Federating heterogeneous datasets to enhance data sharing and experiment reproducibility

Recent studies have demonstrated the difficulties to replicate scientific findings and/or experiments published in past.1 The effects seen in the replicated experiments were smaller than previously reported. Some of the explanations for these findings include the complexity of the experimental design and the pressure on researches to report positive findings. The International Committee of Medical Journal Editors (ICMJE) suggests that every study considered for publication must submit a plan to share the de-identified patient data no later than 6 months after publication. There is a growing demand to enhance the management of clinical data, facilitate data sharing across institutions and also to keep track of the data from previous experiments. The ultimate goal is to assure the reproducibility of experiments in the future. This paper describes Shiny-tooth, a web based application created to improve clinical data acquisition during the clinical trial; data federation of such data as well as morphological data derived from medical images; Currently, this application is being used to store clinical data from an osteoarthritis (OA) study. This work is submitted to the SPIE Biomedical Applications in Molecular, Structural, and Functional Imaging conference

Genomic staging of multifocal lung squamous cell carcinomas is independent of the comprehensive morphologic assessment.

Morphologic and molecular data for staging of multifocal lung squamous cell carcinomas (LSCC) are limited. In this study, whole exome sequencing (WES) was used as the gold standard to determine if multifocal LSCC represented separate primary cancers (SPLC) or intrapulmonary metastases (IPM). Genomic profiles were compared to the comprehensive morphologic assessment. WES was performed on 20 tumor pairs of multifocal LSCC and matched normal lymph nodes using the Illumina NovaSeq6000 S4-Xp (Illumina, San Diego, CA). WES clonal and subclonal analysis data were compared with histological assessment by 16 thoracic pathologists. Additionally, the immune gene profiling of the study cases was characterized by the HTG EdgeSeq Precision Immuno-Oncology Panel. By WES data, eleven cases were classified as SPLC, while seven cases were IPM. Two cases were technically suboptimal. Analysis showed marked genomic and immunogenic heterogeneity, but immune gene expression profiles highly correlated with mutation profiles. Tumors classified as IPM have a large number of shared mutations (ranging from 33.5% to 80.7%) The agreement between individual morphological assessments for each case and WES was 58.3%. One case was unanimously interpreted morphologically as IPM and was in agreement with WES. In a further 17 cases, the number of pathologists whose morphological interpretation was in agreement with WES ranged from two (1 case) up to fifteen pathologists (1 case) per case. Pathologists showed a fair inter-observer agreement in the morphologic staging of multiple LSCC, with an overall kappa of 0.232. Staging of multifocal LSCC based on morphologic assessment is unreliable. Comprehensive genomic analyses should be adopted for the staging of multifocal LSCC

Reproducibility of histopathological subtypes and invasion in pulmonary adenocarcinoma. An international interobserver study

Histological subtyping of pulmonary adenocarcinoma has recently been updated based on predominant pattern, but data on reproducibility are required for validation. This study first assesses reproducibility in subtyping adenocarcinomas and then assesses further the distinction between invasive and non-invasive (wholly lepidic) pattern of adenocarcinoma, among an international group of pulmonary pathologists. Two ring studies were performed using a micro-photographic image-based method, evaluating selected images of lung adenocarcinoma histologic patterns. In the first study, 26 pathologists reviewed representative images of typical and 'difficult' histologic patterns. A total number of scores for the typical patterns combined (n=94) and the difficult cases (n=21) were 2444 and 546, respectively. The mean kappa score (\ub1s.d.) for the five typical patterns combined and for difficult cases were 0.77\ub10.07 and 0.38\ub10.14, respectively. Although 70% of the observers identified 12-65% of typical images as single pattern, highest for solid and least for micropapillary, recognizing the predominant pattern was achieved in 92-100%, of the images except for micropapillary pattern (62%). For the second study on invasion, identified as a key problem area from the first study, 28 pathologists submitted and reviewed 64 images representing typical as well as 'difficult' examples. The kappa for typical and difficult cases was 0.55\ub10.06 and 0.08\ub10.02, respectively, with consistent subdivision by the same pathologists into invasive and non-invasive categories, due to differing interpretation of terminology defining invasion. In pulmonary adenocarcinomas with classic morphology, which comprise the majority of cases, there is good reproducibility in identifying a predominant pattern and fair reproducibility distinguishing invasive from in-situ (wholly lepidic) patterns. However, more precise definitions and better education on interpretation of existing terminology are required to improve recognition of purely in-situ disease, this being an area of increasing importance

The Promises and Challenges of Tumor Mutation Burden as an Immunotherapy Biomarker: A Perspective from the International Association for the Study of Lung Cancer Pathology Committee.

Immune checkpoint inhibitor (ICI) therapies have revolutionized the management of patients with NSCLC and have led to unprecedented improvements in response rates and survival in a subset of patients with this fatal disease. However, the available therapies work only for a minority of patients, are associated with substantial societal cost, and may lead to considerable immune-related adverse events. Therefore, patient selection must be optimized through the use of relevant biomarkers. Programmed death-ligand 1 protein expression by immunohistochemistry is widely used today for the selection of programmed cell death protein 1 inhibitor therapy in patients with NSCLC; however, this approach lacks robust sensitivity and specificity for predicting response. Tumor mutation burden (TMB), or the number of somatic mutations derived from next-generation sequencing techniques, has been widely explored as an alternative or complementary biomarker for response to ICIs. In theory, a higher TMB increases the probability of tumor neoantigen production and therefore, the likelihood of immune recognition and tumor cell killing. Although TMB alone is a simplistic surrogate of this complex interplay, it is a quantitative variable that can be relatively readily measured using currently available sequencing techniques. A large number of clinical trials and retrospective analyses, employing both tumor and blood-based sequencing tools, have evaluated the performance of TMB as a predictive biomarker, and in many cases reveal a correlation between high TMB and ICI response rates and progression-free survival. Many challenges remain before the implementation of TMB as a biomarker in clinical practice. These include the following: (1) identification of therapies whose response is best informed by TMB status; (2) robust definition of a predictive TMB cut point; (3) acceptable sequencing panel size and design; and (4) the need for robust technical and informatic rigor to generate precise and accurate TMB measurements across different laboratories. Finally, effective prediction of response to ICI therapy will likely require integration of TMB with a host of other potential biomarkers, including tumor genomic driver alterations, tumor-immune milieu, and other features of the host immune system. This perspective piece will review the current clinical evidence for TMB as a biomarker and address the technical sequencing considerations and ongoing challenges in the use of TMB in routine practice