Evidence map›Paper›PMID 33522069›Full record

ArticleCell proliferation2021

Tumour microenvironment-based molecular profiling reveals ideal candidates for high-grade serous ovarian cancer immunotherapy.

Xiaofan Lu, Caoyu Ji, Liyun Jiang, Yue Zhu, Yujie Zhou, Jialin Meng, Jun Gao, Tao Lu, Junmei Ye, Fangrong Yan

Open access · goldAbstract read
In one paragraph

Article in Cell proliferation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.3field-weighted citation impact, top 17% of its field
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

15 citing papers in PubMed, 17 citations in OpenAlex.

  1. A prognostic model based on ScissorTranslational cancer research · 2026
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  5. Identifying Explainable Machine Learning Models and a Novel SFRP2International journal of molecular sciences · 2023
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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

10 authors at 3 institutions in 2 countries.

Xiaofan LuState Key laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China.
Caoyu JiState Key laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China.
Liyun JiangState Key laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China.
Yue ZhuState Key laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China.
Yujie ZhouDivision of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
Jialin MengDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Jun GaoState Key laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China.
Tao LuState Key laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China.
Junmei YeState Key laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China.
Fangrong YanState Key laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China.
China Pharmaceutical University · CNFirst Affiliated Hospital of Anhui Medical University · CNShanghai Jiao Tong University · CN

Funding

Key R&D Program of Jiangsu Province [Social Development] BE2020694National Key R&D Program of China 2019YFC1711000National Natural Science Foundation of China 81973145
6 · The paper itself

Abstract

objectiveDue to limited immunological profiles of high-grade serous ovarian cancer (HGSOC), we aimed to characterize its molecular features to determine whether a specific subset that can respond to immunotherapy exists. MATERIALS AND

methodsA training cohort of 418 HGSOC samples from TCGA was analysed by consensus non-negative matrix factorization. We correlated the expression patterns with the presence of immune cell infiltrates, immune regulatory molecules and other genomic or epigenetic features. Two independent cohorts containing 482 HGSOCs and in vitro experiments were used for validation.

resultsWe identified immune and non-immune groups where the former was enriched in signatures that reflect immune cells, infiltration and PD-1 signalling (all, P < 0.001), and presented with a lower chromosomal aberrations but increased neoantigens, tumour mutation burden, and microsatellite instability (all, P < 0.05); this group was further refined into two microenvironment-based subtypes characterized by either immunoactivation or carcinoma-associated fibroblasts (CAFs) and distinct prognosis. CAFs-immune subtype was enriched for factors that mediate immunosuppression and promote tumour progression, including highly expressed stromal signature, TGF-β signalling, epithelial-mesenchymal transition and tumour-associated M2-polarized macrophages (all, P < 0.001). Robustness of these immune-specific subtypes was verified in validation cohorts, and in vitro experiments indicated that activated-immune subtype may benefit from anti-PD1 antibody therapy (P < 0.05).

conclusionOur findings revealed two immune subtypes with different responses to immunotherapy and indicated that some HGSOCs may be susceptible to immunotherapies or combination therapies.

Indexed as

Biomarkers, TumorCystadenocarcinoma, SerousEpithelial-Mesenchymal TransitionFemaleGene Expression ProfilingHumansImmunotherapyOvarian NeoplasmsPrognosisTumor MicroenvironmentBiomarkers, Tumorhigh-grade serous ovarian cancerimmune-specific subtypeimmunotherapy responsemolecular classificationtumour immune microenvironment

Identifiers

PMID33522069
PMCPMC7941229
OpenAlexW3128826539

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.