote KrasG12D-initiated ADC development in mice, but it is unknown how reduced IKKα expression affects the TME. Here, we report that low IKKα expression in human and mouse lung ADC cells correlates with increased monocyte-derived macrophage and regulatory T cell (Treg) scores and elevated transcription of genes coding for macrophage-recruiting and Treg-inducing cytokines (CSF1, CCL22, TNF, and IL-23A). By stimulating recruitment of monocyte-derived macrophages from the bone marrow and enforcing a TNF/TNFR2/c-Rel signaling cascade that stimulates Treg generation, these cytokines promote lung ADC progression. Depletion of TNFR2, c-Rel, or TNF in CD4+ T cells or monocyte-derived macrophages dampens Treg generation and lung tumorigenesis. Treg depletion also attenuates carcinogenesis. In conclusion, reduced cancer cell IKKα activity enhances formation of a protumorigenic TME through a pathway whose constituents may serve as therapeutic targets for KRAS-initiated lung ADC.

NF-κB Signaling Modulates miR-452-5p and miR-335-5p Expression to Functionally Decrease Epithelial Ovarian Cancer Progression in Tumor-Initiating Cells.

Epithelial ovarian cancer (EOC) remains the fifth leading cause of cancer-related death in women worldwide, partly due to the survival of chemoresistant, stem-like tumor-initiating cells (TICs) that promote disease relapse. We previously described a role for the NF-κB pathway in promoting TIC chemoresistance and survival through NF-κB transcription factors (TFs) RelA and RelB, which regulate genes important for the inflammatory response and those associated with cancer, including microRNAs (miRNAs). We hypothesized that NF-κB signaling differentially regulates miRNA expression through RelA and RelB to support TIC persistence. Inducible shRNA was stably expressed in OV90 cells to knockdown RELA or RELB; miR-seq analyses identified differentially expressed miRNAs hsa-miR-452-5p and hsa-miR-335-5p in cells grown in TIC versus adherent conditions. We validated the miR-seq findings via qPCR in TIC or adherent conditions with RELA or RELB knocked-down. We confirmed decreased expression of hsa-miR-452-5p when either RELA or RELB were depleted and increased expression of hsa-miR-335-5p when RELA was depleted. Either inhibiting miR-452-5p or mimicking miR-335-5p functionally decreased the stem-like potential of the TICs. These results highlight a novel role of NF-κB TFs in modulating miRNA expression in EOC cells, thus opening a better understanding toward preventing recurrence of EOC.

Implementation of ensemble machine learning algorithms on exome datasets for predicting early diagnosis of cancers.

Classification of different cancer types is an essential step in designing a decision support model for early cancer predictions. Using various machine learning (ML) techniques with ensemble learning is one such method used for classifications. In the present study, various ML algorithms were explored on twenty exome datasets, belonging to 5 cancer types. Initially, a data clean-up was carried out on 4181 variants of cancer with 88 features, and a derivative dataset was obtained using natural language processing and probabilistic distribution. An exploratory dataset analysis using principal component analysis was then performed in 1 and 2D axes to reduce the high-dimensionality of the data. To significantly reduce the imbalance in the derivative dataset, oversampling was carried out using SMOTE. Further, classification algorithms such as K-nearest neighbour and support vector machine were used initially on the oversampled dataset. A 4-layer artificial neural network model with 1D batch normalization was also designed to improve the model accuracy. Ensemble ML techniques such as bagging along with using KNN, SVM and MLPs as base classifiers to improve the weighted average performance metrics of the model. However, due to small sample size, model improvement was challenging. Therefore, a novel method to augment the sample size using generative adversarial network (GAN) and triplet based variational auto encoder (TVAE) was employed that reconstructed the features and labels generating the data. The results showed that from initial scrutiny, KNN showed a weighted average of 0.74 and SVM 0.76. Oversampling ensured that the accuracy of the derivative dataset improved significantly and the ensemble classifier augmented the accuracy to 82.91%, when the data was divided into 70:15:15 ratio (training, test and holdout datasets). The overall evaluation metric value when GAN and TVAE increased the sample size was found to be 0.92 with an overall comparison model of 0.66. Therefore, the present study designed an effective model for classifying cancers which when implemented to real world samples, will play a major role in early cancer diagnosis.

Genetics and Pathogenesis of Diffuse Large B-Cell Lymphoma.

BACKGROUND: Diffuse large B-cell lymphomas (DLBCLs) are phenotypically and genetically heterogeneous. Gene-expression profiling has identified subgroups of DLBCL (activated B-cell-like [ABC], germinal-center B-cell-like [GCB], and unclassified) according to cell of origin that are associated with a differential response to chemotherapy and targeted agents. We sought to extend these findings by identifying genetic subtypes of DLBCL based on shared genomic abnormalities and to uncover therapeutic vulnerabilities based on tumor genetics. METHODS: We studied 574 DLBCL biopsy samples using exome and transcriptome sequencing, array-based DNA copy-number analysis, and targeted amplicon resequencing of 372 genes to identify genes with recurrent aberrations. We developed and implemented an algorithm to discover genetic subtypes based on the co-occurrence of genetic alterations. RESULTS: We identified four prominent genetic subtypes in DLBCL, termed MCD (based on the co-occurrence of MYD88L265P and CD79B mutations), BN2 (based on BCL6 fusions and NOTCH2 mutations), N1 (based on NOTCH1 mutations), and EZB (based on EZH2 mutations and BCL2 translocations). Genetic aberrations in multiple genes distinguished each genetic subtype from other DLBCLs. These subtypes differed phenotypically, as judged by differences in gene-expression signatures and responses to immunochemotherapy, with favorable survival in the BN2 and EZB subtypes and inferior outcomes in the MCD and N1 subtypes. Analysis of genetic pathways suggested that MCD and BN2 DLBCLs rely on "chronic active" B-cell receptor signaling that is amenable to therapeutic inhibition. CONCLUSIONS: We uncovered genetic subtypes of DLBCL with distinct genotypic, epigenetic, and clinical characteristics, providing a potential nosology for precision-medicine strategies in DLBCL. (Funded by the Intramural Research Program of the National Institutes of Health and others.).

Single-cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma.

Intratumor molecular heterogeneity of hepatocellular carcinoma is partly attributed to the presence of hepatic cancer stem cells (CSCs). Different CSC populations defined by various cell surface markers may contain different oncogenic drivers, posing a challenge in defining molecularly targeted therapeutics. We combined transcriptomic and functional analyses of hepatocellular carcinoma cells at the single-cell level to assess the degree of CSC heterogeneity. We provide evidence that hepatic CSCs at the single-cell level are phenotypically, functionally, and transcriptomically heterogeneous. We found that different CSC subpopulations contain distinct molecular signatures. Interestingly, distinct genes within different CSC subpopulations are independently associated with hepatocellular carcinoma prognosis, suggesting that a diverse hepatic CSC transcriptome affects intratumor heterogeneity and tumor progression. CONCLUSION: Our work provides unique perspectives into the biodiversity of CSC subpopulations, whose molecular heterogeneity further highlights their role in tumor heterogeneity, prognosis, and hepatic CSC therapy. (Hepatology 2018;68:127-140).

Control of Regulatory T Cell Differentiation by the Transcription Factors Thpok and LRF.

The CD4+ lineage-specific transcription factor Thpok is required for intrathymic CD4+ T cell differentiation and, together with its homolog LRF, supports CD4+ T cell helper effector responses. However, it is not known whether these factors are needed for the regulatory T cell (Treg) arm of MHC class II responses. In this study, by inactivating in mice the genes encoding both factors in differentiated Tregs, we show that Thpok and LRF are redundantly required to maintain the size and functions of the postthymic Treg pool. They support IL-2-mediated gene expression and the functions of the Treg-specific factor Foxp3. Accordingly, Treg-specific disruption of Thpok and Lrf causes a lethal inflammatory syndrome similar to that resulting from Treg deficiency. Unlike in conventional T cells, Thpok and LRF functions in Tregs are not mediated by their repression of the transcription factor Runx3. Additionally, we found that Thpok is needed for the differentiation of thymic Treg precursors, an observation in line with the fact that Foxp3+ Tregs are CD4+ cells. Thus, a common Thpok-LRF node supports both helper and regulatory arms of MHC class II responses.

Whole exome sequencing identifies a novel splice-site mutation in ADAMTS17 in an Indian family with Weill-Marchesani syndrome.

PURPOSE: Weill-Marchesani syndrome (WMS) is a rare connective tissue disorder, characterized by short stature, microspherophakic lens, and stubby hands and feet (brachydactyly). WMS is caused by mutations in the FBN1, ADAMTS10, and LTBP2 genes. Mutations in the LTBP2 and ADAMTS17 genes cause a WMS-like syndrome, in which the affected individuals show major features of WMS but do not display brachydactyly and joint stiffness. The main purpose of our study was to determine the genetic cause of WMS in an Indian family. METHODS: Whole exome sequencing (WES) was used to identify the genetic cause of WMS in the family. The cosegregation of the mutation was determined with Sanger sequencing. Reverse transcription (RT)-PCR analysis was used to assess the effect of a splice-site mutation on splicing of the ADAMTS17 transcript. RESULTS: The WES analysis identified a homozygous novel splice-site mutation c.873+1G>T in a known WMS-like syndrome gene, ADAMTS17, in the family. RT-PCR analysis in the patient showed that exon 5 was skipped, which resulted in the deletion of 28 amino acids in the ADAMTS17 protein. CONCLUSIONS: The mutation in the WMS-like syndrome gene ADAMTS17 also causes WMS in an Indian family. The present study will be helpful in genetic diagnosis of this family and increases the number of mutations of this gene to six.

Characterization of tumor evolution by functional clonality and phylogenetics in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a molecularly heterogeneous solid malignancy, and its fitness may be shaped by how its tumor cells evolve. However, ability to monitor tumor cell evolution is hampered by the presence of numerous passenger mutations that do not provide any biological consequences. Here we develop a strategy to determine the tumor clonality of three independent HCC cohorts of 524 patients with diverse etiologies and race/ethnicity by utilizing somatic mutations in cancer driver genes. We identify two main types of tumor evolution, i.e., linear, and non-linear models where non-linear type could be further divided into classes, which we call shallow branching and deep branching. We find that linear evolving HCC is less aggressive than other types. GTF2IRD2B mutations are enriched in HCC with linear evolution, while TP53 mutations are the most frequent genetic alterations in HCC with non-linear models. Furthermore, we observe significant B cell enrichment in linear trees compared to non-linear trees suggesting the need for further research to uncover potential variations in immune cell types within genomically determined phylogeny types. These results hint at the possibility that tumor cells and their microenvironment may collectively influence the tumor evolution process.

Severus: accurate detection and characterization of somatic structural variation in tumor genomes using long reads.

Most current studies rely on short-read sequencing to detect somatic structural variation (SV) in cancer genomes. Long-read sequencing offers the advantage of better mappability and long-range phasing, which results in substantial improvements in germline SV detection. However, current long-read SV detection methods do not generalize well to the analysis of somatic SVs in tumor genomes with complex rearrangements, heterogeneity, and aneuploidy. Here, we present Severus: a method for the accurate detection of different types of somatic SVs using a phased breakpoint graph approach. To benchmark various short- and long-read SV detection methods, we sequenced five tumor/normal cell line pairs with Illumina, Nanopore, and PacBio sequencing platforms; on this benchmark Severus showed the highest F1 scores (harmonic mean of the precision and recall) as compared to long-read and short-read methods. We then applied Severus to three clinical cases of pediatric cancer, demonstrating concordance with known genetic findings as well as revealing clinically relevant cryptic rearrangements missed by standard genomic panels.

Interleukin-27 treated human macrophages induce the expression of novel microRNAs which may mediate anti-viral properties.

Interleukin-27 (IL-27) is a pleiotropic cytokine which plays important and diverse roles in the immune system. We have previously demonstrated that IL-27 induces potent anti-viral effects against HIV-1, HIV-2, SIV, HSV-2, KSHV and influenza viruses in macrophages. This induction occurred in an interferon (IFN) independent manner and involved down regulation of SPTBN1. MicroRNAs (miRNAs) are critical regulators of mRNA translation and turnover. There have been reports that some miRNAs inhibit viral replication. In this study, we hypothesized that IL-27 could induce the expression of novel miRNAs in macrophages which may have functional relevance in terms of anti-viral activity and primary monocytes were differentiated into macrophages using either M-CSF (M-Mac) or a combination of M-CSF and IL-27 (I-Mac) for seven days. Following this, total RNA was extracted from these cells and deep sequencing was performed, in parallel with gene expression microarrays. Using the novel miRNA discovery software, miRDeep, seven novel miRNAs were discovered in these macrophages. Four of which were preferentially expressed in I-Mac (miR-SX1, -SX2, -SX3 and -SX6) whilst three were detected in both M-Mac and I-Mac (miR-SX4, -SX5 and -SX7). The expression of six of the seven novel miRNAs was highly correlated with qRT-PCR using specific primer/probes designed for the novel miRNAs. Gene expression microarray further demonstrated that a number of genes were potentially targeted by these differentially expressed novel miRNAs. Finally, several of these novel miRNAs (miR-SX1, -SX4, -SX5, -SX6 and -SX7) were shown to target the open reading frames of a number of viruses (including HSV-1, HSV-2 and HHV-8) which may partially explain the anti-viral properties observed.

Trends of Change in Empathy Among Indian Medical Students: A Two-Year Follow-Up Study.

Background: The development of an empathic approach is essential for doctor-patient relationships. Medical training is a challenging time that may affect empathy. This study aimed to assess the change in empathy in students during medical education. Methods: One hundred and fifty MBBS students were recruited at admission and assessed for empathy, interpersonal reactivity, and general health. They were followed for two years and assessed at three intervals. Results: A significant decline was seen in empathy for both male and female students. The decline was correlated with psychological stress. Gender, family structure, having siblings, and increasing General Health Questionnaire score predicted change in empathy. Conclusion: Empathy declines with advancing training, varying with constitutional and situational factors. The medical curriculum should include skills like empathic communication as well.

A Cross-sectional Assessment of Depression, Anxiety, and Cognition in Perimenopausal and Menopausal Women.

Introduction: Menopausal transition involves failure of ovarian function followed by cessation of menstruation. This has been said to lead to psychiatric comorbidities such as depression and anxiety. Estrogen also has beneficial effects on cognition and thus fluctuation in the same can lead to cognitive decline. Given the number of women undergoing menopause, timely screening of the comorbidities is of importance. Aims and Objectives: Our study aimed at assessment of anxiety, depression, and cognitive impairment in perimenopausal and postmenopausal women presenting in the medicine and gynecology units of a tertiary care hospital. The objectives were to screen the peri- and postmenopausal women presenting with medical and gynecological complaints for the presence of depression and anxiety and assess their cognitive function. To find association of their symptoms with psychosocial and menopausal factors with the psychiatric parameters. Settings and Design: Our study was conducted among the perimenopausal and postmenopausal women visiting gynecology and medicine units in a tertiary care hospital. One hundred and five women in the age group of 45-55 were assessed using a specialized pro forma, Beck's Anxiety Inventory, Beck's Depression Inventory, and Addenbrooke's Cognitive Examination III. Statistical Analysis Used: The results were analyzed using SPSS software (version 20.0). Results: 21.9% of females had moderate levels of anxiety, 24.76% had clinical depression, and 13.33% had mild cognitive impairment. The presence of psychosocial stressors had a significant impact on the anxiety, depression, and cognitive impairment. There was no significant association found between psychiatric parameters and peri- and postmenopausal stage as well between natural or surgical menopause.

UGDH promotes tumor-initiating cells and a fibroinflammatory tumor microenvironment in ovarian cancer.

BACKGROUND: Epithelial ovarian cancer (EOC) is a global health burden, with the poorest five-year survival rate of the gynecological malignancies due to diagnosis at advanced stage and high recurrence rate. Recurrence in EOC is driven by the survival of chemoresistant, stem-like tumor-initiating cells (TICs) that are supported by a complex extracellular matrix and immunosuppressive microenvironment. To target TICs to prevent recurrence, we identified genes critical for TIC viability from a whole genome siRNA screen. A top hit was the cancer-associated, proteoglycan subunit synthesis enzyme UDP-glucose dehydrogenase (UGDH). METHODS: Immunohistochemistry was used to characterize UGDH expression in histological and molecular subtypes of EOC. EOC cell lines were subtyped according to the molecular subtypes and the functional effects of modulating UGDH expression in vitro and in vivo in C1/Mesenchymal and C4/Differentiated subtype cell lines was examined. RESULTS: High UGDH expression was observed in high-grade serous ovarian cancers and a distinctive survival prognostic for UGDH expression was revealed when serous cancers were stratified by molecular subtype. High UGDH was associated with a poor prognosis in the C1/Mesenchymal subtype and low UGDH was associated with poor prognosis in the C4/Differentiated subtype. Knockdown of UGDH in the C1/mesenchymal molecular subtype reduced spheroid formation and viability and reduced the CD133 + /ALDH high TIC population. Conversely, overexpression of UGDH in the C4/Differentiated subtype reduced the TIC population. In co-culture models, UGDH expression in spheroids affected the gene expression of mesothelial cells causing changes to matrix remodeling proteins, and fibroblast collagen production. Inflammatory cytokine expression of spheroids was altered by UGDH expression. The effect of UGDH knockdown or overexpression in the C1/ Mesenchymal and C4/Differentiated subtypes respectively was tested on mouse intrabursal xenografts and showed dynamic changes to the tumor stroma. Knockdown of UGDH improved survival and reduced tumor burden in C1/Mesenchymal compared to controls. CONCLUSIONS: These data show that modulation of UGDH expression in ovarian cancer reveals distinct roles for UGDH in the C1/Mesenchymal and C4/Differentiated molecular subtypes of EOC, influencing the tumor microenvironmental composition. UGDH is a strong potential therapeutic target in TICs, for the treatment of EOC, particularly in patients with the mesenchymal molecular subtype.

Tumor biology and immune infiltration define primary liver cancer subsets linked to overall survival after immunotherapy.

Primary liver cancer is a rising cause of cancer deaths in the US. Although immunotherapy with immune checkpoint inhibitors induces a potent response in a subset of patients, response rates vary among individuals. Predicting which patients will respond to immune checkpoint inhibitors is of great interest in the field. In a retrospective arm of the National Cancer Institute Cancers of the Liver: Accelerating Research of Immunotherapy by a Transdisciplinary Network (NCI-CLARITY) study, we use archived formalin-fixed, paraffin-embedded samples to profile the transcriptome and genomic alterations among 86 hepatocellular carcinoma and cholangiocarcinoma patients prior to and following immune checkpoint inhibitor treatment. Using supervised and unsupervised approaches, we identify stable molecular subtypes linked to overall survival and distinguished by two axes of aggressive tumor biology and microenvironmental features. Moreover, molecular responses to immune checkpoint inhibitor treatment differ between subtypes. Thus, patients with heterogeneous liver cancer may be stratified by molecular status indicative of treatment response to immune checkpoint inhibitors.

Structural variant analysis of a cancer reference cell line sample using multiple sequencing technologies.

BACKGROUND: The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples. RESULTS: We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy. CONCLUSIONS: A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods.

Proteasome inhibition alters mitotic progression through the upregulation of centromeric α-Satellite RNAs.

Cell cycle progression requires control of the abundance of several proteins and RNAs over space and time to properly transit from one phase to the next and to ensure faithful genomic inheritance in daughter cells. The proteasome, the main protein degradation system of the cell, facilitates the establishment of a proteome specific to each phase of the cell cycle. Its activity also strongly influences transcription. Here, we detected the upregulation of repetitive RNAs upon proteasome inhibition in human cancer cells using RNA-seq. The effect of proteasome inhibition on centromeres was remarkable, especially on α-Satellite RNAs. We showed that α-Satellite RNAs fluctuate along the cell cycle and interact with members of the cohesin ring, suggesting that these transcripts may take part in the regulation of mitotic progression. Next, we forced exogenous overexpression and used gapmer oligonucleotide targeting to demonstrate that α-Sat RNAs have regulatory roles in mitosis. Finally, we explored the transcriptional regulation of α-Satellite DNA. Through in silico analyses, we detected the presence of CCAAT transcription factor-binding motifs within α-Satellite centromeric arrays. Using high-resolution three-dimensional immuno-FISH and ChIP-qPCR, we showed an association between the α-Satellite upregulation and the recruitment of the transcription factor NFY-A to the centromere upon MG132-induced proteasome inhibition. Together, our results show that the proteasome controls α-Satellite RNAs associated with the regulation of mitosis.

Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study.

With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies.

Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing.

The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor-normal genomic DNA (gDNA) samples derived from a breast cancer cell line-which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations-and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking 'tumor-only' or 'matched tumor-normal' analyses.

A homozygous mutation in LTBP2 causes isolated microspherophakia.

Microspherophakia is an autosomal-recessive congenital disorder characterized by small spherical lens. It may be isolated or occur as part of a hereditary systemic disorder, such as Marfan syndrome, autosomal dominant and recessive forms of Weill-Marchesani syndrome, autosomal dominant glaucoma-lens ectopia-microspherophakia-stiffness-shortness syndrome, autosomal dominant microspherophakia with hernia, and microspherophakia-metaphyseal dysplasia. The purpose of this study was to map and identify the gene for isolated microspherophakia in two consanguineous Indian families. Using a whole-genome linkage scan in one family, we identified a likely locus for microspherophakia (MSP1) on chromosome 14q24.1-q32.12 between markers D14S588 and D14S1050 in a physical distance of 22.76 Mb. The maximum multi-point lod score was 2.91 between markers D14S1020 and D14S606. The MSP1 candidate region harbors 110 reference genes. DNA sequence analysis of one of the genes, LTBP2, detected a homozygous duplication (insertion) mutation, c.5446dupC, in the last exon (exon 36) in affected family members. This homozygous mutation is predicted to elongate the LTBP2 protein by replacing the last 6 amino acids with 27 novel amino acids. Microspherophakia in the second family did not map to this locus, suggesting genetic heterogeneity. The present study suggests a role for LTBP2 in the structural stability of ciliary zonules, and growth and development of lens.