Development and validation of mFISHseq: A diagnostic test using multiplexed RNA-FISH–guided laser capture microdissection RNA sequencing.
Authors: Loeffler Chiara Maria Lavinia , Paul Evan David , Huraiová Barbora , Matyašovská Natália , Valková Natália , Gábrišová Daniela , Gubová Soňa , Ignačáková Helena , Ondris Tomáš , Bendíková Silvia , Lovíšek Daniel , Ristová Michaela , Gala Michal , Comino-Méndez Iñaki , Morozov Pavel , Barrett J. Carl Carl , Pareja Fresia , Kather Jakob Nikolas , Čekan Pavol 
Published: June 2024

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Background: Breast cancer (BCa) is a heterogeneous disease requiring precise diagnostic tools to guide effective treatment strategies. Current diagnostic assays, including various multigene assays, often fail to adequately address the complex biology of BCa subtypes. To address these limitations and enhance the understanding of BCa biology, we developed and validated a novel diagnostic, prognostic, and predictive tool, called mFISHseq. Methods: Our approach, mFISHseq, integrates multiplexed fluorescent in situ hybridization (FISH) of the four main BCa biomarkers, estrogen ( ESR1)/progesterone ( PGR)/Her2 ( ERBB2) receptors and Ki67 ( MKI67), which are used to guide laser capture microdissection (LCM) of regions of interest followed by RNA-sequencing. This technique ensures tumor purity, facilitates interrogation of tumor heterogeneity, consequently permitting unbiased analysis of whole transcriptome profiling data and explicitly quantifying the variability between different tumor regions. We validated mFISHseq on a retrospective cohort study involving 1,082 FFPE breast tumors with detailed clinicopathological data, informed consent, and ethical committee approval. Results: mFISHseq demonstrated excellent analytical validity with a 93% accuracy rate compared to standard immunohistochemistry (IHC), while providing more quantitative biomarker expression. Prespecified threshold values for mFISHseq derived from a split 70:30 training/test set showed exceptional concordance with IHC as demonstrated by area under the receiver operating characteristic (ROC) curves for all markers (AUC: MKI67=0.98, ERBB2=0.95, ESR1=0.95, PGR=0.93). Both RNA-FISH and -SEQ showed moderate to very strong correlations (Spearman’s r; ERBB2=0.41, MKI67=0.61, PGR=0.66, ESR1=0.75), thus highlighting the potential to use both orthogonal methodologies to cross-validate results. To demonstrate clinical validity, we developed a 293-gene intrinsic subtype classifier, showing substantial agreement to established classifiers like PAM50 and AIMS (Cohen’s κ= 0.75 and 0.73, respectively) and superior prognostic performance. We also report that LCM is an essential component of the mFISHseq workflow, since samples that did not undergo LCM showed reduced biomarker expression, elevated non-tumor gene expression, and misclassification of samples into less aggressive molecular subtypes (e.g., normal-like) and prognostic risk groups (e.g., high to low). Conclusions: The mFISHseq method showed excellent concordance with IHC and the use of LCM provides tumor-enriched samples that are devoid of contamination from non-tumor elements, thus providing unbiased spatially resolved interrogation of tumor heterogeneity. Altogether, mFISHseq solves a long-standing challenge in the precise diagnosis and classification of breast cancer subtypes.