Presented by:

Gianella Contreras Rodriguez

PSI Cohort 2025

Organoid Profiling Identifies Common Responders to Chemotherapy in Pancreatic Cancer

Authors: Herve, Tiriac, David A Tuveson, and others

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VOCAB:

Organoid

PDO

Chemosensitive

Chemorefractory

Sequencing

“An artificially grown mass of cells or tissues that resembles an organ”

Patient derived organoid

The susceptibility of a tumor to be killed by anti-cancer drugs such as chemotherapy.

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The resistance of a tumor to anti-cancer drugs like chemotherapy

Figure 1 B:

Pancreatic cancer PDO samples under a brightfield microscopy. Furthest to the left (hN) is normal pancreatic cell tissue, in the middle (hT) is a PDO from a primary tumor, and to the right is from a fine needle biopsy (hF)

“determining the order of DNA or RNA bases to identify genetic alterations, mutations, and other changes that drive cancer development and progression,”

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Background:

1. Pancreatic cancer = most lethal common solid malignancy
• Treatments = often ineffective
• Predictive biomarkers needed
2. 159 specimens from 138 patients to create a:
• Pancreatic cancer PDO library
3. To determine treatments the patient’s cancer is chemosensitive and chemorefractory to.

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Figure 1c:

Single nucleotide variants (SNVs) in PDO library with mutation frequency of the genes indicated, cancer% to the left and normal % to the right, with a colored coded key indicated patient staging and type of mutation.

Figure 1D: Shows copy number alterations in the PDO library. The cancer stages of the patients are indicated, and copy number ratio is matched with the color key

Objective and Hypothesis:

1. Use pancreatic cancer PDO library to predict clinical responses to systemic treatments

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2. Use PDOs for future therapeutic selection.

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Use results from this

To give you information to do this

PDO library

Personalized treatment

Experimental Design:

1. Created PDOs
2. Sequenced them => Analyzed them =>Therapeutically profiled them (pharmacotyping)
3. ⅚ patients corresponded with one sensitive drug the PDO was sensitive to.

Results:

• 1. PDO pharmacotyping revealed:
• PDOs had high concordance with pancreatic cancer sensitvies and resistances
• Diversity of patients and their cells' response to chemotherapeutic drugs may supersede other causes of drug resistance

Figure 6C and 6D:

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6C- Kaplan-Meier analysis (analysis that measures probability) of PFS of gemcitabine-sensitive and sensitive patients as identified in B

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6D-Kaplan Meier analysis of gemcitabine sensitive and non sensitive patients who were untreated

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Figure 6A:

Demonstrates the data of the different PDOs sensitivities or insensitivity to gemcitabine (chemotherapeutic agent)

Figure 6B:

Demonstrates the RNA-seq data of gemcitabine sensitivity or non-sensitivity

Conclusion:

1. By categorizing PDO cultures molecularly, sequencing their genomes, and therapeutically profiling them with pharmacotyping:
• PDOs have the possibility to =>
1. Create personalized medicine approaches
2. Predict patient responses to chemotherapeutic treatments.

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Categorization of PDOs

Sequencing of PDOs

Therapeutically profiling PDOs with pharmacotyping

Personalized medicine

Predict patient responses to chemotherapeutic treatments

Limitations:

1. Low concordance
• Low purity (% of cancer cells within a tumor sample) in PDOs
2. Time

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If

Greater than 6 weeks

-Personalized medicine and treatment may not be able to occur

1. Decrease time of PDO development and pharmacotyping

Future Directions:

3. Develop technologies and experiments:

ex.) using PDOs for testing of experimental drugs

ex.)immortalize PDOs

Link to article here: Journal Club Article Link

Thank you for listening! Any questions?

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