RESUMO
The human cerebral cortex, pivotal for advanced cognitive functions, is composed of six distinct layers and dozens of functionally specialized areas1,2. The layers and areas are distinguished both molecularly, by diverse neuronal and glial cell subtypes, and structurally, through intricate spatial organization3,4. While single-cell transcriptomics studies have advanced molecular characterization of human cortical development, a critical gap exists due to the loss of spatial context during cell dissociation5,6,7,8. Here, we utilized multiplexed error-robust fluorescence in situ hybridization (MERFISH)9, augmented with deep-learning-based cell segmentation, to examine the molecular, cellular, and cytoarchitectural development of human fetal cortex with spatially resolved single-cell resolution. Our extensive spatial atlas, encompassing 16 million single cells, spans eight cortical areas across four time points in the second and third trimesters. We uncovered an early establishment of the six-layer structure, identifiable in the laminar distribution of excitatory neuronal subtypes by mid-gestation, long before the emergence of cytoarchitectural layers. Notably, while anterior-posterior gradients of neuronal subtypes were generally observed in most cortical areas, a striking exception was the sharp molecular border between primary (V1) and secondary visual cortices (V2) at gestational week 20. Here we discovered an abrupt binary shift in neuronal subtype specification at the earliest stages, challenging the notion that continuous morphogen gradients dictate mid-gestation cortical arealization6,10. Moreover, integrating single-nuclei RNA-sequencing and in situ whole transcriptomics revealed an early upregulation of synaptogenesis in V1-specific Layer 4 neurons, suggesting a role of synaptogenesis in this discrete border formation. Collectively, our findings underscore the crucial role of spatial relationships in determining the molecular specification of cortical layers and areas. This work not only provides a valuable resource for the field, but also establishes a spatially resolved single-cell analysis paradigm that paves the way for a comprehensive developmental atlas of the human brain.
RESUMO
The presence of variants of uncertain significance (VUS) in DNA mismatch repair (MMR) genes leads to uncertainty in the clinical management of patients being evaluated for Lynch syndrome (LS). Currently, there is no platform to systematically use tumor-derived evidence alongside germline data for the assessment of VUS in relation to LS. We developed INT2GRATE (INTegrated INTerpretation of GeRmline And Tumor gEnomes) to leverage information from the tumor genome to inform the potential role of constitutional VUS in MMR genes. INT2GRATE platform has two components: a comprehensive evidence-based decision tree that integrates well-established clinico-genomic data from both the tumor and constitutional genomes to help inform the potential relevance of germline VUS in LS; and a web-based user interface (UI). With the INT2GRATE decision tree operating in the backend, INT2GRATE UI enables the front-end collection of comprehensive clinical genetics and tumor-derived evidence for each VUS to facilitate INT2GRATE assessment and data sharing in the publicly accessible ClinVar database. The performance of the INT2GRATE decision tree was assessed by qualitative retrospective analysis of genomic data from 5057 cancer patients with MMR alterations which included 52 positive control cases. Of 52 positive control cases with LS and pathogenic MMR alterations, 23 had all the testing parameters for the evaluation by INT2GRATE. All these variants were correctly categorized as INT2GRATE POSITIVE. The stringent INT2GRATE decision tree flagged 29 of positive cases by identifying the absence or unusual presentation of specific evidence, highlighting the conservative INT2GRATE logic in favor of a higher degree of confidence in the results. The remaining 99% of cases were correctly categorized as INCONCLUSIVE due to the absence of LS criteria and ≥1 tumor parameters. INT2GRATE is an effective platform for clinical and genetics professionals to collect and assess clinical genetics and complimentary tumor-derived information for each germline VUS in suspected LS patients. Furthermore, INT2GRATE enables the collation of integrated tumor-derived evidence relevant to germline VUS in LS, and sharing them with a large community, a practice that is needed in precision oncology.
RESUMO
Genomic profiles of tumors are often unique and represent characteristic mutational signatures defined by DNA damage or DNA repair response processes. The tumor-derived somatic information has been widely used in therapeutic applications, but it is grossly underutilized in the assessment of germline genetic variants. Here, we present a comprehensive approach for evaluating the pathogenicity of germline variants in cancer using an integrated interpretation of somatic and germline genomic data. We have previously demonstrated the utility of this integrated approach in the reassessment of pathogenic germline variants in selected cancer patients with unexpected or non-syndromic phenotypes. The application of this approach is presented in the assessment of rare variants of uncertain significance (VUS) in Lynch-related colon cancer, hereditary paraganglioma-pheochromocytoma syndrome, and Li-Fraumeni syndrome. Using this integrated method, germline VUS in PMS2, MSH6, SDHC, SHDA, and TP53 were assessed in 16 cancer patients after genetic evaluation. Comprehensive clinical criteria, somatic signature profiles, and tumor immunohistochemistry were used to re-classify VUS by upgrading or downgrading the variants to likely or unlikely actionable categories, respectively. Going forward, collation of such germline variants and creation of cross-institutional knowledgebase datasets that include integrated somatic and germline data will be crucial for the assessment of these variants in a larger cancer cohort.
RESUMO
PURPOSE: Given regulatory approval of immune checkpoint inhibitors in patients with mismatch repair-deficient (MMR-D) cancers agnostic to tumor type, it has become important to characterize occurrence of MMR-D and develop cost-effective screening approaches. Using a next-generation sequencing (NGS) panel (OncoPanel), we developed an algorithm to identify MMR-D frequency in tumor samples and applied it in a clinical setting with pathologist review. METHODS: To predict MMR-D, we adapted methods described previously for use in NGS panels, which assess patterns of single base-pair insertion or deletion events occurring in homopolymer regions. Tumors assayed with OncoPanel between July 2013 and July 2018 were included. For tumors tested after June 2017, sequencing results were presented to pathologists in real time for clinical MMR determination, in the context of tumor mutation burden, other mutational signatures, and clinical data. RESULTS: Of 20,301 tumors sequenced, 2.7% (553) were retrospectively classified as MMR-D by the algorithm. Of 4,404 samples with pathologist sign-out of MMR status, the algorithm classified 147 (3.3%) as MMR-D: in 116 cases, MMR-D was confirmed by a pathologist, five cases were overruled by the pathologist, and 26 were assessed as indeterminate. Overall, the highest frequencies of OncoPanel-inferred MMR-D were in endometrial (21%; 152/723), colorectal (9.7%; 169/1,744), and small bowel (9.3%; 9/97) cancers. When algorithm predictions were compared with historical MMR immunohistochemistry or polymerase chain reaction results in a set of 325 tumors sequenced before initiation of pathologist assessment, the overall sensitivity and specificity of the algorithm were 91.1% and 98.2%, respectively. CONCLUSION: We show that targeted, tumor-only NGS can be leveraged to determine MMR signatures across tumor types, suggesting that broader biomarker screening approaches may have clinical value.