ORGAVADS: establishment of tumor organoids from head and neck squamous cell carcinoma to assess their response to innovative therapies.

BACKGROUND: Radiotherapy is one of the cornerstones of the treatment of Head and Neck Squamous Cell Carcinomas (HNSCC). However, radioresistance is associated with a high risk of recurrence. To propose strategies (such as combinations with drugs) that could over intrinsic radioresistance, it is crucial to predict the response to treatment. Patient-Derived Tumor Organoids (PDTO) are in vitro tridimensional microtumors obtained from patient' own cancer samples. They have been shown to serve as reliable surrogates of the tumor response in patients. METHODS: The ORGAVADS study is a multicenter observational trial conducted to investigate the feasibility of generating and testing PDTO derived from HNSCC for the evaluation of sensitivity to treatments. PDTO are obtained after dissociation of resected tumors remaining from tissues necessary for the diagnosis. Embedding of tumor cells is then performed in extracellular matrix and culture in medium supplemented with growth factors and inhibitors. Histological and immunohistochemical characterizations are performed to validate the resemblance between PDTO and their original tumor. Response of PDTO to chemotherapy, radiotherapy and innovating combinations are assessed, as well as response to immunotherapy using co-cultures of PDTO with autologous immune cells collected from patient blood samples. Transcriptomic and genetic analyses of PDTO allow validation of the models compared to patients' own tumor and identification of potential predictive biomarkers. DISCUSSION: This study is designed to develop PDTO models from HNSCC. It will allow comparing the response of PDTO to treatment and the clinical response of the patients from whom they are derived. Our aim is to study the PDTO ability to predict the clinical response to treatment for each patient in view of a personalized medicine as well as to establish a collection of HNSCC models that will be useful for future innovative strategies evaluation. TRIAL REGISTRATION: NCT04261192, registered February 7, 2020, last amendment v4 accepted on June, 2021.

Using a convolutional neural network for classification of squamous and non-squamous non-small cell lung cancer based on diagnostic histopathology HES images.

Histological stratification in metastatic non-small cell lung cancer (NSCLC) is essential to properly guide therapy. Morphological evaluation remains the basis for subtyping and is completed by additional immunohistochemistry labelling to confirm the diagnosis, which delays molecular analysis and utilises precious sample. Therefore, we tested the capacity of convolutional neural networks (CNNs) to classify NSCLC based on pathologic HES diagnostic biopsies. The model was estimated with a learning cohort of 132 NSCLC patients and validated on an external validation cohort of 65 NSCLC patients. Based on image patches, a CNN using InceptionV3 architecture was trained and optimized to classify NSCLC between squamous and non-squamous subtypes. Accuracies of 0.99, 0.87, 0.85, 0.85 was reached in the training, validation and test sets and in the external validation cohort. At the patient level, the CNN model showed a capacity to predict the tumour histology with accuracy of 0.73 and 0.78 in the learning and external validation cohorts respectively. Selecting tumour area using virtual tissue micro-array improved prediction, with accuracy of 0.82 in the external validation cohort. This study underlines the capacity of CNN to predict NSCLC subtype with good accuracy and to be applied to small pathologic samples without annotation.

Prognostic value of Thyroid Transcription Factor-1 expression in lung adenocarcinoma in patients treated with anti PD-1/PD-L1.

Anti-PD1/PD-L1-directed immune checkpoint inhibitors are game changers in advanced non-small-cell lung cancer, but biomarkers are lacking. The aim of our study was to find clinically relevant biomarkers of the efficacy of ICI in non-squamous NSCLC. We conducted a retrospective study of patients receiving ICI for advanced non squamous NSCLC in two cohorts. For a subset of patients, RNAseq data were generated on tumor biopsy taken before ICI. The primary end point was progression-free survival under ICI. Secondary end point was overall survival from ICI initiation. In the cohort, we studied 231 patients. Clinico-pathological characteristics included KRAS mutant status (n = 88), TTF1-positive expression (n = 136), LIPI (Lung Immune Prognostic Index) score of 0 (n = 116). In our cohort, lack of TTF1 expression, LIPI score >0, line of treatment >1, and liver metastases were associated with poorer PFS. TTF1 and PD-L1 status could be used to stratify survival and improve the AUC for prediction of prognosis in comparison with the PD-L1 gold standard. Using an external cohort of 154 patients, we confirmed the independent prognostic role of TTF1. TTF1 expression and PD-L1 can be used to stratify risk and predict PFS and OS in patients treated with ICI for NS-NSCLC.

Usefulness of Flow Cytometry for the Detection of Cutaneous Localization in Malignant Hematologic Disorders.

BACKGROUND: Histological evaluation of malignant hematologic involvement of the skin can be challenging and needs an extended immunohistochemistry panel. We assessed the ability of flow cytometry (FCM) to detect neoplastic cell subsets in skin biopsies as a useful tool that supplements the histological examination in a complementary way. METHODS: Two hundred and forty-three consecutive skin biopsies were retrospectively analyzed between April 2012 and July 2017. RESULTS: Among them, 147 samples, corresponding to 128 patients, were analyzed at diagnosis. Eighty-seven patients had erythrodermic inflammatory dermatoses, and 41 patients had cutaneous hematologic neoplasms. Cutaneous T-cell lymphomas were the most frequent disorders, accounting for 70% of cases (29/41). Cutaneous B-cell lymphoma was found in only 17% of cases (7/41) and immature hematologic malignancies in 5% (2/41). Three patients had secondary skin involvement. The sensitivity of FCM skin biopsy analysis was 78.1% (32/41). Among the 243 samples, 27 patients had mycosis fungoides (MF) or Sezary syndrome (SS) with available FCM data. A loss of CD26 expression was identified in 92% of cases of transformed MF or SS versus 40% of cases of non-transformed MF (P = 0.0057 χ²). Among the 12 MF patients with negative CD26 expression, six progressed to SS versus none in the positive group (50% vs. 0% P = 0.0168 χ²). CONCLUSIONS: FCM analysis of the skin biopsies is a sensitive method and a useful tool for improving the sensitivity of diagnosis of hematologic skin neoplasms. Among the MF patients, a loss of CD26 expression could be a marker of higher risk of progression. © 2019 International Clinical Cytometry Society.