cfDNA fragmentation features reflect underlying tumor biology in pancreatic cancer
Last updated: 2025-03-27
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Fraction of CNV changes by chromosomal arm for PDAC cancers in TCGA are shown alongside assessment of copy number changes in CheckPAC patients, as quantified by the median log-ratio by arm for tumor copy number gains and losses and z-scores by arm for all patients with plasma samples at baseline, and at follow-up for each of the clinical RECIST 1.1 response categories.
library(tidyverse)
library(readxl)
library(data.table)
library(RColorBrewer)
library(here)
devtools::load_all(here("code/liver.tools"))
source(here("code/functions.R"))# Load TCGA data
fig.data <- readRDS(here("data/fig2c_p2_data.rds"))
# Update liver to pancreas at the source
# Load CNV data from FACETS
fnames <- list.files(here("data/estimates"), pattern=".tsv$")
noares <- fnames %>%
file.path(here("data/estimates"), .) %>%
map_dfr(get_cnv)
# Load DELFI features
features <- read_csv(here("data/checkpac_features.csv"))New names:
Rows: 228 Columns: 987
── Column specification
──────────────────────────────────────────────────────── Delimiter: "," chr
(1): id dbl (986): ...1, zscore_10p, zscore_10q, zscore_11p, zscore_11q,
zscore_12p,...
ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
Specify the column types or set `show_col_types = FALSE` to quiet this message.
• `` -> `...1`clean_data<-read_excel(here("data/supplementary_tables.xlsx"), sheet="Table S1",range="A2:X45")
delfi_pred<-read_excel(here("data/supplementary_tables.xlsx"), sheet="Table S2",range="A2:P219")
delfi_pred<-delfi_pred %>% filter(Timepoint!="follow up", Timepoint!="cycle 1")
DELFI_complete<-inner_join(delfi_pred,clean_data, by="Patient")# TCGA panel
setDT(fig.data)
fig.data[,bin:=as.factor(rev(bin))][] seqnames pos arm bin variable value disease change
<fctr> <num> <fctr> <fctr> <fctr> <num> <char> <char>
1: chr1 7500000 1p 473 liver.Loss -0.086956522 liver Loss
2: chr1 17500000 1p 472 liver.Loss -0.092391304 liver Loss
3: chr1 22500000 1p 471 liver.Loss -0.092391304 liver Loss
4: chr1 27500000 1p 470 liver.Loss -0.097826087 liver Loss
5: chr1 32500000 1p 469 liver.Loss -0.086956522 liver Loss
---
942: chr22 27500000 22q 5 liver.Gain 0.005434783 liver Gain
943: chr22 32500000 22q 4 liver.Gain 0.010869565 liver Gain
944: chr22 37500000 22q 3 liver.Gain 0.016304348 liver Gain
945: chr22 42500000 22q 2 liver.Gain 0.016304348 liver Gain
946: chr22 47500000 22q 1 liver.Gain 0.000000000 liver Gainfig.data$disease<-"TCGA Pancreatic Cancers\n "
tcga <- fig.data %>%
mutate(disease="TCGA Pancreatic Cancers\n ") %>%
ggplot(aes(x=value, y=bin, color=change, fill=change)) +
facet_grid(arm~disease, scales = 'free_y') +
geom_col() +
scale_x_continuous() +
scale_fill_manual(values=c("#FF6636","#66CCCC"))+
scale_colour_manual(values=c("#FF6636","#66CCCC"))+
theme_minimal(base_size=24) +
theme(strip.text.y = element_text(angle = 0,
hjust = 0.5,
vjust = 0.5,
size=20),
strip.text.x=element_text(size=20),
axis.text.y = element_blank(),
axis.ticks = element_blank(),
panel.grid = element_blank(),
legend.title = element_blank(),
legend.position="bottom") +
xlab("Proportion of\ncases with CNV") +
ylab("Chromosome Arm")
# Tumor panel
noares1 <- noares %>%
mutate(colors= case_when((cnv_score>=.05) ~ "Positive",
(cnv_score>=(-.05)) ~ "Neutral",
(cnv_score<(-.05)) ~ "Negative"))
noares1$colors<-factor(noares1$colors, levels=c("Positive","Neutral","Negative"))
noares1 <- noares1 %>% mutate(transp=if_else(colors=="Neutral",1,1))
noares1$y=1
noares1<-noares1 %>% rename(Arm= chrarm)
noares1 <- noares1 %>%rename(id=ID)
noares1<-noares1 %>% mutate(BOR="Tumor")
noares1 <- noares1 %>%
rename(z=cnv_score) %>%
mutate(root2=nroot(z, 2)) %>%
mutate(root3=nroot(z, 3))
noares2<-noares1 %>% mutate(source="Tumor")
# Plasma panel
DELFI_complete$id<-DELFI_complete$Sample
DELFI_complete<-DELFI_complete %>% mutate(BOR = case_when((Timepoint == "Baseline") ~ "Baseline",
TRUE ~ `BOR RECIST 1.1`))
DELFI_complete<-DELFI_complete %>% filter(`BOR RECIST 1.1`!="Not Evaluable")
cols <- c("#FF6636","#66CCCC","#FFCC66","#FFCC66","#66CCCC","#FFFF00","#FF9900")
features <- features %>% select(id,starts_with("z"))
features <- inner_join(features, DELFI_complete %>%
select(id,BOR),
by=c("id"="id"))
features <- features %>%
gather(key="Arm", value="Zscore", starts_with("z"))
features$Arm <- sapply( str_split(features$Arm,"_"), "[", 2 )
chrlevels <- c("1p","1q","2p","2q","3p","3q","4p","4q","5p",
"5q","6p","6q","7p","7q","8p","8q","9p","9q",
"10p","10q","11p","11q","12p","12q",
"13q","14q","15q","16p","16q","17p","17q",
"18p","18q","19p","19q","20p","20q","21q","22q")
features$Arm <- factor(features$Arm,
levels = chrlevels)
features <- features %>% mutate(colors=if_else(Zscore<=0,"Negative","Positive"))
features <- features %>%
mutate(colors=if_else(Zscore>= -3.22 & Zscore <= 3.22 ,
"Neutral", features$colors))
features <- features %>% mutate(transp=if_else(colors=="Neutral",1,1))
features$colors<-factor(features$colors,levels=c("Positive","Negative","Neutral"))
features$y=1
features <- features %>% mutate(Zscore=if_else(Zscore<=-150,-150,Zscore))
features <- features %>% mutate(Zscore=if_else(Zscore>150,150,Zscore))
features2 <- features %>%
rename(z=Zscore) %>%
mutate(root2=nroot(z, 2)) %>%
mutate(root3=nroot(z, 3))
features2<-features2 %>%mutate(source="Plasma")
# Combine tumor and plasma data
features3<-rbind(features2, noares2) %>%
mutate(BOR = factor(BOR, levels = c("Tumor", "Baseline", "Progressive Disease",
"Stable Disease", "Partial Response")))
# Restrict data to -150 to 150 for plasma and -1.5 to 1.5 for tumor
xaxis_lim <- tibble(id = paste(rep("DUMMY", 10), 1:10),
BOR = factor(rep(levels(features3$BOR), each = 2),
levels = levels(features3$BOR)),
Arm = factor("1p", levels = chrlevels),
colors = factor(rep(c("Negative", "Positive"), 5),
levels = levels(features3$colors)),
z = c(c(-1.5, 1.5),
rep(c(-150, 150), 4)),
transp = 0,
y = 1)
ns <- features3 %>%
group_by(BOR) %>%
summarize(n=length(unique(id))) %>%
mutate(label=paste0(BOR, "\n(n = ", n, ")"))
ns <- setNames(ns$label, ns$BOR)
jhu <- features3 %>%
bind_rows(xaxis_lim) %>%
ggplot(aes(x=y, y=z, color=colors, alpha=transp)) +
geom_point(size=5) +
facet_grid(Arm ~ BOR, labeller=labeller(BOR=ns), scales = "free_x") +
coord_flip() +
theme_minimal(base_size=24) +
theme(strip.text.y.left = element_text(angle = 0,
hjust = 0.5,
vjust = 0.5),
axis.text.y = element_blank(),
axis.ticks = element_blank(),
panel.grid = element_blank(),
plot.title = element_blank(),
legend.title = element_blank(),
axis.title.y=element_blank(),
legend.position = "bottom",
strip.text.y = element_blank()) +
scale_y_continuous() +
scale_alpha_identity() +
scale_fill_manual(values = cols) +
scale_color_manual(values = cols) +
ylab("Z-Score")
cowplot::plot_grid(tcga, jhu, nrow = 1, rel_widths = c(1, 2.5), align = "h")
sessionInfo()R version 4.4.1 (2024-06-14)
Platform: aarch64-apple-darwin20
Running under: macOS 15.3.1
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: America/New_York
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] liver.tools_0.0.0.9000 here_1.0.1 RColorBrewer_1.1-3
[4] data.table_1.17.0 readxl_1.4.5 lubridate_1.9.4
[7] forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4
[10] purrr_1.0.4 readr_2.1.5 tidyr_1.3.1
[13] tibble_3.2.1 ggplot2_3.5.1 tidyverse_2.0.0
[16] workflowr_1.7.1
loaded via a namespace (and not attached):
[1] tidyselect_1.2.1 farver_2.1.2 fastmap_1.2.0 promises_1.3.2
[5] digest_0.6.37 timechange_0.3.0 mime_0.12 lifecycle_1.0.4
[9] ellipsis_0.3.2 processx_3.8.6 magrittr_2.0.3 compiler_4.4.1
[13] rlang_1.1.5 sass_0.4.9 tools_4.4.1 yaml_2.3.10
[17] knitr_1.49 labeling_0.4.3 htmlwidgets_1.6.4 bit_4.6.0
[21] pkgbuild_1.4.6 pkgload_1.4.0 miniUI_0.1.1.1 withr_3.0.2
[25] desc_1.4.3 grid_4.4.1 urlchecker_1.0.1 git2r_0.35.0
[29] profvis_0.4.0 xtable_1.8-4 colorspace_2.1-1 scales_1.3.0
[33] cli_3.6.4 rmarkdown_2.29 crayon_1.5.3 generics_0.1.3
[37] remotes_2.5.0 rstudioapi_0.17.1 httr_1.4.7 tzdb_0.4.0
[41] sessioninfo_1.2.3 cachem_1.1.0 parallel_4.4.1 cellranger_1.1.0
[45] vctrs_0.6.5 devtools_2.4.5 jsonlite_1.9.1 callr_3.7.6
[49] hms_1.1.3 bit64_4.6.0-1 jquerylib_0.1.4 rematch_2.0.0
[53] glue_1.8.0 ps_1.9.0 cowplot_1.1.3 stringi_1.8.4
[57] gtable_0.3.6 later_1.4.1 munsell_0.5.1 pillar_1.10.1
[61] htmltools_0.5.8.1 R6_2.6.1 rprojroot_2.0.4 vroom_1.6.5
[65] evaluate_1.0.3 shiny_1.10.0 memoise_2.0.1 httpuv_1.6.15
[69] bslib_0.9.0 Rcpp_1.0.14 whisker_0.4.1 xfun_0.51
[73] fs_1.6.5 usethis_3.1.0 getPass_0.2-4 pkgconfig_2.0.3