Detection of KRAS, NRAS and BRAF by mass spectrometry - a sensitive, reliable, fast and cost-effective technique

Background: According to current clinical guidelines mutational analysis for KRAS and NRAS is recommended prior to EGFR-directed therapy of colorectal cancer (CRC) in the metastatic setting. Therefore, reliable, fast, sensitive and cost-effective methods for routine tissue based molecular diagnostics are required that allow the assessment of the CRC mutational status in a high throughput fashion. Methods: We have developed a custom designed assay for routine mass-spectrometric (MS) (MassARRAY®, Agena Bioscience) analysis to test the presence/absence of 18 KRAS, 14 NRAS and 4 BRAF mutations. We have applied this assay to 93 samples from patients with CRC and have compared the results with Sanger sequencing and a chip hybridization assay (KRAS LCD-array Kit, Chipron). In cases with discordant results, next-generation sequencing (NGS) was performed. Results: MS detected a KRAS mutation in 46/93 (49 %), a NRAS mutation in 2/93 (2 %) and a BRAF mutation in 1/93 (1 %) of the cases. MS results were in agreement with results obtained by combination of the two other methods in 92 (99 %) of 93 cases. In 1/93 (1 %) of the cases a G12V mutation has been detected by Sanger sequencing and MS, but not by the chip assay. In this case, NGS has confirmed the G12V mutation in KRAS. Conclusions: Mutational analysis by MS is a reliable method for routine diagnostic use, which can be easily extended for testing of additional mutations

Susceptibility to collagen-induced arthritis is modulated by TGFβ responsiveness of T cells

The objective of our study was to determine the regulatory effects that endogenous transforming growth factor β (TGFβ) exerts on T cells in the pathogenesis of collagen-induced arthritis (CIA). CIA was induced in transgenic mice expressing a dominant negative TGFβ type II receptor in T cells under the control of the human CD2 promoter. Clinical and histological arthritis scores were determined and experiments on disease induction and the healing phase of disease were performed. The proliferation and cytokine production of draining lymph node cells in vitro were analyzed. Transgenic mice were more susceptible to induction of CIA. The overall incidence was higher in transgenic mice than in wild-type mice (57% vs 35%, P < 0.05). Affected transgenic animals displayed a significantly higher clinical (4.5 ± 0.6 vs 1.67 ± 0.19, P = 0.001) and histological arthritis score (8.01 ± 0.9 vs 4.06 ± 1.1, P < 0.05). Draining lymph node cells of transgenic mice secreted more tumor necrosis factor α and IFNγ and proliferated more vigorously in response to collagen type II and upon CD3/CD28 costimulation in vitro. Therefore, the regulation of T cells by endogenous TGFβ is important for the maintenance of joint integrity after arthritis induction. Defects in TGFβ-signalling as a susceptibility factor for rheumatoid arthritis may warrant further investigation

Fra-2 transgenic mice as a novel model of pulmonary hypertension associated with systemic sclerosis

Objective: Systemic sclerosis-associated pulmonary arterial hypertension differs from idiopathic pulmonary arterial hypertension with respect to histopathology, treatment responses and survival. Medical progress on PAH is hampered by the lack of human biosamples and suitable animal models. In this study, the authors evaluated fos-related antigen 2 (Fra-2) transgenic mice as a novel model for systemic sclerosis-associated pulmonary arterial hypertension. Methods: Lung sections of Fra-2 transgenic (n=12) and wild-type mice (n=6) were analysed at 16 weeks by histology using Dana Point criteria. Cellular and molecular key players were assessed by immunohistochemistry. To test the model's sensitivity to change over treatment, a subgroup of Fra-2 transgenic mice (n=6) was treated with the tyrosine kinase inhibitor nilotinib twice daily 37.5 mg orally from 8 weeks of age. Results: Fra-2 transgenic mice developed severe vascular remodelling of pulmonary arteries and non-specific interstitial pneumonia-like interstitial lung disease resembling human systemic sclerosis-associated pulmonary hypertension. Histological features typical for systemic sclerosis-associated pulmonary arterial hypertension, such as intimal thickening with concentric laminar lesions, medial hypertrophy, perivascular inflammatory infiltrates, adventitial fibrosis, but not pulmonary occlusive venopathy were frequently detected. Platelet-derived growth factor signalling pathways were activated in pulmonary vessels of Fra-2 transgenic compared with wild-type mice. Since treatment with nilotinib strongly prevented the development of proliferative vasculopathy and lung fibrosis, the model proved to be sensitive to treatment. Conclusions: This study suggests that Fra-2 transgenic mice as an animal model of systemic sclerosis-associated pulmonary arterial hypertension display main characteristic features of the human disease. It therefore allows studying pathophysiological aspects and might serve as a preclinical model for interventional proof-of-concept studies

Deep learning for the detection of anatomical tissue structures and neoplasms of the skin on scanned histopathological tissue sections

Basal cell carcinoma (BCC), squamous cell carcinoma (SqCC) and melanoma are among the most common cancer types. Correct diagnosis based on histological evaluation after biopsy or excision is paramount for adequate therapy stratification. Deep learning on histological slides has been suggested to complement and improve routine diagnostics, but publicly available curated and annotated data and usable models trained to distinguish common skin tumors are rare and often lack heterogeneous non-tumor categories. A total of 16 classes from 386 cases were manually annotated on scanned histological slides, 129,364 100 x 100 µm (~395 x 395 px) image tiles were extracted and split into a training, validation and test set. An EfficientV2 neuronal network was trained and optimized to classify image categories. Cross entropy loss, balanced accuracy and Matthews correlation coefficient were used for model evaluation. Image and patient data were assessed with confusion matrices. Application of the model to an external set of whole slides facilitated localization of melanoma and non-tumor tissue. Automated differentiation of BCC, SqCC, melanoma, naevi and non-tumor tissue structures was possible, and a high diagnostic accuracy was achieved in the validation (98%) and test (97%) set. In summary, we provide a curated dataset including the most common neoplasms of the skin and various anatomical compartments to enable researchers to train, validate and improve deep learning models. Automated classification of skin tumors by deep learning techniques is possible with high accuracy, facilitates tumor localization and has the potential to support and improve routine diagnostics

Detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) including Variant Analysis by Mass Spectrometry in Placental Tissue

Among neonates, tested positive for SARS-CoV-2, the majority of infections occur through postpartum transmission. Only few reports describe intrauterine or intrapartum SARS-CoV-2 infections in newborns. To understand the route of transmission, detection of the virus or virus nucleic acid in the placenta and amniotic tissue are of special interest. Current methods to detect SARS-CoV-2 in placental tissue are immunohistochemistry, electron microscopy, in-situ hybridization, polymerase chain reaction (PCR) and next-generation sequencing. Recently, we described an alternative method for the detection of viral ribonucleic acid (RNA), by combination of reverse transcriptase-PCR and mass spectrometry (MS) in oropharyngeal and oral swabs. In this report, we could detect SARS-CoV-2 in formal-fixed and paraffin-embedded (FFPE) placental and amniotic tissue by multiplex RT-PCR MS. Additionally, we could identify the British variant (B.1.1.7) of the virus in this tissue by the same methodology. Combination of RT-PCR with MS is a fast and easy method to detect SARS-CoV-2 viral RNA, including specific variants in FFPE tissue