PCIG: a web-based application to explore immune-genomics interactions across cancer types.

MOTIVATION: Genomic alterations can modulate the tumor immunophenotype depending on their nature and tissue of origin. Although this immune-genomic interaction may shape disease progression and response to immunotherapy, the factors governing such dynamics and the influence of each tissue-specific context remain poorly understood. RESULTS: Here, we have developed the PanCancer ImmunoGenomics (PCIG) tool, a web-based resource that provides researchers with the opportunity to mine immunome-genome relationships across several cancer types using data from the Pan-Cancer Analysis of Whole-Genomes (PCAWG) study, which comprises >2,600 samples spanning across 20 different cancer primary sites. PCIG yields an integrative analysis of the crosstalk between somatic genomic alterations and different immune features, thus helping to understand immune response-related processes. AVAILABILITY AND IMPLEMENTATION: PCIG is freely available at https://pcig.vhio.net and is supported by all major web browsers. PCIG was developed with Django, which is a Python-based free and open-source framework, and it uses SQL Server as a relational database management system. The code is freely available for download at GitHub https://github.com/AnnaPG/PCIG and in its online supplementary material. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Efficacy of chemotherapy for malignant pleural mesothelioma according to histology in a real-world cohort.

CheckMate 743 trial demonstrated survival benefit of immunotherapy in first line in MPM with some differences in the efficacy of chemotherapy according to histology. The objective of this study is to characterize the impact of chemotherapy according to histology in patients diagnosed with MPM at our institution. Clinical records of all MPM patients diagnosed at Vall d'Hebron University Hospital between November 2002 and April 2020 were reviewed. Associations between clinical variables and outcomes were assessed with Cox regression models. Survival data were calculated by the Kaplan-Meier method. 189 patients were included with 76% of tumors classified as epithelioid subtype. First line chemotherapy was offered to 85% of patients. Median survival in overall population was 21.3 months (95% CI 17.2-24.3). We found that patients with epithelioid tumors had better overall survival (OS) and progression free survival (PFS). Median OS of epithelioid patients treated with first line chemotherapy was 26.7 months versus 15.0 months in non-epithelioid patients (HR 2.25 CI 95% 1.4-3.4; p < 0.001). Median PFS for patients with epithelioid tumors treated with chemotherapy was 4.8 months versus 3.6 months in non-epithelioid (HR 1.5 CI 95% 1.0-2.3; p = 0.03). The improvement of outcomes in patients with epithelioid histology was detected in patients treated with cisplatin or carboplatin. Histology was not a predictive factor for the platinum agent sensitivity (p of interaction PFS = 0.09, p of interaction OS = 0.65). In our series, patients with non-epithelioid tumors presented worse prognosis. Although epithelioid tumors exposed to cisplatin had higher PFS, histology was not a clear predictor of chemotherapy efficacy.

Phase I prognostic online (PIPO): A web tool to improve patient selection for oncology early phase clinical trials.

PURPOSE: Patient selection in phase 1 clinical trials (Ph1t) continues to be a challenge. The aim of this study was to develop a user-friendly prognostic calculator for predicting overall survival (OS) outcomes in patients to be included in Ph1t with immune checkpoint inhibitors (ICIs) or targeted agents (TAs) based on clinical parameters assessed at baseline. METHODS: Using a training cohort with consecutive patients from the VHIO phase 1 unit, we constructed a prognostic model to predict median OS (mOS) as a primary endpoint and 3-month (3m) OS rate as a secondary endpoint. The model was validated in an internal cohort after temporal data splitting and represented as a web application. RESULTS: We recruited 799 patients (training and validation sets, 558 and 241, respectively). Median follow-up was 21.2 months (m), mOS was 10.2 m (95% CI, 9.3-12.7) for ICIs cohort and 7.7 m (95% CI, 6.6-8.6) for TAs cohort. In the multivariable analysis, six prognostic variables were independently associated with OS - ECOG, number of metastatic sites, presence of liver metastases, derived neutrophils/(leukocytes minus neutrophils) ratio [dNLR], albumin and lactate dehydrogenase (LDH) levels. The phase 1 prognostic online (PIPO) calculator showed adequate discrimination and calibration performance for OS, with C-statistics of 0.71 (95% CI 0.64-0.78) in the validation set. The overall accuracy of the model for 3m OS prediction was 87.2% (95% CI 85%-90%). CONCLUSIONS: PIPO is a user-friendly objective and interactive tool to calculate specific survival probabilities for each patient before enrolment in a Ph1t. The tool is available at https://pipo.vhio.net/.

Multiple stable conformations account for reversible concentration-dependent oligomerization and autoinhibition of a metamorphic metallopeptidase.

Molecular plasticity controls enzymatic activity: the native fold of a protein in a given environment is normally unique and at a global free-energy minimum. Some proteins, however, spontaneously undergo substantial fold switching to reversibly transit between defined conformers, the "metamorphic" proteins. Here, we present a minimal metamorphic, selective, and specific caseinolytic metallopeptidase, selecase, which reversibly transits between several different states of defined three-dimensional structure, which are associated with loss of enzymatic activity due to autoinhibition. The latter is triggered by sequestering the competent conformation in incompetent but structured dimers, tetramers, and octamers. This system, which is compatible with a discrete multifunnel energy landscape, affords a switch that provides a reversible mechanism of control of catalytic activity unique in nature.

A novel family of soluble minimal scaffolds provides structural insight into the catalytic domains of integral membrane metallopeptidases.

In the search for structural models of integral-membrane metallopeptidases (MPs), we discovered three related proteins from thermophilic prokaryotes, which we grouped into a novel family called "minigluzincins." We determined the crystal structures of the zymogens of two of these (Pyrococcus abyssi proabylysin and Methanocaldococcus jannaschii projannalysin), which are soluble and, with ∼100 residues, constitute the shortest structurally characterized MPs to date. Despite relevant sequence and structural similarity, the structures revealed two unique mechanisms of latency maintenance through the C-terminal segments previously unseen in MPs as follows: intramolecular, through an extended tail, in proabylysin, and crosswise intermolecular, through a helix swap, in projannalysin. In addition, structural and sequence comparisons revealed large similarity with MPs of the gluzincin tribe such as thermolysin, leukotriene A4 hydrolase relatives, and cowrins. Noteworthy, gluzincins mostly contain a glutamate as third characteristic zinc ligand, whereas minigluzincins have a histidine. Sequence and structural similarity further allowed us to ascertain that minigluzincins are very similar to the catalytic domains of integral membrane MPs of the MEROPS database families M48 and M56, such as FACE1, HtpX, Oma1, and BlaR1/MecR1, which are provided with trans-membrane helices flanking or inserted into a minigluzincin-like catalytic domain. In a time where structural biochemistry of integral-membrane proteins in general still faces formidable challenges, the minigluzincin soluble minimal scaffold may contribute to our understanding of the working mechanisms of these membrane MPs and to the design of novel inhibitors through structure-aided rational drug design approaches.