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. 2023 Jul:174:262-272.
doi: 10.1016/j.ygyno.2023.05.059. Epub 2023 May 26.

Integration of clinical sequencing and immunohistochemistry for the molecular classification of endometrial carcinoma

Eric Rios-Doria  1 , Amir Momeni-Boroujeni  2 , Claire F Friedman  3 , Pier Selenica  2 , Qin Zhou  4 , Michelle Wu  1 , Antonio Marra  2 , Mario M Leitao Jr  5 , Alexia Iasonos  4 , Kaled M Alektiar  6 , Yukio Sonoda  5 , Vicky Makker  3 , Elizabeth Jewell  5 , Ying Liu  3 , Dennis Chi  5 , Dimitry Zamarin  3 , Nadeem R Abu-Rustum  5 , Carol Aghajanian  3 , Jennifer J Mueller  5 , Lora H Ellenson  2 , Britta Weigelt  7
Affiliations

Integration of clinical sequencing and immunohistochemistry for the molecular classification of endometrial carcinoma

Eric Rios-Doria et al. Gynecol Oncol. 2023 Jul.

Abstract

Purpose: Using next generation sequencing (NGS), The Cancer Genome Atlas (TCGA) found that endometrial carcinomas (ECs) fall under one of four molecular subtypes, and a POLE mutation status, mismatch repair (MMR) and p53 immunohistochemistry (IHC)-based surrogate has been developed. We sought to retrospectively classify and characterize a large series of unselected ECs that were prospectively subjected to clinical sequencing by utilizing clinical molecular and IHC data.

Experimental design: All patients with EC with clinical tumor-normal MSK-IMPACT NGS from 2014 to 2020 (n = 2115) were classified by integrating molecular data (i.e., POLE mutation, TP53 mutation, MSIsensor score) and MMR and p53 IHC results. Survival analysis was performed for primary EC patients with upfront surgery at our institution.

Results: Utilizing our integrated approach, significantly more ECs were molecularly classified (1834/2115, 87%) as compared to the surrogate (1387/2115, 66%, p < 0.001), with an almost perfect agreement for classifiable cases (Kappa 0.962, 95% CI 0.949-0.975). Discrepancies were primarily due to TP53 mutations in p53-IHC-normal ECs. Of the 1834 ECs, most were of copy number (CN)-high molecular subtype (40%), followed by CN-low (32%), MSI-high (23%) and POLE (5%). Histologic and genomic variability was present amongst all molecular subtypes. Molecular classification was prognostic in early- and advanced-stage disease, including early-stage endometrioid EC.

Conclusions: The integration of clinical NGS and IHC data allows for an algorithmic approach to molecularly classifying newly diagnosed EC, while overcoming issues of IHC-based genetic alteration detection. Such integrated approach will be important moving forward given the prognostic and potentially predictive information afforded by this classification.

Keywords: Clinical sequencing; Endometrial carcinoma; Immunohistochemistry; Molecular classification; Mutation.

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Conflict of interest statement

Conflicts of interest N.R. Abu-Rustum reports Stryker/Novadaq and GRAIL grants paid to the institution, outside the current study. C.F. Friedman reports institutional research support from Seagen, Merck, BMS, AstraZeneca, Mersana and Hotspot Therapeutics; consulting fees from BMS, Seagen and Aadi Biosciences; honoraria for lectures from Onclive; meeting/ travel support by Puma; participation on Data Safety Monitoring or Advisory Board of Merck, Genentech and Marengo (all uncompensated). D. Zamarin reports institutional research support from AstraZeneca, Merck, Plexxikon Synthekine and Genentech; consulting fees from AstraZeneca, Synthekine, Astellas, Tessa Therapeutics, Memgen, Celldex, Crown Biosciences, Hookipa Biotech, Kalivir, Xencor and GSK; royalties from Merck; and stock options from Accurius Therapeutics, ImmunOS Therapeutics and Calidi Biotherapeutics, all outside the submitted work. V. Makker reports meeting/travel support by Eisai and Merck; participation on Data Safety Monitoring or Advisory Board of Duality, Merck, Karyopharm, Exelexis, Eisai, Karyopharm, BMS, Clovis, Faeth Immunocore, Morphosys, AstraZeneca, Novartis, GSK, Bayer (all unpaid), and study support to the institution by Merck, Eisai, AztraZeneca, Faeth, Karyopharm, Zymeworks, Duality, Clovis, Bayer and Takeda. Y. Liu reports institutional research funding from Repare Therapeutics, AstraZeneca and GSK; honoraria from Total Health and Sarah Lawrence College; and travel/meeting support by AstraZeneca, outside the submitted work. B. Weigelt reports a research grant from REPARE Therapeutics paid to the institution, outside the submitted work. D.S. Chi reports personal fees from Apyx Medical, Verthermia Inc., Biom ‘Up, and AstraZeneca, as well as recent or current stock/options ownership of Apyx Medical, Verthemia, Intuitive Surgical, Inc., TransEnterix, Inc., Doximity, Moderna, and BioNTech SE. E.L. Jewell reports personal fees from Covidien/Medtronic. M. M. Leitao is an ad hoc speaker for Intuitive Surgical, Inc.; outside the submitted work, he is on the Advisory Board of Ethicon/Johnson & Johnson and Takeda; and reports grants paid to the institution by KCI/Acelity. C. Aghajanian reports clinical trial funding paid to the institution from AstraZeneca; consulting fees (advisory board) from Eisai/Merck, Roche/Genentech, Abbvie, AstraZeneca/Merck, and Repare Therapeutics; advisory board participation (no fee) for Blueprint Medicine; and leadership/fiduciary roles for the GOG Foundation Board of Directors (travel cost reimbursement) and NRG Oncology Board of Directors (unpaid). The remaining authors have no conflicts of interest to declare.

Figures

Figure 1.
Figure 1.. Patient selection and molecular classification of endometrial cancers integrating clinical tumor-normal sequencing and immunohistochemistry data.
A. CONSORT diagram summarizing the endometrial cancer patients included in this study. B. Method employed for classification of endometrial cancers into the molecular subtypes using clinical MSK-IMPACT sequencing results and immunohistochemistry. C. Distribution of histologic subtypes and molecular subtypes for 1,834 endometrial cancers subjected to clinical sequencing. CN-H, copy number-high; CN-L, copy number-low; G1, grade 1; G2, grade 2; G3, grade 3; MSI-H, microsatellite instability-high; NOS, not otherwise specified.
Figure 2.
Figure 2.. Endometrial cancer molecular classification according to the integrated clinical tumor-normal sequencing/immunohistochemistry-based and the conventional ProMisE approaches.
A. TP53 mutations and p53 expression patterns by immunohistochemistry in endometrial cancers classified as of copy number-high molecular subtype. B. Sequencing-derived MSI-sensor scores and DNA mismatch repair (MMR) deficiency/ proficiency by immunohistochemistry in endometrial cancers classified as of MSI-H molecular subtype. C. Agreement of molecular subtype assignments using our integrated molecular and immunohistochemistry-based approach (top) and the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE; second row from top). Information on the TP53 mutation status, p53 immunohistochemistry, MSIsensor score and MMR immunohistochemistry are shown below.
Figure 3.
Figure 3.. Landscape of somatic mutations and gene copy number alterations of endometrial cancers by molecular subtype integrating clinical sequencing and immunohistochemistry.
A. Oncoprints depicting the most recurrent somatic alterations in cancer-related genes in endometrial carcinomas by molecular subtype. Each column represents a tumor and the Oncoprint rows depict alterations for each gene. The bottom part of the graph shows the summary of histopathologic and clinical information for each case. The bar graph on the right of the panel shows the number and distribution of alterations for each gene across all subtypes. Mutation types and clinicopathologic features are color coded according to the legend. B. Tumor mutational burden in endometrial cancer by molecular subtype. C. Fraction of genome altered endometrial cancer by molecular subtype. P-value, Kruskal-Wallis rank sum test. CN-H, copy number-high; CN-L, copy number-low; MSI-H, microsatellite instability-high; N/A, not available; NOS, not otherwise specified.
Figure 4.
Figure 4.. Survival outcomes of endometrial cancer patients by molecular subtype using an integrated clinical sequencing – immunohistochemistry-based classification approach.
Survival was assessed in 925 patients with endometrial cancer of all histologic types whose tumors were subjected to MSK-IMPACT prior to recurrence, had upfront surgery, were surgically staged, and had surgery performed at our institution (see Supplementary Fig. S1). A. Kaplan-Meier curve comparing progression-free survival (PFS) and overall survival (OS) in all 925 endometrial cancer patients by molecular subtype. B. PFS (n=679) and OS (n=502) of endometrial cancer patients with stage I/II disease. C. PFS and OS of endometrial cancer patients with stage III/IV disease (n=246). For stage III and stage IV analysis separately, see Supplementary Fig. S3. D. PFS and OS of patients with stage I/II endometrioid endometrial cancer (n=502). Survival compared with log-rank test. *p-value defined excluding the POLE molecular subtype due to the lack of events. CN-H, copy number-high; CN-L, copy number-low; MSI-H, microsatellite instability-high.
Figure 5.
Figure 5.. Survival outcomes in high-risk histologic types and in copy number-low endometrial cancer patients by chromosomal instability.
A. Fraction of genome altered (FGA, %) among copy number-high (CN-H) endometrial cancers of serous histology (n=265), endometrioid histology (n=74), and carcinosarcoma (n=195). B. Progression-free survival (PFS) and overall survival (OS) of patients meeting survival criteria with endometrial carcinomas of CN-H serous (n=82), CN-H endometrioid (n=32), and CN-H carcinosarcoma (n=78) histologic types. C. PFS and OS of patients with CN-low (CN-L) endometrial cancer (n=249; survival cohort) dichotomized by the median FGA of CN-H endometrial cancer (median 20%; Supplementary Fig. S4). Survival compared with log-rank test.
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