Joint Clustering of Single-Cell Sequencing and Fluorescence In Situ Hybridization Data for Reconstructing Clonal Heterogeneity in Cancers

Deconvolution and Phylogeny Inference of Diverse Variant Types Integrating Bulk DNA-seq with Single-cell RNA-seq

Motivation

Reconstructing clonal lineage trees ("tumor phylogenetics") has become a core tool of cancer genomics. Earlier approaches based on bulk DNA sequencing (DNA-seq) have largely given way to single-cell DNA-seq (scDNA-seq), which offers far greater resolution for clonal substructure. Available data has lagged behind computational theory, though. While single-cell RNA-seq (scRNA-seq) has become widely available, scDNA-seq is still sufficiently costly and technically challenging to preclude routine use on large cohorts. This forces difficult tradeoffs between the limited genome coverage of scRNA-seq, limited availability of scDNA-seq, and limited clonal resolution of bulk DNA-seq. These limitations are especially problematic for studying structural variations and focal copy number variations that are crucial to cancer progression but difficult to observe in RNA-seq.

Results

We develop a method, TUSV-int, combining advantages of these various genomic technologies by integrating bulk DNA-seq and scRNA-seq data into a single deconvolution and phylogenetic inference computation while allowing for single nucleotide variant (SNV), copy number alteration (CNA) and structural variant (SV) data. We accomplish this by using integer linear programming (ILP) to deconvolve heterogeneous variant types and resolve them into a clonal lineage tree. We demonstrate improved deconvolution performance over comparative methods lacking scRNA-seq data or using more limited variant types. We further demonstrate the power of the method to better resolve clonal structure and mutational histories through application to a previously published DNA-seq/scRNA-seq breast cancer data set.

Availability

The source code for TUSV-int is available at https://github.com/CMUSchwartzLab/TUSV-INT.git.

Alcohol-associated liver cancer

Heavy alcohol intake induces a wide spectrum of liver diseases ranging from steatosis, steatohepatitis, cirrhosis, and HCC. Although alcohol consumption is a well-known risk factor for the development, morbidity, and mortality of HCC globally, alcohol-associated hepatocellular carcinoma (A-HCC) is poorly characterized compared to viral hepatitis-associated HCC. Most A-HCCs develop after alcohol-associated cirrhosis (AC), but the direct carcinogenesis from ethanol and its metabolites to A-HCC remains obscure. The differences between A-HCC and HCCs caused by other etiologies have not been well investigated in terms of clinical prognosis, genetic or epigenetic landscape, molecular mechanisms, and heterogeneity. Moreover, there is a huge gap between basic research and clinical practice due to the lack of preclinical models of A-HCC. In the current review, we discuss the pathogenesis, heterogeneity, preclinical approaches, epigenetic, and genetic profiles of A-HCC, and discuss the current insights into and the prospects for future research on A-HCC. The potential effect of alcohol on cholangiocarcinoma and liver metastasis is also discussed.

Prognostic Impact of EGFR Amplification and Visceral Pleural Invasion in Early Stage Pulmonary Squamous Cell Carcinomas Patients after Surgical Resection of Primary Tumor

Over the last few decades, an increasing amount of information has been accumulated on biomarkers in non-small cell lung cancer (NSCLC). Despite these advances, most biomarkers have been identified in the adenocarcinoma histological subtype (AC). However, the application of molecular-targeted therapies in the prognosis and treatment of SCC in the clinical setting is very limited, becoming one of the main focus areas in research. Here, we prospectively analyzed the frequency of numerical/structural abnormalities of chromosomes 5, 7, 8, 9, 13 and 22 with FISH in 48 pulmonary SCC patients. From a total of 12 probes, only abnormalities of the 7p12 and 22q12 chromosomal regions were identified as unique genetic variables associated with the prognosis of the disease. The study for these two chromosomal regions was extended to 108 patients with SCC. Overall, chromosome losses were observed more frequently than chromosome gains, i.e., 61% versus 19% of all the chromosome abnormalities detected. The highest levels of genetic amplification were detected for the 5p15.2, 7p12, 8q24 and 22q11 chromosome bands, of which several genes are potentially involved in the pathogenesis of SCC, among others, include the EGFR gene at chromosome 7p12. Patients who displayed EGFR amplification (n = 13; 12%) were mostly older than 65 years (p = 0.07) and exclusively patients in early T-primary tumor stage (pT1−pT2; p = 0.03) with a significantly shortened overall survival (OS) (p ≤ 0.001). Regarding prognosis, the clinical, biological, and histopathologic characteristics of the disease that displayed a significant adverse influence on OS in the univariate analysis included patients older than 65 years (p = 0.02), the presence of lymph node involvement (p = 0.005), metastasis (p = 0.01) and, visceral pleural invasion (VPI) at diagnosis (p = 0.04). EGFR amplification also conferred an adverse impact on patient OS in the whole series (p = 0.02) and especially in patients in early stages (pT1−pT2; p = 0.01). A multivariate analysis of the prognostic factors for OS showed that the most informative combination of independent variables to predict an adverse outcome was the presence of VPI and/or EGFR amplification (p < 0.001). Based on these two variables, a scoring system was built to stratify patients into low- (no adverse features: score 0; n = 69), intermediate- (one adverse feature: score 1; n = 29) and high-risk (two adverse features: score 2; n = 5) groups, with significantly different (p = 0.001) OS rates at 50 months, which were as following: 32%, 28% and 0%, respectively. In the present study, we show that the presence of a high level of 7p12 (EGFR) amplification, exclusively detected in early stage SCC (pT1−pT2), is an independent adverse prognostic factor for OS. The identification of the EGFR gene copy number using FISH techniques may provide a more accurate diagnosis of high-risk populations after the complete resection of the primary tumor. When combined with VPI, three groups of pulmonary SCC were clearly identified that show the extent of the disease. This is of such importance that further prospective studies are necessary in larger series of SCC patients to be classified at the time of diagnosis. This could be achieved with the combined assessment of 7p12 amplification and VPI in primary tumor samples.

OUP accepted manuscript

MOTIVATION

Cancer develops through a process of clonal evolution in which an initially healthy cell gives rise to progeny gradually differentiating through the accumulation of genetic and epigenetic mutations. These mutations can take various forms, including single-nucleotide variants (SNVs), copy number alterations (CNAs) or structural variations (SVs), with each variant type providing complementary insights into tumor evolution as well as offering distinct challenges to phylogenetic inference.

RESULTS

In this work, we develop a tumor phylogeny method, TUSV-ext, which incorporates SNVs, CNAs and SVs into a single inference framework. We demonstrate on simulated data that the method produces accurate tree inferences in the presence of all three variant types. We further demonstrate the method through application to real prostate tumor data, showing how our approach to coordinated phylogeny inference and clonal construction with all three variant types can reveal a more complicated clonal structure than is suggested by prior work, consistent with extensive polyclonal seeding or migration.

AVAILABILITY AND IMPLEMENTATION

https://github.com/CMUSchwartzLab/TUSV-ext.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.