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Johan Lindberg

Karolinska University Hospital

Sweden

Research Interests

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Professors in Sweden Professors in Cell Biology Cell Biology professors in Sweden

Articles (23)

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Collaborators (21)

Martin Eklund

Professor

Karolinska Institutet

SWEDEN

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Brinton Seashore-Ludlow

Karolinska Institutet

SWEDEN

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Jørgen Bjerggaard Jensen

Aarhus University

DENMARK

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Subhayan Chattopadhyay

Lund University

SWEDEN

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Jacob Fredsøe

Aarhus University

DENMARK

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Karin Holmsten

Karolinska Institutet

SWEDEN

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Karina Dalsgaard Sørensen

VIP, Professor

Aarhus University

DENMARK

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Anders Ullén

Professor of Clinical Oncology

Karolinska Institutet

SWEDEN

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Kimmo Kartasalo

Karolinska Institutet

SWEDEN

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Brieuc SAUTOIS

Clinical Professor

CHU de Liège - Hôpital du Sart Tilman

BELGIUM

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Michael Borre

Chair professor

Aarhus University Hospital

DENMARK

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Bram De Laere

Karolinska Institutet

SWEDEN

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Lene Hjerrild Iversen

Professor, consultant surgeon

Aarhus University Hospital

DENMARK

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Edmond Kwan

Senior Research Fellow

MONASH UNIVERSITY

AUSTRALIA

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Gottfrid Sjödahl

Lund University

SWEDEN

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Karin Jirström

Professor

Lund University

SWEDEN

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Päivi Östling

Karolinska Institutet

SWEDEN

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Gabriel Renaud

Associate Professor

Laval University

CANADA

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Søren Vang

DVIP-external, Head of Clinical Bioinformatics

Aarhus University

DENMARK

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Anna Martling

Karolinska Institutet

SWEDEN

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Antti Rannikko

University of Helsinki

FINLAND

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Johan Lindberg

Research Interests

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Articles (23)

Functional profiling of ovarian cancer models reveals Bcl-xL/NOTCH targeting to overcome resistance.

Clinical Trial Protocol for ProBio-mHSPC: A ctDNA-driven De-escalation and Intensification Platform Trial for Metastatic Hormone-sensitive Prostate Cancer.

Deep targeted sequencing of circulating tumor DNA to inform treatment in patients with metastatic castration-resistant prostate cancer

Exploring novel genomic biomarkers for response and survival after neoadjuvant chemotherapy and radical cystectomy of muscle-invasive bladder cancer

Low-Dose Aspirin for PI3K-Altered Localized Colorectal Cancer

Prognostic Value of the Circulating Tumor DNA Fraction in Metastatic Castration-resistant Prostate Cancer: Results from the ProBio Platform Trial.

Reliable on-treatment prognostication and target identification with a customized assay for circulating tumor DNA in patients with newly diagnosed pancreatic cancer

Low-Dose Aspirin for PI3K-Altered Localized Colorectal Cancer. Reply.

Systematic profiling of cancer-fibroblast interactions reveals drug combinations in ovarian cancer.

Low-dose aspirin to reduce recurrence rate in colorectal cancer patients with PI3K pathway alterations: 3-year results from a randomized placebo-controlled trial.

Comprehensive Genomic Profiling Alters Clinical Diagnoses in a Significant Fraction of Tumors Suspicious of Sarcoma.

Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer.

Prognostic Value of Low-Pass Whole Genome Sequencing of Circulating Tumor DNA in Metastatic Castration-Resistant Prostate Cancer

<i>AR</i> and <i>PI3K</i> Genomic Profiling of Cell-free DNA Can Identify Poor Responders to Lutetium-177-PSMA Among Patients with Metastatic Castration-resistant Prostate Cancer.

Transcriptome-wide prediction of prostate cancer gene expression from histopathology images using co-expression-based convolutional neural networks

Ductal and acinar components of mixed prostatic adenocarcinoma frequently have a common clonal origin

Circulating tumor DNA (ctDNA) in adjuvant therapy of early stage colon cancer: current status and future perspectives

Clinical Trial Protocol for ProBio: An Outcome-adaptive and Randomised Multiarm Biomarker-driven Study in Patients with Metastatic Prostate Cancer

ESMO recommendations on the use of circulating tumour DNA assays for patients with cancer: a report from the ESMO Precision Medicine Working Group

Fusion Gene Detection Using Whole-Exome Sequencing Data in Cancer Patients

Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization

Using deep learning to detect patients at risk for prostate cancer despite benign biopsies

Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies-Current Status and Next Steps

Collaborators (21)

Martin Eklund

Brinton Seashore-Ludlow

Jørgen Bjerggaard Jensen

Subhayan Chattopadhyay

Jacob Fredsøe

Karin Holmsten

Karina Dalsgaard Sørensen

Anders Ullén

Kimmo Kartasalo

Brieuc SAUTOIS

Michael Borre

Bram De Laere

Lene Hjerrild Iversen

Edmond Kwan

Gottfrid Sjödahl

Karin Jirström

Päivi Östling

Gabriel Renaud

Søren Vang

Anna Martling

Antti Rannikko

Make your next move.