Evidence map›Paper›PMID 42801661›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Integrated Multi-Omics Reveals Cellular States and Microenvironmental Remodeling in Coexisting DCIS and IDC.

Ning Zhang, Tong Wan, Siyue Zhang, Yunzhen Jiang, Peng Su, Jixin Liu, Zhitong Chen, Jie Hao, Haoyu Wang, Bing Chen and 9 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Ning Zhang *Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Ji'nan, China.ORCID https://orcid.org/0000-0002-6430-4236
Tong Wan *Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Ji'nan, China.
Siyue Zhang *Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Ji'nan, China.
Yunzhen JiangCheong Kun Lun College, University of Macau, Macau, China.
Peng SuDepartment of Pathology, Qilu Hospital of Shandong University, Ji'nan, China.
Jixin LiuSchool of Mathematics, Shandong University, Ji'nan, China.ORCID https://orcid.org/0009-0001-8133-8956
Zhitong ChenSchool of Mathematics, Shandong University, Ji'nan, China.
Jie HaoDepartment of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Ji'nan, China.
Haoyu WangDepartment of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Ji'nan, China.ORCID https://orcid.org/0009-0009-5435-8458
Bing ChenBiological Resource Center, Qilu Hospital of Shandong University, Ji'nan, China.
Wenjing ZhaoBiological Resource Center, Qilu Hospital of Shandong University, Ji'nan, China.ORCID https://orcid.org/0000-0003-4477-596X
Lijuan WangBiological Resource Center, Qilu Hospital of Shandong University, Ji'nan, China.ORCID https://orcid.org/0000-0002-7885-9945
Tao XingDepartment of Radiation Oncology, Townsville University Hospital, Townsville, Australia.ORCID https://orcid.org/0000-0001-5064-3408
Qihuang ZhangDepartment of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, McGill University, Montreal, Canada.ORCID https://orcid.org/0000-0003-1455-2159
Ulf SchmitzComputational Biomedicine Lab, College of Science and Engineering, James Cook University, Townsville, Australia.ORCID https://orcid.org/0000-0001-5806-4662
Zhiyong DingMills Institute for Personalized Cancer Care, Fynn Biotechnologies Ltd., Ji'nan, China.ORCID https://orcid.org/0000-0003-0151-0822
Nicola CrosettoDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-3019-6978
Bingqiang LiuSchool of Mathematics, Shandong University, Ji'nan, China.ORCID https://orcid.org/0000-0002-5734-1135
Qifeng YangDepartment of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Ji'nan, China.ORCID https://orcid.org/0000-0003-0576-8513

Funding

Cheeloo Young Scholar Program of Shandong UniversityFoundation from Clinical Research Center of Shandong University 2020SDUCRCA015National Key Research and Development Program 2020YFA0712400National Natural Science Foundation of China 82373005National Natural Science Foundation of China 82373267National Natural Science Foundation of China 82573211Natural Science Foundation of Shandong Province ZR2024MH002Special Foundation for Taishan Scholars tstp20250509Special Support Plan for National High Level Talents W01020103
6 · The paper itself

Abstract

Ductal carcinoma in situ (DCIS) is a non-invasive precursor of invasive ductal carcinoma (IDC), yet the biological mechanisms underlying the transition from DCIS to IDC remain incompletely understood. Here, we integrate spatial transcriptomics, single-cell RNA sequencing, and single-cell DNA sequencing on coexisting DCIS and IDC samples to characterize cellular and microenvironmental alterations. Integrated analyses reveal differential molecular characterizations between coexisting DCIS and IDC and identify candidate genes (MGP, PLAT, and SERPINA3) potentially limiting the progression from DCIS to IDC. Malignant epithelial meta-programs (MPs) delineate distinct transcriptional states, with development-associated MP1 enriched in DCIS and cell cycle-related MP5 enriched in IDC. Further analysis reveals varied microenvironmental features in DCIS and IDC, with invasion-associated Mph_SPP1 and development-associated iCAFs_HOPX enriched in DCIS, while immunosuppressive Mph_PRDM1 and metabolism-related tCAFs_BNIP3 predominate in IDC. We then construct a machine learning model to identify DCIS at high risk of progression, which is externally validated across independent bulk RNA-sequencing cohorts (mean AUC = 0.903). Collectively, this study provides an integrative framework for understanding the molecular and spatial features that distinguish DCIS from IDC, with the potential to inform more precise risk stratification and clinical management for DCIS progression.

Indexed as

ductal carcinoma in situinvasive ductal carcinomamachine learningmulti‐omics integrationsingle‐cell sequencingspatial transcriptomics

Identifiers

PMID42801661
PMCPMC13616352

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.