Conventional and semi-automatic histopathological analysis of tumor cell content for multigene sequencing of lung adenocarcinoma.

BACKGROUND

Targeted genetic profiling of tissue samples is paramount to detect druggable genetic aberrations in patients with non-squamous non-small cell lung cancer (NSCLC). Accurate upfront estimation of tumor cell content (TCC) is a crucial pre-analytical step for reliable testing and to avoid false-negative results. As of now, TCC is usually estimated on hematoxylin-eosin (H&E) stained tissue sections by a pathologist, a methodology that may be prone to substantial intra- and interobserver variability. Here we the investigate suitability of digital pathology for TCC estimation in a clinical setting by evaluating the concordance between semi-automatic and conventional TCC quantification.

METHODS

TCC was analyzed in 120 H&E and thyroid transcription factor 1 (TTF-1) stained high-resolution images by 19 participants with different levels of pathological expertise as well as by applying two semi-automatic digital pathology image analysis tools (HALO and QuPath).

RESULTS

Agreement of TCC estimations [intra-class correlation coefficients (ICC)] between the two software tools (H&E: 0.87; TTF-1: 0.93) was higher compared to that between conventional observers (0.48; 0.47). Digital TCC estimations were in good agreement with the average of human TCC estimations (0.78; 0.96). Conventional TCC estimators tended to overestimate TCC, especially in H&E stainings, in tumors with solid patterns and in tumors with an actual TCC close to 50%.

CONCLUSIONS

Our results determine factors that influence TCC estimation. Computer-assisted analysis can improve the accuracy of TCC estimates prior to molecular diagnostic workflows. In addition, we provide a free web application to support self-training and quality improvement initiatives at other institutions.

Informations de copyright

2021 Translational Lung Cancer Research. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tlcr-20-1168). DK reports personal fees from AstraZeneca, Bristol-Myers Squibb, and Pfizer outside the submitted work. ALV reports personal fees from Astra Zeneca, outside the submitted work. RL reports grants from Deutsche Forschungsgemeinschaft (DFG), Dietmar Hopp Stiftung, outside the submitted work. CPH reports grants from Siemens, Pfizer, MeVis, Boehringer Ingelheim, German Center for Lung Research, personal fees from Astellas, AstraZeneca, Basilea, Bayer, Boehringer Ingelheim, Bracco MEDA Pharma, Chiesi, Covidien, Essex, Fresenius, Gilead, Grifols, Intermune, Lilly, MSD, Novartis, Pfizer, Pierre Fabre, Roche, Schering-Plough, Siemens, other from GSK, outside the submitted work; in addition, CPH has a patent Method and Device For Representing the Microstructure of the Lungs, IPC8 Class: AA61B5055FI, PAN: 20080208038 issued. FH reports personal fees from Uptake, BTG, Olympus, Pulmonx, outside the submitted work. PC reports grants and personal fees from Novartis, Roche, AstraZeneca, Takeda, and personal fees from Pfizer, Chugai, Boehringer, outside the submitted work. TM reports grants and non-financial support from Roche Diagnostics GmbH, Penzberg, Germany, outside the submitted work; in addition, TM has a patent WO2019158460 pending, a patent WO2019211418 pending, a patent WO2019215223 pending, a patent EP3391053 issued, and a patent EP3365679 pending. MR reports personal fees from Amgen, AstraZeneca, Boehringer-Ingelheim, BMS, Lilly, Celgene, Merck, Mirati, MSD, Novartis, Pfizer, Roche, Samsung Bioepis, outside the submitted work. WW reports personal fees from Roche, MSD, BMS, AstraZeneca, Pfizer, Merck, Lilly, Boehringer, Novartis, Takeda, Amgen, Astellas, Illumina, Agilent, Siemens, Molecular Health and grants from Roche, MSD, BMS, Bruker, AstraZeneca, outside the submitted work. JB reports grants from German Cancer Aid, outside the submitted work. MT reports grants, personal fees and non-financial support from AstraZeneca, Bristol-Myers Squibb, Takeda, Roche, personal fees and non-financial support from AbbVie, Boehringer Ingelheim, Celgene, Chugai, Lilly, Novartis, Pfizer, outside the submitted work. SP reports personal fees from Abbvie, Amgen, AstraZeneca, Bayer, Biocartis, Boehringer-Ingelheim, BMS, Clovis, Daiichi Sankyo, Debiopharm, Eli Lilly, F. Hoffmann-La Roche, Foundation Medicine, Illumina, Janssen, Merck Sharp and Dohme, Merck Serono, Merrimack, Novartis, Pharma Mar, Pfizer, Regeneron, Sanofi, Seattle Genetics and Takeda, Takeda, Bioinvent, Medscape, Phosphoplatin Therapeutics; non-financial support from Amgen, AstraZeneca, Boehringer-Ingelheim, BMS, Clovis, F. Hoffmann-La Roche, Illumina, Merck Sharp and Dohme, Merck Serono, Novartis, Pfizer, Phosphoplatin; outside the submitted work; all fees to Institution. PS reports personal fees from BMS, MSD, Incyte, Janssen, Amgen, Novartis, Roche and AstraZeneca outside the submitted work. AS reports grants and personal fees from Bayer, BMS, grants from Chugai and personal fees from Astra Zeneca, MSD, Takeda, Seattle Genetics, Novartis, Illumina, Thermo Fisher, Eli Lily, Takeda, outside the submitted work. The other authors have no conflicts of interest to declare.