Biology subjects

Matsen, C. B.

Publications and source records attributed to Matsen, C. B..

3 recordsLinked to original sources

bioRxiv2022

Replicative Instability Drives Cancer Progression

In the past decade, defective DNA repair has been increasingly linked with cancer progression. Human tumors with markers of defective DNA repair and increased replication stress have been shown to exhibit genomic instability and poor survival rates across tumor types. Here we utilize-omics data from two independent consortia to identify the genetic underpinnings of replication stress, therapy resistance, and primary carcinoma to brain metastasis in BRCA wildtype tumors. In doing so, we have defined a new pan-cancer class of tumors characterized by replicative instability (RIN). RIN is defined by genomic evolution secondary to replicative challenge. Our data supports a model whereby defective single-strand break repair, translesion synthesis, and non-homologous end joining effectors drive RIN. Collectively, we find that RIN accelerates cancer progression by driving copy number alterations and transcriptional program rewiring that promote tumor evolution. Statement of SignificanceDefining the genetic basis of genomic instability with wildtype BRCA repair effectors is a significant unmet need in cancer research. Here we identify and characterize a pan-cancer cohort of tumors driven by replicative instability (RIN). We find that RIN drives therapy resistance and distant metastases across multiple tumor types.

cancer biology↗

bioRxiv2021

A breast cancer patient-derived xenograft and organoid platform for drug discovery and precision oncology

Model systems that recapitulate the complexity of human tumors and the reality of variable treatment responses are urgently needed to better understand cancer biology and to develop more effective cancer therapies. Here we report development and characterization of a large bank of patient-derived xenografts (PDX) and matched organoid cultures from tumors that represent some of the greatest unmet needs in breast cancer research and treatment. These include endocrine-resistant, treatment-refractory, and metastatic breast cancers and, in some cases, multiple tumor collections from the same patients. The models can be grown long-term with high fidelity to the original tumors. We show that development of matched PDX and PDX-derived organoid (PDxO) models facilitates high-throughput drug screening that is feasible and cost-effective, while also allowing in vivo validation of results. Our data reveal consistency between drug screening results in organoids and drug responses in breast cancer PDX. Moreover, we demonstrate the feasibility of using these patient-derived models for precision oncology in real time with patient care, using a case of a triple negative breast cancer with early metastatic recurrence as an example. Our results uncovered an FDA-approved drug with high efficacy against the models. Treatment with the PDxO-directed therapy resulted in a complete response for the patient and a progression-free survival period more than three times longer than her previous therapies. This work provides valuable new methods and resources for functional precision medicine and drug development for human breast cancer. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=189 HEIGHT=200 SRC="FIGDIR/small/433268v2_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@134d5cdorg.highwire.dtl.DTLVardef@1c0a419org.highwire.dtl.DTLVardef@556a4forg.highwire.dtl.DTLVardef@1b68c9c_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2017

Population-Based Relative Risks For Specific Family History Constellations Of Breast Cancer - Towards Individualized Risk Estimation

PurposeUsing a large resource linking genealogy with decades of cancer data, RRs were estimated for breast cancer (BC) based on specific family history extending to first cousins.\n\nMethodsRRs for BC were estimated in 640,366 females with breast cancer family histories that included number of first-(FDR), second-(SDR), and third-degree relatives (TDR), maternal and paternal relatives, and age at earliest diagnosis.\n\nResultsRRs for first-degree relatives of BC cases ranged from 1.61 (=1 FDR affected, CI: 1.56, 1.67) to 5.00 ([≥]4 FDRs affected, CI: 3.35, 7.18). RRs for second degree relatives of probands with 0 affected FDRs ranged from 1.08 ([≥]1 SDR affected, CI: 1.04, 1.12) to 1.71 ([≥]4 SDRs affected, CI: 1.26, 2.27) and for second degree relatives of probands with exactly 1 FDR from 1.54 (0 SDRs affected, CI:1.47, 1.61) to 4.78 ([≥] 5 SDRs; CI 2.47, 8.35). RRs for third-degree relatives with no closer relatives affected were significantly elevated for probands with >=5 affected TDRs RR=1.32, CI: 1.11, 1.57).\n\nConclusionsThe majority of females analyzed had a family history of BC. Any number of affected FDRs or SDRs significantly increased risk for BC, and more than 4 TDRs, even with no affected FDRs or SDRs significantly increased risk. Risk prediction derived from specific and extended family history allows identification of females at highest risk even when they do not have a conventionally defined \"high risk\" family; these risks could be a powerful, efficient tool to individualize cancer prevention and screening.

genetics↗