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Treatment Resistant Cancers

Treatment Resistant Cancers

Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...

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Metastasis is the spread of cancer cells from the original site to distant locations in the body. Cancer cells can spread via blood vessels (hematogenous) as well as lymph vessels in the body.
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The epithelial-to-mesenchymal transition or EMT is a developmental process commonly observed in wound healing, embryogenesis, and cancer metastasis. EMT is induced by transforming growth factor-beta (TGF-β) or receptor tyrosine kinase (RTK) ligands, which further...

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Updated: Apr 28, 2026

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis

Published on: March 8, 2022

Serial Spatial Transcriptomics Reveal Divergent Routes to Therapy Resistance in Metastatic Breast Cancer.

Hisham Mohammed¹, Gordon Mills¹, Aaron Doe¹

¹Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA.

Research Square

|April 27, 2026

Summary

This summary is machine-generated.

This study reveals how metastatic tumors adapt and resist treatment by analyzing individual patient cells spatially. Understanding these spatial resistance mechanisms can guide better combination therapies for metastatic breast cancer.

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Area of Science:

Oncology
Genomics
Computational Biology

Background:

Metastatic solid tumors develop therapeutic resistance via complex adaptive strategies.
Current precision medicine relies on bulk biomarkers, missing spatial and cellular resistance contexts.

Purpose of the Study:

To develop and apply a patient-centric spatial framework for analyzing metastatic tumor heterogeneity.
To identify spatial principles and mechanisms of therapeutic resistance in metastatic breast cancer.

Main Methods:

Integrated probabilistic topic modeling with spatial deep learning on 345,207 cells from ten biopsies across four metastatic breast cancer patients.
Longitudinal profiling spanning personalized treatment courses up to 3.5 years.

Main Results:

Observed universal principles of metastatic survival: pathway independence, microenvironment remodeling, and compensatory signaling.
Identified distinct mechanisms for these principles, including loss of luminal identity, ESR1 activation, invasive nest formation, immune evasion, fibroblast barriers, and rewired signaling networks.
Demonstrated that spatial profiling reveals patient-specific resistance mechanisms.

Conclusions:

Spatial profiling offers a method to identify individual resistance mechanisms in metastatic breast cancer.
Findings enable rational design of multi-axis combination therapies and earlier treatment decisions for improved patient outcomes.