New light on how ovarian cancer grows and evolves

Date:
August 5, 2020
Source:
CUNY Graduate School of Public Health and Health Policy
Summary:
Medical researchers provide new insights into how ovarian cancer
grows and evolves within a person.



FULL STORY ==========================================================================
In a paper published in the journal Cancer Research, professor Levi
Waldron, post-doctoral fellow Ludwig Geistlinger, and colleagues at the Institute for Implementation Science in Population Health (ISPH) at the
CUNY Graduate School of Public Health and Health Policy (CUNY SPH) provide
new insights into how ovarian cancer grows and evolves within a person.


==========================================================================
The paper, "Multi-omic analysis of subtype evolution and heterogeneity in
high- grade serous ovarian carcinoma" is of basic scientific interest
for its methodology and insights into the decades-long process of tumorigenesis, and of practical interest for the implications these
insights have on the viability of subtype-targeted therapies. More than
20,000 women receive a new diagnosis of ovarian cancer each year in the
United States, and approximately 14,000 die each year.

"Understanding how a heterogeneous tumor evolves prior to diagnosis
is difficult because we can't directly observe that evolution," says
Professor Waldron. "But by observing tumors identified at different stages
of that evolution, and through detailed investigation of tumor genomics
and heterogeneity, we can still learn something about it. The key thing we wanted to know was whether a tumor starts as a certain subtype and stays
that way, or evolves, changes, and even multiplies subtypes over time. If subtypes can evolve and multiply within one tumor, then subtype-specific therapies are unlikely to help." To answer these questions, the team
developed a new method of inferring the existence of heterogeneous
subtypes from complementary types of genomic data, published separately
in the Journal of Clinical Oncology -- Clinical Cancer Informatics,
and teamed up with researchers from the University of Minnesota who
leveraged new technology to sequence the RNA of single cells.

"We used complementary but completely different approaches to approach
the same question -- one using more traditional approach using DNA
and RNA sequencing of hundreds of bulk tumors, and the other using new single-cell sequencing methods for a few tumors," Waldron elaborates,
"Seeing a consistent picture from both approaches really strengthened confidence in results coming from two novel approaches." A surprising
outcome of the research is a dismissal of the idea of discrete
transcriptome subtypes for this cancer, and replacement by a model
of continuous tumor development that includes mixtures of subclones, accumulation of mutations, infiltration of immune and stromal cells
in proportions correlated with tumor stage and tissue of origin, and
evolution between properties previously associated with discrete subtypes.

"Unfortunately, previous ideas of discrete subtypes were overly simplistic
and unlikely to progress our understanding, prevention, or treatment
of this disease," says Waldron. "Fortunately, with the clearer picture
emerging of tumor heterogeneity, and the rapid development of technologies
to help understand it, we are well-positioned to make progress."

========================================================================== Story Source: Materials provided by CUNY_Graduate_School_of_Public_Health_and_Health_Policy.

Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Ludwig Geistlinger, Sehyun Oh, Marcel Ramos, Lucas Schiffer,
Rebecca S.

LaRue, Christine M. Henzler, Sarah A. Munro, Claire Daughters,
Andrew C.

Nelson, Boris J. Winterhoff, Zenas Chang, Shobhana Talukdar, Mihir
Shetty, Sally A. Mullany, Martin Morgan, Giovanni Parmigiani,
Michael J.

Birrer, Li-Xuan Qin, Markus Riester, Timothy K. Starr, Levi Waldron.

Multi-omic analysis of subtype evolution and heterogeneity in
high-grade serous ovarian carcinoma. Cancer Research, 2020;
canres.0521.2020 DOI: 10.1158/0008-5472.CAN-20-0521 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/08/200805110125.htm

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