A pan-cancer compendium of chromosomal instability

Chromatin structure in cancer

In the past decade, we have seen the emergence of sequence-based methods to understand chromosome organization. With the confluence of in situ approaches to capture information on looping, topological domains, and larger chromatin compartments, understanding chromatin-driven disease is becoming feasible. Excitingly, recent advances in single molecule imaging with capacity to reconstruct “bulk-cell” features of chromosome conformation have revealed cell-to-cell chromatin structural variation. The fundamental question motivating our analysis of the literature is, can altered chromatin structure drive tumorigenesis? As our community learns more about rare disease, including low mutational frequency cancers, understanding “chromatin-driven” pathology will illuminate the regulatory structures of the genome. We describe recent insights into altered genome architecture in human cancer, highlighting multiple pathways toward disruptions of chromatin structure, including structural variation, noncoding mutations, metabolism, and de novo mutations to architectural regulators themselves. Our analysis of the literature reveals that deregulation of genome structure is characteristic in distinct classes of chromatin-driven tumors. As we begin to integrate the findings from single cell imaging studies and chromatin structural sequencing, we will be able to understand the diversity of cells within a common diagnosis, and begin to define structure–function relationships of the misfolded genome.

Ovarian cancer mutational processes drive site-specific immune evasion

High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability1-4 patterned by distinct mutational processes5,6, tumour heterogeneity7-9 and intraperitoneal spread7,8,10. Immunotherapies have had limited efficacy in HGSOC11-13, highlighting an unmet need to assess how mutational processes and the anatomical sites of tumour foci determine the immunological states of the tumour microenvironment. Here we carried out an integrative analysis of whole-genome sequencing, single-cell RNA sequencing, digital histopathology and multiplexed immunofluorescence of 160 tumour sites from 42 treatment-naive patients with HGSOC. Homologous recombination-deficient HRD-Dup (BRCA1 mutant-like) and HRD-Del (BRCA2 mutant-like) tumours harboured inflammatory signalling and ongoing immunoediting, reflected in loss of HLA diversity and tumour infiltration with highly differentiated dysfunctional CD8+ T cells. By contrast, foldback-inversion-bearing tumours exhibited elevated immunosuppressive TGFβ signalling and immune exclusion, with predominantly naive/stem-like and memory T cells. Phenotypic state associations were specific to anatomical sites, highlighting compositional, topological and functional differences between adnexal tumours and distal peritoneal foci. Our findings implicate anatomical sites and mutational processes as determinants of evolutionary phenotypic divergence and immune resistance mechanisms in HGSOC. Our study provides a multi-omic cellular phenotype data substrate from which to develop and interpret future personalized immunotherapeutic approaches and early detection research.

Extrachromosomal DNA amplifications in cancer

Extrachromosomal DNA (ecDNA) amplification is an important driver alteration in cancer. It has been observed in most cancer types and is associated with worse patient outcome. The functional impact of ecDNA has been linked to its unique properties, such as its circular structure that is associated with altered chromatinization and epigenetic regulatory landscape, as well as its ability to randomly segregate during cell division, which fuels intercellular copy number heterogeneity. Recent investigations suggest that ecDNA is structurally more complex than previously anticipated and that it localizes to specialized nuclear bodies (hubs) and can act in trans as an enhancer for genes on other ecDNAs or chromosomes. In this Review, we synthesize what is currently known about how ecDNA is generated and how its genetic and epigenetic architecture affects proto-oncogene deregulation in cancer. We discuss how recently identified ecDNA functions may impact oncogenesis but also serve as new therapeutic vulnerabilities in cancer.

Functional analysis of structural variants in single cells using Strand-seq

Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their functional consequences. We present a computational method, scNOVA, which uses Strand-seq to perform haplotype-aware integration of SV discovery and molecular phenotyping in single cells by using nucleosome occupancy to infer gene expression as a readout. Application to leukemias and cell lines identifies local effects of copy-balanced rearrangements on gene deregulation, and consequences of SVs on aberrant signaling pathways in subclones. We discovered distinct SV subclones with dysregulated Wnt signaling in a chronic lymphocytic leukemia patient. We further uncovered the consequences of subclonal chromothripsis in T cell acute lymphoblastic leukemia, which revealed c-Myb activation, enrichment of a primitive cell state and informed successful targeting of the subclone in cell culture, using a Notch inhibitor. By directly linking SVs to their functional effects, scNOVA enables systematic single-cell multiomic studies of structural variation in heterogeneous cell populations.

Comparative Genomic Hybridization and Transcriptome Sequencing Reveal Genes with Gain in Acute Lymphoblastic Leukemia: JUP Expression Emerges as a Survival-Related Gene

Acute lymphoblastic leukemia (ALL) in children or adults is characterized by structural and numeric aberrations in chromosomes; these anomalies strongly correlate with prognosis and clinical outcome. Therefore, this work aimed to identify the genes present in chromosomal gain regions found more frequently in patients with acute lymphoblastic leukemia (ALL) and ALL-derived cell lines using comparative genomic hybridization (CGH). In addition, validation of the genes found in these regions was performed utilizing RNAseq from JURKAT, CEM, and SUP-B15 cell lines, as well as expression microarrays derived from a MILE study. Chromosomes with common gain zones that were maintained in six or more samples were 14, 17, and 22, in which a total of 22 genes were identified. From them, NT5C3B, CNP, ACLY, and GNB1L maintained overexpression at the mRNA level in the cell lines and in patients with ALL. It is noteworthy that SALL2 showed very high expression in T-ALL, while JUP was highly expressed in B-ALL lineages. Interestingly, the latter correlated with worse survival in patients. This provided evidence that the measurement of these genes has high potential for clinical utility; however, their expressions should first be evaluated with a sensitive test in a more significant number of patients.

Molecular Management of High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

Genomic Instability in Cerebrospinal Fluid Cell-Free DNA Predicts Poor Prognosis in Solid Tumor Patients with Meningeal Metastasis

Simple Summary

We established a genomic instability score using unfiltered sequencing data from meningeal metastasis (MM) cell-free circulating tumor DNA (ctDNA) samples and found that substantial genomic instability (GI) was present in cerebrospinal fluid ctDNA rather than plasma ctDNA, implying that MM lesions have a significantly increased GI status compared to primary tumors or extracranial metastatic lesions, which may suggest tumor clonal evolution. We also found that high GI status was an independent poor prognostic factor in lung adenocarcinoma MM patients, including meningeal metastasis-free survival (MFS) and overall survival (OS). Considering that genomically unstable tumors are more sensitive to PARP inhibitors, targeting GI alone or in combination with conventional therapy may be a promising treatment strategy for solid tumor patients with MM.

Abstract

Genomic instability (GI), which leads to the accumulation of DNA loss, gain, and rearrangement, is a hallmark of many cancers such as lung cancer, breast cancer, and colon cancer. However, the clinical significance of GI has not been systematically studied in the meningeal metastasis (MM) of solid tumors. Here, we collected both cerebrospinal fluid (CSF) and plasma samples from 56 solid tumor MM patients and isolated cell-free ctDNA to investigate the GI status using a next-generation sequencing-based comprehensive genomic profiling of 543 cancer-related genes. According to the unfiltered heterozygous mutation data-derived GI score, we found that 37 (66.1%) cases of CSF and 3 cases (6%) of plasma had a high GI status, which was further validated by low-depth whole-genome sequencing analysis. It is demonstrated that a high GI status in CSF was associated with poor prognosis, high intracranial pressure, and low Karnofsky performance status scores. More notably, a high GI status was an independent poor prognostic factor of poor MM-free survival and overall survival in lung adenocarcinoma MM patients. Furthermore, high occurrences of the co-mutation of TP53/EGFR, TP53/RB1, TP53/ERBB2, and TP53/KMT2C were found in MM patients with a high GI status. In summary, the GI status in CSF ctDNA might be a valuable prognostic indicator in solid tumor patients with MM.

Chromosomal Instability, Selection and Competition: Factors That Shape the Level of Karyotype Intra-Tumor Heterogeneity

Intra-tumor heterogeneity (ITH) is a pan-cancer predictor of survival, with high ITH being correlated to a dismal prognosis. The level of ITH is, hence, a clinically relevant characteristic of a malignancy. ITH of karyotypes is driven by chromosomal instability (CIN). However, not all new karyotypes generated by CIN are viable or competitive, which limits the amount of ITH. Here, we review the cellular processes and ecological properties that determine karyotype ITH. We propose a framework to understand karyotype ITH, in which cells with new karyotypes emerge through CIN, are selected by cell intrinsic and cell extrinsic selective pressures, and propagate through a cancer in competition with other malignant cells. We further discuss how CIN modulates the cell phenotype and immune microenvironment, and the implications this has for the subsequent selection of karyotypes. Together, we aim to provide a comprehensive overview of the biological processes that shape the level of karyotype heterogeneity.

DETexT: An SNV detection enhancement for low read depth by integrating mutational signatures into TextCNN

Detecting SNV at very low read depths helps to reduce sequencing requirements, lowers sequencing costs, and aids in the early screening, diagnosis, and treatment of cancer. However, the accuracy of SNV detection is significantly reduced at read depths below ×34 due to the lack of a sufficient number of read pairs to help filter out false positives. Many recent studies have revealed the potential of mutational signature (MS) in detecting true SNV, understanding the mutational processes that lead to the development of human cancers, and analyzing the endogenous and exogenous causes. Here, we present DETexT, an SNV detection method better suited to low read depths, which classifies false positive variants by combining MS with deep learning algorithms to mine correlation information around bases in individual reads without relying on the support of duplicate read pairs. We have validated the effectiveness of DETexT on simulated and real datasets and conducted comparative experiments. The source code has been uploaded to https://github.com/TrinaZ/extra-lowRD for academic use only.