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Received — 4 April 2026 ⏭ Nature Cancer
  • ✇Nature Cancer
  • Harnessing foundation models for digital pathology without re-training Zhiping Xiao · Sheng Wang
    Nature Cancer, Published online: 03 April 2026; doi:10.1038/s43018-025-01108-9Applications of digital pathology in clinical oncology have largely depended on the requirement for labeled data and model re-training. A study now presents PRET, a training-free framework with robust performance for pan-cancer diagnosis that adapts pathology foundation models to diverse tasks at inference stage, from screening and subtyping tasks to segmentation and metastasis detection tasks.
     
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Harnessing foundation models for digital pathology without re-training

✇Nature Cancer
By: Zhiping Xiao · Sheng Wang
3 April 2026 at 08:00

Nature Cancer, Published online: 03 April 2026; doi:10.1038/s43018-025-01108-9

Applications of digital pathology in clinical oncology have largely depended on the requirement for labeled data and model re-training. A study now presents PRET, a training-free framework with robust performance for pan-cancer diagnosis that adapts pathology foundation models to diverse tasks at inference stage, from screening and subtyping tasks to segmentation and metastasis detection tasks.

A tumor-derived metabolite primes the leptomeningeal pre-metastatic niche

✇Nature Cancer
By: Shi Li · Cyrus M. Ghajar
3 April 2026 at 08:00

Nature Cancer, Published online: 03 April 2026; doi:10.1038/s43018-026-01138-x

Leptomeningeal metastases are a devastating complication of solid tumors; how this niche becomes pro-metastatic remains poorly understood. A study now reveals that tumor cells prime a pre-metastatic niche within the leptomeninges via exosome-derived 5-HIAA, triggering vascular leakiness and accumulation of disseminated tumor cells.

Leptomeningeal metastatic cancer cells induce a permissive choroid plexus vasculature through extracellular-vesicle-derived 5-HIAA signaling

✇Nature Cancer
By: Yang Huang · Yifan Hou · Jiahui Yang · Wanqi Yang · Hanxin Liu · Haibao Peng · Xiaohui Li · Jiaxu Zhao · Ye Zhang · Rui Zeng · Youming Zeng · Cheng Li · Qiangqiang Zhang · Yudan Chi
3 April 2026 at 08:00

Nature Cancer, Published online: 03 April 2026; doi:10.1038/s43018-026-01145-y

Huang, Hou, Yang et al. demonstrate that leptomeningeal metastatic cells favor the formation of a premetastatic niche by remodeling the choroid plexus vasculature through the serotonin metabolite 5-hydroxyindoleacetic acid, which signals into endothelial cells through the aryl hydrocarbon receptor.

PRET is a few-shot system for pan-cancer recognition without example training

✇Nature Cancer
By: Yi Li · Ziyu Ning · Tianqi Xiang · Qixiang Zhang · Zhihao Lin · Min Yi · Feiyan Feng · Baozhen Zeng · Xuexia Qian · Lu Sun · Jiace Qin · Ling Xiang · Chao Fan · Tian Qin · Qian Wang · Xiu-Wu Bian · Kun-Hsing Yu · Kang Zhang · Qingling Zhang · Xiaomeng Li
3 April 2026 at 08:00

Nature Cancer, Published online: 03 April 2026; doi:10.1038/s43018-026-01141-2

Li et al. present PRET, a few-shot system for pan-cancer detection not requiring model fine-tuning, validated it in multicenter datasets and found that it outperformed existing approaches across tasks and pathologists in lymph node metastasis detection.

Single-cell and spatial profiling in cancer biology and clinical oncology

✇Nature Cancer
By: Chris J. Frangieh · Joy Linyue Fan · Johannes C. Melms · Parin Shah · Elham Azizi · Benjamin Izar
3 April 2026 at 08:00

Nature Cancer, Published online: 03 April 2026; doi:10.1038/s43018-026-01142-1

Izar and colleagues review the insights into cancer biology gained via single-cell analyses and spatial profiling and overview the challenges and opportunities associated with the implementation of these approaches to guide clinical discovery.
Received — 2 April 2026 ⏭ Nature Cancer

Decoding pediatric brain tumors via CSF-derived methylomes

✇Nature Cancer
By: Camila S. Fang · Alexandra M. Miller
30 March 2026 at 08:00

Nature Cancer, Published online: 30 March 2026; doi:10.1038/s43018-026-01139-w

Cerebrospinal fluid (CSF)-derived cell-free DNA holds promise for CNS tumors, but its limited yield poses challenges. A study now presents M-PACT, a framework that uses sub-nanogram CSF-derived cell-free DNA methylomes for tumor classification, paving the way for minimally invasive diagnosis of pediatric brain tumors.
Received — 26 March 2026 ⏭ Nature Cancer

Reprogramming of stroma-derived chemokine networks drives the loss of tissue organization in nodal B cell lymphoma

✇Nature Cancer
By: Felix Czernilofsky · Anna Mathioudaki · Lea Jopp-Saile · Raphael Lutz · Dominik Vonficht · Xi Wang · Christina Schniederjohann · Harald Voehringer · Tobias Roider · Marc-Andrea Baertsch · Claus Rodemer · Henry Löffler-Wirth · Michael Grau · Donnacha Fitzgerald · Johannes Mammen · Jan Kosla · Nora Liebers · Peter-Martin Bruch · Diana Ordoñez-Rueda · Alexander Brobeil · Gunhild Mechtersheimer · Caroline Pabst · Carsten Müller-Tidow · Andreas Trumpp · Marc Seifert · Frank Neumann · Mathias Heikenwälder · Vladimir Benes · Wolfgang Huber · Jörg Distler · Georg Lenz · Hans Binder · Reiner Siebert · Garry P. Nolan · Moritz Gerstung · Judith B. Zaugg · Daniel Hübschmann · Simon Haas · Sascha Dietrich
25 March 2026 at 08:00

Nature Cancer, Published online: 25 March 2026; doi:10.1038/s43018-026-01136-z

Czernilofsky et al. identified factors that reprogram stromal cells into an inflammatory, dysfunctional state, leading to the structural disorganization of lymph nodes in B cell lymphoma at single-cell and spatial resolutions.

Tucatinib–trastuzumab–capecitabine for treatment of leptomeningeal metastasis in women with HER2<sup>+</sup> breast cancer: TBCRC049 phase 2 study results

✇Nature Cancer
By: Rashmi K. Murthy · Barbara J. O’Brien · Donald A. Berry · Akshara Singareeka-Raghavendra · Maria Gule Monroe · Jason Johnson · Jason White · Jill Schwartz-Gomez · Ariel Topletz-Erickson · Mina Lobbous · Kristen Riley · Michelle Melisko · Aki Morikawa · Sherise D. Ferguson · John F. de Groot · Ian E. Krop · Vicente Valero · Mothaffar F. Rimawi · Antonio C. Wolff · Debu Tripathy · Nancy U. Lin · Erica M. Stringer-Reasor
18 March 2026 at 08:00

Nature Cancer, Published online: 18 March 2026; doi:10.1038/s43018-026-01120-7

Murthy and colleagues discussed recent research on the effect of a tucanitib–trastuzumab–capecitabine regimen in patients with HER2+ breast cancer and leptomeningeal metastasis.
Received — 14 March 2026 ⏭ Nature Cancer
  • ✇Nature Cancer
  • A functional map of m<sup>6</sup>A sites in cancer Yalong Wang · Han Xu
    Nature Cancer, Published online: 13 March 2026; doi:10.1038/s43018-026-01137-yRNA N6-methyladenosine (m6A) is the most abundant internal RNA modification, yet its functional landscape in cancer remains poorly defined. A study now introduces a METTL3-based RNA base-editing screen that maps functional m6A sites and reveals m6A-dependent translational activation of the tumor suppressor CHD9 in prostate cancer and beyond.
     
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A functional map of m<sup>6</sup>A sites in cancer

✇Nature Cancer
By: Yalong Wang · Han Xu
13 March 2026 at 08:00

Nature Cancer, Published online: 13 March 2026; doi:10.1038/s43018-026-01137-y

RNA N6-methyladenosine (m6A) is the most abundant internal RNA modification, yet its functional landscape in cancer remains poorly defined. A study now introduces a METTL3-based RNA base-editing screen that maps functional m6A sites and reveals m6A-dependent translational activation of the tumor suppressor CHD9 in prostate cancer and beyond.

The genomic model P-CARE enables precision prostate cancer screening in a national healthcare system

✇Nature Cancer
13 March 2026 at 08:00

Nature Cancer, Published online: 13 March 2026; doi:10.1038/s43018-025-01111-0

We developed and clinically implemented the genomic prostate cancer risk prediction model P-CARE that identifies men at a high or low risk of prostate cancer. P-CARE enabled the design and initiation of a precision screening trial across the national healthcare system in which it was developed.
  • ✇Nature Cancer
  • AI for breast cancer screening Allan Hackshaw · Rosalind Given-Wilson
    Nature Cancer, Published online: 10 March 2026; doi:10.1038/s43018-025-01109-8Whether support from artificial intelligence (AI) models improves breast screening is a topic of research in national cancer screening programmes and clinical oncology. Three studies now show that AI tools can assist radiologists with evaluating mammograms, substantially reducing workloads and possibly improving screening performance.
     
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AI for breast cancer screening

✇Nature Cancer
By: Allan Hackshaw · Rosalind Given-Wilson
10 March 2026 at 08:00

Nature Cancer, Published online: 10 March 2026; doi:10.1038/s43018-025-01109-8

Whether support from artificial intelligence (AI) models improves breast screening is a topic of research in national cancer screening programmes and clinical oncology. Three studies now show that AI tools can assist radiologists with evaluating mammograms, substantially reducing workloads and possibly improving screening performance.

Diagnostic accuracy, fairness and clinical implementation of AI for breast cancer screening: results of multicenter retrospective and prospective technical feasibility studies

✇Nature Cancer
By: Christopher J. Kelly · Marc Wilson · Lucy M. Warren · Richard Sidebottom · Mark Halling-Brown · Lin Yang · Megumi Morigami · Jenny Venton · Reena Chopra · Jane Chang · Jonathan Dixon · Fiona J. Gilbert · Daniel I. Golden · Elzbieta Gruzewska · Lesley Honeyfield · Amandeep Hujan · Delara Khodabakhshi · Emma Lewis · Namrata Malhotra · Rachita Mallya · Della Ogunleye · Charlotte Purdy · Rory Sayres · Marcin Sieniek · Tsvetina Stoycheva · Aminata Sy · Susan Thomas · Dominic Ward · Lihong Xi · Shawn Xu · Shravya Shetty · Ara Darzi · Kenneth Young · Hema Purushothaman · Lisanne Khoo · Mamatha Reddy · Hutan Ashrafian · Deborah Cunningham
10 March 2026 at 08:00

Nature Cancer, Published online: 10 March 2026; doi:10.1038/s43018-026-01127-0

Kelly et al. assessed an artificial intelligence system for breast cancer screening in retrospective datasets, followed by prospective feasibility evaluation, and report its accuracy, fairness and clinical implementation in multiple workflow settings.

Impact of using artificial intelligence as a second reader in breast screening including arbitration

✇Nature Cancer
By: Lucy M. Warren · Jenny Venton · Kenneth C. Young · Mark Halling-Brown · Christopher J. Kelly · Marc Wilson · Megumi Morigami · Lisanne Khoo · Deborah Cunningham · Richard Sidebottom · Mamatha Reddy · Hema Purushothaman · Delara Khodabakhshi · Lesley Honeyfield · Amandeep Hujan · Tsvetina Stoycheva · Andy Joiner · Reena Chopra · Aminata Sy · Dominic Ward · Lin Yang · Rory Sayres · Daniel Golden · Namrata Malhotra · Rachita Mallya · Lihong Xi · Della Ogunleye · Charlotte Purdy · Alistair Mackenzie · Susan Thomas · Shravya Shetty · Fiona J. Gilbert · Ara Darzi · Hutan Ashrafian
10 March 2026 at 08:00

Nature Cancer, Published online: 10 March 2026; doi:10.1038/s43018-026-01128-z

Warren et al. used data from a retrospective cohort of 50,000 women attending breast screening. Arbitration between human and AI decisions was performed in a reader study following normal arbitration workflow. After arbitration, replacing the second human reader with AI in a double-read breast screening workflow was noninferior to two human readers.

Prospective evaluation of artificial intelligence integration into breast cancer screening in multiple workflow settings: the GEMINI study

✇Nature Cancer
By: Clarisse Florence de Vries · Gerald Lip · Roger Todd Staff · Jaroslaw Artur Dymiter · Benjamin Tse · Annie Ng · Georgia Fox · Cary Oberije · Lesley Ann Anderson
10 March 2026 at 08:00

Nature Cancer, Published online: 10 March 2026; doi:10.1038/s43018-026-01126-1

De Vries et al. performed prospective evaluation of AI for breast cancer screening leveraged in many different workflow settings and report several clinical and operational gains depending on the type of AI integration.
Received — 11 March 2026 ⏭ Nature Cancer

CRTAM inhibition mitigates toxicity of immune checkpoint inhibitors without antitumor efficacy trade-off

✇Nature Cancer
By: Si-Cong Ma · Zi-Xuan Rong · Zi-Peng Xu · Yan-Pei Zhang · Kui-Mao Zhuang · Hao Sun · Chuan-Hui Cao · Ze-Nan Wu · Hai-Peng Zhang · Qiang Zuo · Jia-Run Lin · Jia-Xin Cheng · Hua-Ting Qu · Duan-Duan Han · Wei Wei · Ke Liu · Xiao-Ting Cai · Ze-Qin Guo · Xue Bai · Li Liu · De-Hua Wu · Zhong-Yi Dong
5 March 2026 at 08:00

Nature Cancer, Published online: 05 March 2026; doi:10.1038/s43018-026-01135-0

Dong and colleagues report that blockade of T cell-expressed cytotoxic and regulatory T cell molecule results in selective mitigation of immune-related toxicities without affecting antitumor efficacy of immune checkpoint inhibitors.
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