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RET signaling as a mediator of estrogen receptor positive breast cancer brain metastasis.

Code ↔ Paper

3 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 3 matches · 1 of them tie a paragraph to a whole file, not to given lines: a weak match, whose lines are not tinted
  1. [1] § Methods › Analysis of gene expression from published & public datasets ↔ codes/02_Figure 1fg.ipynb, lines 59–93 · score 0.90 · disease free survival, surv_categorize, surv_cutpoint, PAM50 subtype, LumA, coxph
  2. [2] § Methods › Reverse phase protein array (RPPA) ↔ 2-Analysis/Helper_Scripts/21_Fig4_SupFig11_DNAm_Alterations.R, lines 313–434 · score 0.62 · logFC, limma package, linear, log2, vector, models
  3. [3] § Methods › In vivo xenograft study ↔ index/libs/bootstrap/bootstrap.min.js, the whole file · a weak match · score 0.60 · dimensions, placement, body, pre, pad, window

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

Jupyter notebook · 137 lines · 3.9 KB · no license · 1 match

  1. # %% [markdown]
  2. # # Header
  4. # %%
  5. library(GSVA)
  6. library("survminer")
  7. library(dplyr)
  8. require("survival")
  9. library(gtools)
  11. # %%
  12. parse_gmt = function(gmt_path){
  13. db = readLines(gmt_path)
  14. geneset = list()
  15. for (line in db){
  16. line =
  17. words = as.vector(strsplit(line, "\\s{1,}")[[1]])
  18. set_name = words[1]
  19. genes = words[-c(1,2)]
  20. geneset[[set_name]] = genes
  21. }
  22. return(geneset)}
  26. coxConvert = function(x){ x <- summary(x)
  27. p.value<-signif(x$wald["pvalue"], digits=2)
  28. wald.test<-signif(x$wald["test"], digits=2)
  29. beta<-signif(x$coef[1], digits=2);#coeficient beta
  30. HR <-signif(x$coef[2], digits=2);#exp(beta)
  31. HR.confint.lower <- signif(x$conf.int[,"lower .95"], 2)
  32. HR.confint.upper <- signif(x$conf.int[,"upper .95"],2)
  33. HR <- paste0(HR, " (",
  34. HR.confint.lower, "-", HR.confint.upper, ")")
  35. res<-c(beta, HR, wald.test, p.value)
  36. names(res)<-c("beta", "HR (95% CI for HR)", "wald.test",
  37. "p.value")
  38. return(res)
  39. }
  41. # %%
  42. setwd('../')
  44. # %% [markdown]
  45. # # Load data
  47. # %%
  48. df = read.csv('data/metabric/nolan.surv.expr.csv', row.names = 1, check.names = F)
  49. expr = t(df[,8:19496])
  51. # %%
  52. dbpath = 'data/geneset/GDNF.gmt'
  53. geneset = parse_gmt(dbpath)
  55. resPrefix = 'data/gsva/Metabric_GDNF'
  56. #res = gsva(expr, geneset, method='gsva')
  57. #write.csv(res, file=paste(resPrefix, '.gsva.csv', sep=''), quote=F)
  59. # %% [markdown]
  60. # # ER+, GDNF
  62. # %%
  63. gsva = as.data.frame(t(read.csv('data/gsva/Metabric_GDNF.gsva.csv', check.names = F, row.names = 1)))
  64. GDNF = gsva[,1] - gsva[,2] # Up minus Dn
  65. gsva$GDNF = GDNF
  67. base = df[,1:12]
  68. gsva = gsva[rownames(base),]
  70. base$Sig = gsva$GDNF
  72. # ER pos and LumA
  73. ## select
  74. plot.dat = base[base[,"ER_IHC_status"]=='pos',] #& base[,"NOT_IN_OSLOVAL_Pam50Subtype"]=='LumA',]
  76. ########## ssgsea
  77. x.cut= surv_cutpoint(plot.dat, time="DSS.time", event="DSS.status", variables="Sig")
  78. x.cat <- surv_categorize(x.cut)
  79. plot.dat$cat = x.cat$Sig
  81. cox <- coxph(Surv(DSS.time, DSS.status) ~ Sig, data = plot.dat)
  82. print(summary(cox))
  84. res.cox = coxConvert(cox)
  85. print(res.cox)
  86. # beta HR (95% CI for HR) wald.test p.value
  87. # "0.57" "1.8 (1.4-2.2)" "26" "3.5e-07"
  88. fit <- survfit(Surv(DSS.time, DSS.status) ~ Sig, data = x.cat)
  89. g = ggsurvplot(fit, risk.table = TRUE, pval = TRUE, conf.int = FALSE, risk.table.height = 0.4)
  90. g$plot = g$plot + labs(y = "Disease Free Survival")
  91. pdf('plots/Metabric.DSS.GDNF_gsva.pdf', width=4.8, height=4, onefile=F)
  92. print(g)
  93. dev.off()
  95. # %% [markdown]
  96. # # ER+, RET
  98. # %%
  99. # gsva
  100. gsva = as.data.frame(t(read.csv('data/gsva/Metabric_GDNF.gsva.csv', check.names = F, row.names = 1)))
  101. GDNF = gsva[,1] - gsva[,2] # Up minus Dn
  102. gsva$GDNF = GDNF
  104. base = df[,1:12]
  105. gsva = gsva[rownames(base),]
  107. #--------
  108. # gsva
  109. RET = df$RET # Up minus Dn
  110. base = df[,1:12]
  111. base$Sig = RET
  113. # ER pos and LumA
  114. ## select
  115. plot.dat = base[base[,"ER_IHC_status"]=='pos',] #& base[,"NOT_IN_OSLOVAL_Pam50Subtype"]=='LumA',]
  117. ########## ssgsea
  118. x.cut= surv_cutpoint(plot.dat, time="DSS.time", event="DSS.status", variables="Sig")
  119. x.cat <- surv_categorize(x.cut)
  120. plot.dat$cat = x.cat$Sig
  122. cox <- coxph(Surv(DSS.time, DSS.status) ~ Sig, data = plot.dat)
  123. print(summary(cox))
  125. res.cox = coxConvert(cox)
  126. print(res.cox)
  127. # beta HR (95% CI for HR) wald.test p.value
  128. # "-0.0085" "0.99 (0.91-1.1)" "0.04" "0.85"
  129. fit <- survfit(Surv(DSS.time, DSS.status) ~ Sig, data = x.cat)
  130. g = ggsurvplot(fit, risk.table = TRUE, pval = TRUE, conf.int = FALSE, risk.table.height = 0.4)
  131. g$plot = g$plot + labs(y = "Disease Free Survival")
  132. pdf('plots/Metabric.DSS.RET.pdf', width=4.8, height=4, onefile=F)
  133. print(g)
  134. dev.off()
  136. # %%

02_Figure 1fg.ipynb at commit a9f7018, no license · at the source

Overview

Authors: Simeng Liu1,2,3, Geoffrey Pecar1,4, Ye Cao1,2,3, Fangyuan Chen1,2,3, Abdalla Wedn1,5, Osama S Shah1,4, Jennifer M Atkinson1,4, Jagmohan Hooda1,4, Steffi Oesterreich1,4, Adrian V Lee1,4
ORCID iDs: Geoffrey Pecar, Jagmohan Hooda, Steffi Oesterreich, Adrian V Lee
  1. Women’s Cancer Research Center, UPMC Hillman Cancer Center and Magee-Womens Research Institute, Pittsburgh, PA USA
  2. School of Medicine, Tsinghua University, Beijing, China
  3. School of Medicine, University of Pittsburgh, Pittsburgh, PA USA
  4. Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA USA
  5. Molecular Pharmacology Graduate Program (MPGP), University of Pittsburgh, Pittsburgh, PA USA
Institutions: University of Pittsburgh (United States); Magee-Womens Research Institute (United States); UPMC Hillman Cancer Center (United States); Tsinghua University (China); Magee-Womens Hospital (United States); University of Pittsburgh Medical Center (United States)
Journal: Communications biology, volume 9, issue 1, article 1209
Dates: received 25 August 2025; accepted 4 May 2026; published online 21 May 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s42003-026-10252-6 · PMID 42162219 · PMCID PMC13582822 · OpenAlex W7161753235
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), mouse (organism), other condition (population), cellular / molecular (subfield)
Methods: Statistics, Machine learning, Connectivity, Preprocessing
Keywords: Breast cancer, Metastasis
MeSH: Brain Neoplasms*, Breast Neoplasms*, Proto-Oncogene Proteins c-ret*, Receptors, Estrogen*, Signal Transduction*, Animals, Cell Line, Tumor, Female, Gene Expression Regulation, Neoplastic, Glial Cell Line-Derived Neurotrophic Factor, Humans, Mice (* major topic)
Topic: Brain Metastases and Treatment (Pulmonary and Respiratory Medicine, Medicine), according to OpenAlex
Funding: NIH HHS (S10 OD028483); NCI NIH HHS (P30 CA047904, P30 CA016672)
Citations: not cited yet (Europe PMC); 70 references in the paper
Research resources: MCF-7 RRID:CVCL_0031, HEK293T RRID:CVCL_0063, T-47D RRID:CVCL_0553, MDA-MB-134-VI RRID:CVCL_0617, RRID:SCR_006307

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repositories

Its files are read in the Code ↔ Paper reader above, with 3 matches between paragraphs and lines of code.

ChelseaCHENX/RET-Brain-Metastasis-Analysis

License: none: the authors keep all their rights
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: a9f7018cf334233973b8d432f16b893292b73425, 5 September 2025
Languages: Jupyter (4), R (1), Python (1)
Size: 27 files, 6 scripts
Software Heritage: not archived
Found in: the text, “Analysis of gene expression from published & pub”
Holds: README, 4 notebooks
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Matplotlib (2 files), seaborn (2 files), survival (2 files), tidyverse (2 files), anndata (1 file), NumPy (1 file), pandas (1 file)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
7 files
At the source: github.com/ChelseaCHENX/RET-Brain-Metastasis-Analysis

leeoesterreich/ILC_CellLine_Encyclopedia

License: Apache-2.0
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: c7aace899dfbf96a78c3b82081fc983068b3067c, 18 February 2026
Languages: R (43), JavaScript (16)
Size: 286 files, 59 scripts
Software Heritage: not archived
Found in: the text, “Analysis of gene expression from published & pub”
Holds: README, license file, 1 notebook
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Tools: tidyverse (20 files), ComplexHeatmap (15 files), ggplot2 (15 files), reshape2 (9 files), circlize (8 files), ggpubr (5 files), limma (3 files), data.table (2 files), clusterProfiler (1 file), DESeq2 (1 file), patchwork (1 file), pheatmap (1 file)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
61 files
At the source: github.com/leeoesterreich/ILC_CellLine_Encyclopedia

leeoesterreich/RET_Project_Analysis

License: none: the authors keep all their rights
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: 2db5d19a3e78a4f6a95193b8df071bd200611021, 15 September 2025
Languages: R (1)
Size: 6 files, 1 script
Software Heritage: not archived
Found in: the text, “Analysis of gene expression from published & pub”
Holds: README, 1 notebook
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: circlize (1 file), ComplexHeatmap (1 file)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
2 files
At the source: github.com/leeoesterreich/RET_Project_Analysis

leeoesterreich/RET-Brain-Metastasis-Analysis-Geoff

License: none: the authors keep all their rights
State: the link is dead, verified on 28 September 2026
Evidence: found in the paper
Software Heritage: not archived
Found in: “Code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 28 September 2026: the link is dead
  • 28 September 2026: the link is dead
At the source: github.com/leeoesterreich/RET-Brain-Metastasis-Analysis-Geoff

Zenodo 19501083

License: CC-BY-4.0
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Matplotlib (2 files), seaborn (2 files), survival (2 files), tidyverse (2 files), anndata (1 file), NumPy (1 file), pandas (1 file)
Availability: 1 check, the latest on 28 September 2026: the link answers (HTTP 200)
  • 28 September 2026: the link answers (HTTP 200)
7 files
At the source: zenodo.org/records/19501083

Code availability statement

The paper has a code availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1038/s42003-026-10252-6.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 5 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 72 scripts, each with its path and the digest of its content;
  • 3 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

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Data availability statement

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  • no repository, dataset or request procedure was recognized in it

Read it in the paper: doi.org/10.1038/s42003-026-10252-6.

Versions

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Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 10 authors, 2 keywords, 12 MeSH terms, 2 funders, 68 references, 5 RRIDs.

Cite

This paper

Liu, S., Pecar, G., Cao, Y., Chen, F., Wedn, A., Shah, O. S., Atkinson, J. M., Hooda, J., Oesterreich, S., & Lee, A. V. (2026). RET signaling as a mediator of estrogen receptor positive breast cancer brain metastasis. Communications biology, 9(1), 1209. https://doi.org/10.1038/s42003-026-10252-6

BibTeX

@article{liu2026ret,
author = {Liu, Simeng and Pecar, Geoffrey and Cao, Ye and Chen, Fangyuan and Wedn, Abdalla and Shah, Osama S and Atkinson, Jennifer M and Hooda, Jagmohan and Oesterreich, Steffi and Lee, Adrian V},
title = {{RET signaling as a mediator of estrogen receptor positive breast cancer brain metastasis}},
journal = {Communications biology},
year = {2026},
month = may,
volume = {9},
number = {1},
pages = {1209},
publisher = {Nature Publishing Group},
issn = {2399-3642},
doi = {10.1038/s42003-026-10252-6},
url = {https://doi.org/10.1038/s42003-026-10252-6},
pmid = {42162219},
pmcid = {PMC13582822}
}

RIS

TY - JOUR
AU - Liu, Simeng
AU - Pecar, Geoffrey
AU - Cao, Ye
AU - Chen, Fangyuan
AU - Wedn, Abdalla
AU - Shah, Osama S
AU - Atkinson, Jennifer M
AU - Hooda, Jagmohan
AU - Oesterreich, Steffi
AU - Lee, Adrian V
TI - RET signaling as a mediator of estrogen receptor positive breast cancer brain metastasis
T2 - Communications biology
J2 - Commun Biol
PY - 2026
DA - 2026/05/21
VL - 9
IS - 1
SP - 1209
SN - 2399-3642
PB - Nature Publishing Group
DO - 10.1038/s42003-026-10252-6
UR - https://doi.org/10.1038/s42003-026-10252-6
LA - en
ER -

CSL-JSON

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"author": [
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"family": "Liu",
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