Machine learning-based somatic variant calling in cell-free DNA of metastatic breast cancer patients using large NGS panels.

Next generation sequencing of cell-free DNA (cfDNA) is a promising method for treatment monitoring and therapy selection in metastatic breast cancer (MBC). However, distinguishing tumor-specific variants from sequencing artefacts and germline variation with low false discovery rate is challenging when using large targeted sequencing panels covering many tumor suppressor genes. To address this, we built a machine learning model to remove false positive variant calls and augmented it with additional filters to ensure selection of tumor-derived variants. We used cfDNA of 70 MBC patients profiled with both the small targeted Oncomine breast panel (Thermofisher) and the much larger Qiaseq Human Breast Cancer Panel (Qiagen). The model was trained on the panels' common regions using Oncomine hotspot mutations as ground truth. Applied to Qiaseq data, it achieved 35% sensitivity and 36% precision, outperforming basic filtering. For 20 patients we used germline DNA to filter for somatic variants and obtained 245 variants in total, while our model found seven variants, of which six were also detected using the germline strategy. In ten tumor-free individuals, our method detected in total one (potentially germline) variant, in contrast to 521 variants detected without our model. These results indicate that our model largely detects somatic variants.

Detection of circulating tumour DNA after neoadjuvant chemoradiotherapy in patients with locally advanced oesophageal cancer.

Active surveillance instead of standard surgery after neoadjuvant chemoradiotherapy (nCRT) has been proposed for patients with oesophageal cancer. Circulating tumour DNA (ctDNA) may be used to facilitate selection of patients for surgery. We show that detection of ctDNA after nCRT seems highly suggestive of major residual disease. Tumour biopsies and blood samples were taken before, and 6 and 12 weeks after, nCRT. Biopsies were analysed with regular targeted next-generation sequencing (NGS). Circulating cell-free DNA (cfDNA) was analysed using targeted NGS with unique molecular identifiers and digital polymerase chain reaction. cfDNA mutations matching pre-treatment biopsy mutations confirmed the presence of ctDNA. In total, 31 patients were included, of whom 24 had a biopsy mutation that was potentially detectable in cfDNA (77%). Pre-treatment ctDNA was detected in nine of 24 patients (38%), four of whom had incurable disease progression before surgery. Pre-treatment ctDNA detection had a sensitivity of 47% (95% CI 24-71) (8/17), specificity of 85% (95% CI 42-99) (6/7), positive predictive value (PPV) of 89% (95% CI 51-99) (8/9), and negative predictive value (NPV) of 40% (95% CI 17-67) (6/15) for detecting major residual disease (>10% residue in the resection specimen or progression before surgery). After nCRT, ctDNA was detected in three patients, two of whom had disease progression. Post-nCRT ctDNA detection had a sensitivity of 21% (95% CI 6-51) (3/14), specificity of 100% (95% CI 56-100) (7/7), PPV of 100% (95% CI 31-100) (3/3), and NPV of 39% (95% CI 18-64) (7/18) for detecting major residual disease. The addition of ctDNA to the current set of diagnostics did not lead to more patients being clinically identified with residual disease. These results indicate that pre-treatment and post-nCRT ctDNA detection may be useful in identifying patients at high risk of disease progression. The addition of ctDNA analysis to the current set of diagnostic modalities may not improve detection of residual disease after nCRT. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Detection of tumor-derived extracellular vesicles in plasma from patients with solid cancer.

BACKGROUND: Extracellular vesicles (EVs) are actively secreted by cells into body fluids and contain nucleic acids of the cells they originate from. The goal of this study was to detect circulating tumor-derived EVs (ctEVs) by mutant mRNA transcripts (EV-RNA) in plasma of patients with solid cancers and compare the occurrence of ctEVs with circulating tumor DNA (ctDNA) in cell-free DNA (cfDNA). METHODS: For this purpose, blood from 20 patients and 15 healthy blood donors (HBDs) was collected in different preservation tubes (EDTA, BCT, CellSave) and processed into plasma within 24 h from venipuncture. EVs were isolated with the ExoEasy protocol from this plasma and from conditioned medium of 6 cancer cell lines and characterized according to MISEV2018-guidelines. RNA from EVs was isolated with the ExoRNeasy protocol and evaluated for transcript expression levels of 96 genes by RT-qPCR and genotyped by digital PCR. RESULTS: Our workflow applied on cell lines revealed a high concordance between cellular mRNA and EV-RNA in expression levels as well as variant allele frequencies for PIK3CA, KRAS and BRAF. Plasma CD9-positive EV and GAPDH EV-RNA levels were significantly different between the preservation tubes. The workflow detected only ctEVs with mutant transcripts in plasma of patients with high amounts (> 20%) of circulating tumor DNA (ctDNA). Expression profiling showed that the EVs from patients resemble healthy donors more than tumor cell lines supporting that most EVs are derived from healthy tissue. CONCLUSIONS: We provide a workflow for ctEV detection by spin column-based generic isolation of EVs and PCR-based measurement of gene expression and mutant transcripts in EV-RNA derived from cancer patients' blood plasma. This workflow, however, detected tumor-specific mutations in blood less often in EV-RNA than in cfDNA.

IGF1R signaling drives antiestrogen resistance through PAK2/PIX activation in luminal breast cancer.

Antiestrogen resistance in estrogen receptor positive (ER+) breast cancer is associated with increased expression and activity of insulin-like growth factor 1 receptor (IGF1R). Here, a kinome siRNA screen has identified 10 regulators of IGF1R-mediated antiestrogen with clinical significance. These include the tamoxifen resistance suppressors BMPR1B, CDK10, CDK5, EIF2AK1, and MAP2K5, and the tamoxifen resistance inducers CHEK1, PAK2, RPS6KC1, TTK, and TXK. The p21-activated kinase 2, PAK2, is the strongest resistance inducer. Silencing of the tamoxifen resistance inducing genes, particularly PAK2, attenuates IGF1R-mediated resistance to tamoxifen and fulvestrant. High expression of PAK2 in ER+ metastatic breast cancer patients is correlated with unfavorable outcome after first-line tamoxifen monotherapy. Phospho-proteomics has defined PAK2 and the PAK-interacting exchange factors PIXα/ß as downstream targets of IGF1R signaling, which are independent from PI3K/ATK and MAPK/ERK pathways. PAK2 and PIXα/ß modulate IGF1R signaling-driven cell scattering. Targeting PIXα/ß entirely mimics the effect of PAK2 silencing on antiestrogen re-sensitization. These data indicate PAK2/PIX as an effector pathway in IGF1R-mediated antiestrogen resistance.

Increased MAPK1/3 Phosphorylation in Luminal Breast Cancer Related with PIK3CA Hotspot Mutations and Prognosis.

INTRODUCTION: While mutations in PIK3CA are most frequently (45%) detected in luminal breast cancer, downstream PI3K/AKT/mTOR pathway activation is predominantly observed in the basal subtype. The aim was to identify proteins activated in PIK3CA mutated luminal breast cancer and the clinical relevance of such a protein in breast cancer patients. MATERIALS AND METHODS: Expression levels of 171 signaling pathway (phospho-)proteins established by The Cancer Genome Atlas (TCGA) using reverse phase protein arrays (RPPA) were in silico examined in 361 breast cancers for their relation with PIK3CA status. MAPK1/3 phosphorylation was evaluated with immunohistochemistry on tissue microarrays (TMA) containing 721 primary breast cancer core biopsies to explore the relationship with metastasis-free survival. RESULTS: In silico analyses revealed increased phosphorylation of MAPK1/3, p38 and YAP, and decreased expression of p70S6K and 4E-BP1 in PIK3CA mutated compared to wild-type luminal breast cancer. Augmented MAPK1/3 phosphorylation was most significant, i.e. in luminal A for both PIK3CA exon 9 and 20 mutations and in luminal B for exon 9 mutations. In 290 adjuvant systemic therapy naïve lymph node negative (LNN) breast cancer patients with luminal cancer, high MAPK phosphorylation in nuclei (HR=0.49; 95% CI, 0.25-0.95; P=.036) and in tumor cells (HR=0.37; 95% CI, 0.18-0.79; P=.010) was related with favorable metastasis-free survival in multivariate analyses including traditional prognostic factors. CONCLUSION: Enhanced MAPK1/3 phosphorylation in luminal breast cancer is related to PIK3CA exon-specific mutations and correlated with favorable prognosis especially when located in the nuclei of tumor cells.