Longitudinal Study of Advanced Non-Small Cell Lung Cancer with Initial Durable Clinical Benefit to Immunotherapy: Strategies for Anti-PD-1/PD-L1 Continuation beyond Progression.

BACKGROUND AND AIM: A better understanding of resistance to checkpoint inhibitors is essential to define subsequent treatments in advanced non-small cell lung cancer. By characterizing clinical and radiological features of progression after anti-programmed death-1/programmed death ligand-1 (anti-PD-1/PD-L1), we aimed to define therapeutic strategies in patients with initial durable clinical benefit. PATIENTS AND METHODS: This monocentric, retrospective study included patients who presented progressive disease (PD) according to RECIST 1.1 criteria after anti-PD-1/PD-L1 monotherapy. Patients were classified into two groups, "primary resistance" and "Progressive Disease (PD) after Durable Clinical Benefit (DCB)", according to the Society of Immunotherapy of Cancer classification. We compared the post-progression survival (PPS) of both groups and analyzed the patterns of progression. An exploratory analysis was performed using the tumor growth rate (TGR) to assess the global growth kinetics of cancer and the persistent benefit of immunotherapy beyond PD after DCB. RESULTS: A total of 148 patients were included; 105 of them presented "primary resistance" and 43 "PD after DCB". The median PPS was 5.2 months (95% CI: 2.6-6.5) for primary resistance (p < 0.0001) vs. 21.3 months (95% CI: 18.5-36.3) for "PD after DCB", and the multivariable hazard ratio was 0.14 (95% CI: 0.07-0.30). The oligoprogression pattern was frequent in the "PD after DCB" group (76.7%) and occurred mostly in pre-existing lesions (72.1%). TGR deceleration suggested a persistent benefit of PD-1/PD-L1 blockade in 44.2% of cases. CONCLUSIONS: PD after DCB is an independent factor of longer post-progression survival with specific patterns that prompt to contemplate loco-regional treatments. TGR is a promising tool to assess the residual benefit of immunotherapy and justify the continuation of immunotherapy in addition to radiotherapy or surgery.

How to Improve Cancer Patients ENrollment in Clinical Trials From rEal-Life Databases Using the Observational Medical Outcomes Partnership Oncology Extension: Results of the PENELOPE Initiative in Urologic Cancers.

PURPOSE: To compare the computability of Observational Medical Outcomes Partnership (OMOP)-based queries related to prescreening of patients using two versions of the OMOP common data model (CDM; v5.3 and v5.4) and to assess the performance of the Greater Paris University Hospital (APHP) prescreening tool. MATERIALS AND METHODS: We identified the prescreening information items being relevant for prescreening of patients with cancer. We randomly selected 15 academic and industry-sponsored urology phase I-IV clinical trials (CTs) launched at APHP between 2016 and 2021. The computability of the related prescreening criteria (PC) was defined by their translation rate in OMOP-compliant queries and by their execution rate on the APHP clinical data warehouse (CDW) containing data of 205,977 patients with cancer. The overall performance of the prescreening tool was assessed by the rate of true- and false-positive cases of three randomly selected CTs. RESULTS: We defined a list of 15 minimal information items being relevant for patients' prescreening. We identified 83 PC of the 534 eligibility criteria from the 15 CTs. We translated 33 and 62 PC in queries on the basis of OMOP CDM v5.3 and v5.4, respectively (translation rates of 40% and 75%, respectively). Of the 33 PC translated in the v5.3 of the OMOP CDM, 19 could be executed on the APHP CDW (execution rate of 58%). Of 83 PC, the computability rate on the APHP CDW reached 23%. On the basis of three CTs, we identified 17, 32, and 63 patients as being potentially eligible for inclusion in those CTs, resulting in positive predictive values of 53%, 41%, and 21%, respectively. CONCLUSION: We showed that PC could be formalized according to the OMOP CDM and that the oncology extension increased their translation rate through better representation of cancer natural history.

Chemotherapy-induced ileitis associated or not with colitis in digestive oncology patients: An AGEO multicentre study.

BACKGROUND: The characteristics and management of ileitis induced by chemotherapy in cancer patients are poorly described in the literature. METHODS: This retrospective multicentre study enroled patients hospitalized in a digestive oncology unit for a symptomatic chemotherapy-induced ileitis. RESULTS: Forty-three patients were included, with a regimen based on fluoropyrimidine and/or irinotecan in 95% of cases. Five patients were excluded due to the diagnosis of infectious ileitis (Clostridium difficile in 3 patients, Campylobacter jejuni in 1 patient and cytomegalovirus in 1 patient). The most frequently described symptoms were diarrhoea (77% including 54% of grade 3-4 diarrhoea), abdominal pain (58%), fever (51%) and vomiting (56%). An ileo-colonoscopy was performed in 35% of patients and did not show any specific results or severity criteria. The ileitis was complicated by bowel perforation and/or obstruction in 3 patients. Disease progression was favourable in 1-2 weeks in the vast majority of cases, on symptomatic treatment, allowing resumption of the chemotherapy regimen involved in 67% of patients. CONCLUSION: Chemotherapy-induced ileitis is a rare complication that most often involves fluoropyri-midine- and/or irinotecan-based regimens. In most cases, endoscopic examinations were not contributory and do not seem useful in the event of non-severe symptomatology which most often develops favourably on symptomatic therapy, allowing resumption of the chemotherapy involved.

Using an Ontological Representation of Chemotherapy Toxicities for Guiding Information Extraction and Integration from EHRs.

INTRODUCTION: Chemotherapies against cancers are often interrupted due to severe drug toxicities, reducing treatment opportunities. For this reason, the detection of toxicities and their severity from EHRs is of importance for many downstream applications. However toxicity information is dispersed in various sources in the EHRs, making its extraction challenging. METHODS: We introduce OntoTox, an ontology designed to represent chemotherapy toxicities, its attributes and provenance. We illustrated the interest of OntoTox by integrating toxicities and grading information extracted from three heterogeneous sources: EHR questionnaires, semi-structured tables, and free-text. RESULTS: We instantiated 53,510, 2,366 and 54,420 toxicities from questionnaires, tables and free-text respectively, and compared the complementarity and redundancy of the three sources. DISCUSSION: We illustrated with this preliminary study the potential of OntoTox to guide the integration of multiple sources, and identified that the three sources are only moderately overlapping, stressing the need for a common representation.

viroCapt: A Bioinformatics Pipeline for Identifying Viral Insertion in Human Host Genome.

INTRODUCTION: The implication of viruses in human cancers, as well as the emergence of next generation sequencing has permitted to investigate further their role and pathophysiology in the development of this disease. One such mechanism is the integration of portions of viral genomes in the human genome, as well as the specific action of viral oncogenes.inding integration sites and preserved oncogenes is still relying on heavy manual intervention. METHODS: We developed an analysis and interpretation pipeline to determine viral insertions. Using data from directed viral capture, the pipeline conducts a crude genotyping phase to select reference viral genomes, identifies chimeric reads, extracts the putative human sequences to locate in the human reference genome, scores and ranks candidate junctions, and exports tabular and visual results. RESULTS: We leverage common bioinformatics tools (bowtie2, samtools, blat), and a dedicated filtering and ranking algorithm, implemented in R, to infer candidate junctions and insertions. Static results (tables, figures) are produced, as well as an interactive interpretation tool developed as a shiny web app. DISCUSSION: We validated this pipeline against published results of HPV, HBV, and AAV2 insertions and show good information retrieval.

Extraction of Tumor Response Criteria in Semi-Structured Imaging Report.

In this study, we extracted information from 6,376 french CT scan semi-structured text reports evaluating the cancer treatment response using the RECIST methodology. We evaluated the performance against manual annotation of 100 reports and measured the evolution of the presence of information over time. The results show high performances of the extraction as well as trends.

Overall Survival and Prognostic Factors among Older Patients with Metastatic Pancreatic Cancer: A Retrospective Analysis Using a Hospital Database.

Pre-therapeutic factors associated with overall survival (OS) among older patients ≥70 years with metastatic pancreatic cancer (mPC) are not known. This was a retrospective single-centre cohort study in Paris including 159 consecutive older patients with mPC between 2000 and 2018. Alongside geriatric parameters, specific comorbidities, cancer-related data and chemotherapy regimens were retrieved. Cox multivariate models were run to assess predictors for OS. The median age was 80 years, 52% were women, 21.5% had diabetes, and 48% had pancreatic head cancer and 72% liver metastases. 62% of the patients (n = 99) received chemotherapy, among which the gemcitabine + nab-paclitaxel (GnP) regimen was the most frequent (72%). Median OS [95%CI] was 7.40 [5.60-10.0] and 1.40 [0.90-2.20] months respectively for patients with and without chemotherapy. The GnP regimen (aHR [95%CI] = 0.47 [0.25-0.89], p = 0.02) and diabetes (aHR = 0.44 [0.24-0.77], p = 0.004) (or anti-diabetic therapy) were multivariate protective factors for death, while ECOG-PS, liver metastases, and the neutrophil cell count were multivariate risk factors for death. In the chemotherapy group, ECOG-PS, number of metastatic sites and the GnP remained significantly associated with OS. Our study confirms the feasibility and efficacy of chemotherapy and the protective effects of diabetes among older patients with mPC.

Impact of two waves of Sars-Cov2 outbreak on the number, clinical presentation, care trajectories and survival of patients newly referred for a colorectal cancer: A French multicentric cohort study from a large group of university hospitals.

The SARS-Cov2 may have impaired care trajectories, patient overall survival (OS), tumor stage at initial presentation for new colorectal cancer (CRC) cases. This study aimed at assessing those indicators before and after the beginning of the pandemic in France. In this retrospective cohort study, we collected prospectively the clinical data of the 11.4 million of patients referred to the Greater Paris University Hospitals (AP-HP). We identified new CRC cases between 1 January 2018 and 31 December 2020, and compared indicators for 2018-2019 to 2020. pTNM tumor stage was extracted from postoperative pathology reports for localized colon cancer, and metastatic status was extracted from CT-scan baseline text reports. Between 2018 and 2020, 3602 and 1083 new colon and rectal cancers were referred to the AP-HP, respectively. The 1-year OS rates reached 94%, 93% and 76% for new CRC patients undergoing a resection of the primary tumor, in 2018-2019, in 2020 without any Sars-Cov2 infection and in 2020 with a Sars-Cov2 infection, respectively (HR 3.78, 95% CI 2.1-7.1). For patients undergoing other kind of anticancer treatment, the percentages are 64%, 66% and 27% (HR 2.1, 95% CI 1.4-3.3). Tumor stage at initial presentation, emergency level of primary tumor resection, delays between the first multidisciplinary meeting and the first anticancer treatment did not differ over time. The SARS-Cov2 pandemic has been associated with less newly diagnosed CRC patients and worse 1-year OS rates attributable to the infection itself rather than to its impact on hospital care delivery or tumor stage at initial presentation.

Next-Generation Sequencing Targeted Panel in Routine Care for Metastatic Colon Cancers.

In digestive oncology, the clinical impact of targeted next-generation sequencing (NGS) in routine practice should be addressed. In this work, we studied the impact of a 22-gene NGS amplicon-based panel with Ion Torrent Proton Sequencing, prospectively performed in routine practice. We analyzed the results of extended molecular testing, beyond RAS and BRAF, in metastatic colorectal cancer (mCRC) patients in a single-center, retrospective, observational study of consecutive mCRC patients followed up at the Georges Pompidou European Hospital between January 2016 and December 2018. Overall, 210 patients with mCRC were included. Median follow-up was 25.4 months (IQR: 14.9-39.5). The three most frequently mutated genes were: TP53 (63%), KRAS (41%) and PIK3CA (19%). A positive association was found between overall survival and performance status (PS) ≥ 2 (HR: 4.91 (1.84-13.1); p = 0.001) and differentiation (HR: 4.70 (1.51-14.6); p = 0.007) in multivariate analysis. The NGS panel enabled five patients to access a targeted therapy not currently registered for CRC. In conclusion, targeted NGS panels in mCRC are feasible in routine practice, but need to be regularly updated and in-depth studies are needed to better analyze the prognostic factors.

A framework for validating AI in precision medicine: considerations from the European ITFoC consortium.

BACKGROUND: Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their implementation in health care settings remains limited, mostly due to a lack of robust validation procedures. There is a need to develop reliable assessment frameworks for the clinical validation of AI. We present here an approach for assessing AI for predicting treatment response in triple-negative breast cancer (TNBC), using real-world data and molecular -omics data from clinical data warehouses and biobanks. METHODS: The European "ITFoC (Information Technology for the Future Of Cancer)" consortium designed a framework for the clinical validation of AI technologies for predicting treatment response in oncology. RESULTS: This framework is based on seven key steps specifying: (1) the intended use of AI, (2) the target population, (3) the timing of AI evaluation, (4) the datasets used for evaluation, (5) the procedures used for ensuring data safety (including data quality, privacy and security), (6) the metrics used for measuring performance, and (7) the procedures used to ensure that the AI is explainable. This framework forms the basis of a validation platform that we are building for the "ITFoC Challenge". This community-wide competition will make it possible to assess and compare AI algorithms for predicting the response to TNBC treatments with external real-world datasets. CONCLUSIONS: The predictive performance and safety of AI technologies must be assessed in a robust, unbiased and transparent manner before their implementation in healthcare settings. We believe that the consideration of the ITFoC consortium will contribute to the safe transfer and implementation of AI in clinical settings, in the context of precision oncology and personalized care.

Placental growth factor level in plasma predicts COVID-19 severity and in-hospital mortality.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a respiratory disease associated with vascular inflammation and endothelial injury. OBJECTIVES: To correlate circulating angiogenic markers vascular endothelial growth factor A (VEGF-A), placental growth factor (PlGF), and fibroblast growth factor 2 (FGF-2) to in-hospital mortality in COVID-19 adult patients. METHODS: Consecutive ambulatory and hospitalized patients with COVID-19 infection were enrolled. VEGF-A, PlGF, and FGF-2 were measured in each patient ≤48 h following admission. RESULTS: The study enrolled 237 patients with suspected COVID-19: 208 patients had a positive diagnostic for COVID-19, of whom 23 were mild outpatients and 185 patients hospitalized after admission. Levels of VEGF-A, PlGF, and FGF-2 significantly increase with the severity of the disease (P < .001). Using a logistic regression model, we found a significant association between the increase of FGF-2 or PlGF and mortality (odds ratio [OR] 1.11, 95% confidence interval [CI; 1.07-1.16], P < .001 for FGF-2 and OR 1.07 95% CI [1.04-1.10], P < .001 for PlGF) while no association were found for VEGF-A levels. Receiver operating characteristic curve analysis was performed and we identified PlGF above 30 pg/ml as the best predictor of in-hospital mortality in COVID-19 patients. Survival analysis for PlGF confirmed its interest for in-hospital mortality prediction, by using a Kaplan-Meier survival curve (P = .001) and a Cox proportional hazard model adjusted to age, body mass index, D-dimer, and C-reactive protein (3.23 95% CI [1.29-8.11], P = .001). CONCLUSION: Angiogenic factor PlGF is a relevant predictive factor for in-hospital mortality in COVID-19 patients. More than a biomarker, we hypothesize that PlGF blocking strategies could be a new interesting therapeutic approach in COVID-19.

OSIRIS: A Minimum Data Set for Data Sharing and Interoperability in Oncology.

PURPOSE: Many institutions throughout the world have launched precision medicine initiatives in oncology, and a large amount of clinical and genomic data is being produced. Although there have been attempts at data sharing with the community, initiatives are still limited. In this context, a French task force composed of Integrated Cancer Research Sites (SIRICs), comprehensive cancer centers from the Unicancer network (one of Europe's largest cancer research organization), and university hospitals launched an initiative to improve and accelerate retrospective and prospective clinical and genomic data sharing in oncology. MATERIALS AND METHODS: For 5 years, the OSIRIS group has worked on structuring data and identifying technical solutions for collecting and sharing them. The group used a multidisciplinary approach that included weekly scientific and technical meetings over several months to foster a national consensus on a minimal data set. RESULTS: The resulting OSIRIS set and event-based data model, which is able to capture the disease course, was built with 67 clinical and 65 omics items. The group made it compatible with the HL7 Fast Healthcare Interoperability Resources (FHIR) format to maximize interoperability. The OSIRIS set was reviewed, approved by a National Plan Strategic Committee, and freely released to the community. A proof-of-concept study was carried out to put the OSIRIS set and Common Data Model into practice using a cohort of 300 patients. CONCLUSION: Using a national and bottom-up approach, the OSIRIS group has defined a model including a minimal set of clinical and genomic data that can be used to accelerate data sharing produced in oncology. The model relies on clear and formally defined terminologies and, as such, may also benefit the larger international community.

Episomal HPV16 responsible for aggressive and deadly metastatic anal squamous cell carcinoma evidenced in peripheral blood.

Archival tissue samples collected longitudinally from a patient who died from HPV16-induced high-grade anal intraepithelial squamous cell carcinoma with vertebral HPV16-positive metastasis were retrospectively analyzed by the Capture-HPV method (Capt-HPV) followed by Next-Generation Sequencing (NGS). Full length nucleotide sequences of the same HPV16 were identified from the initial and second anal biopsy samples, from plasma sample and from vertebral metastasis biopsy. Remarkably, HPV was episomal in each sample. The HPV genome sequence was closest to the HPV16 Qv18158E variant subtype (A1 lineage) exhibiting base substitutions and deletions in 7 and 2 HPV loci, respectively. In conclusion, the powerful Capt-HPV followed by NGS allows evidencing the detailed cartography of tumoral and circulating HPV DNA, giving rise to a unique and unexpected episomal virus molecular status in a context of aggressive carcinoma, underlying the importance of HPV status and its association with clinical features for further prospective studies.

Impact of obesity on surgical and oncologic outcomes in patients with endometrial cancer treated with a robotic approach.

AIM: The surgical treatment of endometrial cancer (EC) can be more complicated in obese patients. Robotic surgery could simplify the surgical approach in these patients. The aim of our study was to compare the outcomes of robotic surgery in obese (body mass index ≥30 kg/m2 ) and nonobese patients. METHODS: We performed a retrospective study on patients with EC benefitting from a robotic approach in our institution. The primary outcome was the 5-year overall survival (OS). We also assessed the 5-year recurrence-free survival (RFS), type of surgery, laparotomy conversion rate, adjuvant treatment and postoperative morbidity. RESULTS: We analyzed 175 consecutive patients with EC who underwent robotic surgery, 42 patients with obesity and 133 patients without. The median follow-up length was 37 months [1-120]. The OS rate was 97% in the whole population and the RFS was 74%. Obesity did not impact prognosis. Laparotomy conversion rate was low in both groups (5% in patients with obesity vs 3%, P = 0.619). There were no significant differences in terms of postoperative complications (5 vs 9%, P = 0.738). There were significantly less pelvic lymphadenectomies in patients with obesity (5 vs 12%, P = 0.005). In the subgroup of patients with high-risk EC, rate of lymphadenectomy and of adjuvant treatments did not differ between patients with or without obesity. CONCLUSION: Obese patients with EC can be safely treated with a robotic approach, with a low complication rate and similar oncological outcomes compared to nonobese patients.

Contributions from the 2019 Literature on Bioinformatics and Translational Informatics.

OBJECTIVES: Summarize recent research and select the best papers published in 2019 in the field of Bioinformatics and Translational Informatics (BTI) for the corresponding section of the International Medical Informatics Association Yearbook. METHODS: A literature review was performed for retrieving from PubMed papers indexed with keywords and free terms related to BTI. Independent review allowed the section editors to select a list of 15 candidate best papers which were subsequently peer-reviewed. A final consensus meeting gathering the whole Yearbook editorial committee was organized to finally decide on the selection of the best papers. RESULTS: Among the 931 retrieved papers covering the various subareas of BTI, the review process selected four best papers. The first paper presents a logical modeling of cancer pathways. Using their tools, the authors are able to identify two known behaviours of tumors. The second paper describes a deep-learning approach to predicting resistance to antibiotics in Mycobacterium tuberculosis. The authors of the third paper introduce a Genomic Global Positioning System (GPS) enabling comparison of genomic data with other individuals or genomics databases while preserving privacy. The fourth paper presents a multi-omics and temporal sequence-based approach to provide a better understanding of the sequence of events leading to Alzheimer's Disease. CONCLUSIONS: Thanks to the normalization of open data and open science practices, research in BTI continues to develop and mature. Noteworthy achievements are sophisticated applications of leading edge machine-learning methods dedicated to personalized medicine.

Identification of TP53 mutated group using a molecular and immunohistochemical classification of endometrial carcinoma to improve prognostic evaluation for adjuvant treatments.

INTRODUCTION: Molecular classification of endometrial carcinoma has been proposed to predict survival. However, its role in patient management remains to be determined. We aimed to identify whether a molecular and immunohistochemical classification of endometrial carcinoma could improve decision-making for adjuvant therapy. METHODS: All consecutive patients treated for endometrial carcinoma between 2010 and 2017 at Cochin University Hospital were included. Clinical risk of relapse was based on European Society for Medical Oncology-European Society of Gynaecological Oncology-European SocieTy for Radiotherapy & Oncology (ESMO-ESGO-ESTRO) consensus. The clinical event of interest was event-free survival. Formalin-fixed paraffin-embedded tissue samples were processed for histopathological analysis and DNA extraction. The nuclear expression of mismatch repair and TP53 proteins was analyzed by immunohistochemistry. Next-generation sequencing of a panel of 15 genes including TP53 and POLE was performed using Ampliseq panels on Ion Torrent PGM (ThermoFisher). Tumors were allocated into four molecular groups using a sequential method based on next-generation sequencing and immunohistochemistry data: (1) POLE/ultramutated-like; (2) MSI/hypermutated-like (mismatch repair-deficient); (3) TP53-mutated (without POLE mutations or mismatch repair deficiency); (4) not otherwise specified (the remaining tumors). RESULTS: 159 patients were included; 125 tumors were available for molecular characterization and distributed as follows: (1) POLE/ultramutated-like: n=4 (3%); (2) MSI/hypermutated-like: n=35 (30%); (3) TP53-mutated: n=30 (25%); and (4) not otherwise specified: n=49 (42%). Assessing the TP53 status by immunohistochemistry only rather than next-generation sequencing would have misclassified 6 tumors (5%). TP53-mutated tumors were associated with poor prognosis, independently of International Federation of Gynecology and Obstetrics (FIGO) stage and histological grade (Cox-based adjusted hazard ratio (aHR) 5.54, 95% CI 2.30 to 13.4), and independently of clinical risk of relapse (aHR 3.92, 95% CI 1.59 to 9.64). Among patients with FIGO stage I-II tumors, 6 (38%) TP53-mutated tumors had low/intermediate clinical risk of relapse and did not receive adjuvant chemotherapy or radiotherapy. CONCLUSION: Endometrial carcinoma molecular classification identified potentially under-treated patients with poor molecular prognosis despite being at low/intermediate clinical risk of relapse. Consideration of molecular classification in adjuvant therapeutic decisions should be evaluated in prospective trials.

HPV circulating tumoral DNA quantification by droplet-based digital PCR: A promising predictive and prognostic biomarker for HPV-associated oropharyngeal cancers.

We aimed to determine whether pretherapeutic assessment of HPV circulating tumoral DNA (HPV ctDNA) by droplet-based digital PCR (ddPCR) could constitute a predictive and prognostic biomarker for HPV-associated oropharyngeal squamous cell carcinoma (OPSCC). A mono-institutional prospective biomarker study on 66 patients with p16+/HPV16-positive oropharyngeal squamous cell carcinoma (OPSCC) was conducted in European Georges Pompidou Hospital, Paris, France. Blood samples were collected at the time of diagnosis before any treatment. Optimized digital PCR assays were used to quantify HPV16 ctDNA. Forty-seven (71%) patients showed a positive pretherapeutic HPV ctDNA at time of diagnosis. Interestingly, the quantity of HPV16 ctDNA at baseline, as assessed by ddPCR, was significantly correlated with the T/N/M status or OPSCC stages according to the 2018 new staging criteria for high-risk human papillomavirus (HR HPV) related OPSCC from American Joint Committee on Cancer (AJCC). Moreover, all recurrences and the majority (83%) of death reported events occurred in patients with positive HPV16 ctDNA at baseline. Finally, when posttreatment blood samples were available (n = 6), the kinetic of pretreatment/posttreatment HPV16 ctDNA was clearly associated with treatment success or failure. HPV ctDNA monitoring by ddPCR could constitute a useful and noninvasive dynamic biomarker to select HR HPV-related OPSCC patients eligible for potential treatment de-escalation and to monitor treatment response.

Contributions from the 2018 Literature on Bioinformatics and Translational Informatics.

OBJECTIVES: To summarize recent research and select the best papers published in 2018 in the field of Bioinformatics and Translational Informatics (BTI) for the corresponding section of the International Medical Informatics Association (IMIA) Yearbook. METHODS: A literature review was performed for retrieving from PubMed papers indexed with keywords and free terms related to BTI. Independent review allowed the two section editors to select a list of 14 candidate best papers which were subsequently peer-reviewed. A final consensus meeting gathering the whole IMIA Yearbook editorial committee was organized to finally decide on the selection of the best papers. RESULTS: Among the 636 retrieved papers published in 2018 in the various subareas of BTI, the review process selected four best papers. The first paper presents a computational method to identify molecular markers for targeted treatment of acute myeloid leukemia using multi-omics data (genome-wide gene expression profiles) and in vitro sensitivity to 160 chemotherapy drugs. The second paper describes a deep neural network approach to predict the survival of patients suffering from glioma on the basis of digitalised pathology images and genomics biomarkers. The authors of the third paper adopt a pan-cancer approach to take benefit of multi-omics data for drug repurposing. The fourth paper presents a graph-based semi-supervised method to accurate phenotype classification applied to ovarian cancer. CONCLUSIONS: Thanks to the normalization of open data and open science practices, research in BTI continues to develop and mature. Noteworthy achievements are sophisticated applications of leading edge machine-learning methods dedicated to personalized medicine.

Prognostic impact of initial tumor load and intraperitoneal disease dissemination patterns in patients with advanced ovarian cancer undergoing complete cytoreductive surgery.

INTRODUCTION: Complete removal of disease is the most important prognostic factor for patients with advanced epithelial ovarian carcinoma. However, the influence of carcinomatosis distribution on prognosis is unknown and the prognostic impact of implant size according to their location is poorly studied. Our objective was to assess the impact of peritoneal carcinomatosis quantitative and qualitative localizations on progression free survival (PFS) in patients with advanced epithelial ovarian carcinoma (AEOC) after complete cytoreductive surgery. METHODS: We conducted a monocentric cohort study, retrospective from October 2001 to July 2014. Inclusion criteria were high-grade AEOC patients without residual disease (CC0) after primary debulking surgery (PDS) or after interval debulking surgery (IDS) following neoadjuvant chemotherapy (NACT). Peritoneal carcinomatosis was assessed according to qualitative criteria and quantitative criteria. RESULTS: One hundred and one patients were included. Median PFS was 21·2 months and median OS was 62·2 months. On the whole population, involvement of adipocytes-enriched areas tended to be associated with a decreased PFS and was significantly associated with a decreased OS. Any localization was associated with PFS or OS in the "IDS" subgroup. In the "PDS" subgroup, PCI score and involvement of the right mesocolic area were associated with a decreased PFS. CONCLUSION: Initial tumor load has not been found associated with PFS after complete surgery. Adipocytes-enriched areas and right mesocolic areas involvement were associated with poor prognosis in patients receiving primary debulking surgery. Larger-scale studies are needed to assess whether initial tumor load has a prognostic impact even after complete cytoreductive surgery is achieved.

The NRF2 transcriptional target NQO1 has low mRNA levels in TP53-mutated endometrial carcinomas.

BACKGROUND: NRF2 is a major transcription factor regulating the expression of antioxidative/detoxifying enzymes, involved in oncogenic processes and drug resistance. We aimed to identify molecular alterations associated with NRF2 activation in endometrial carcinoma (EC). METHODS: Ninety patients treated (2012-2017) for localized/locally advanced EC were included in this study. Formalin-fixed paraffin-embedded tissue samples were processed for immunohistochemical (NRF2 and Mismatch Repair proteins) analyses. Next generation sequencing (NGS) of a panel of genes including POLE, TP53, NFE2L2, KEAP1 and CUL3 was performed using Ampliseq panels on Ion Torrent PGM (ThermoFisher). NRF2 activity was assessed by NQO1, GCLC, and AKR1C3 mRNA expressions, using TaqMan assays and quantitative RT-PCR. RESULTS: Tumors were classified as POLE exonuclease domain mutated (N = 3, 3%), MMR-deficient (MSI-like) (N = 28, 31%), TP53 mutated (Copy-number high-like) (N = 22, 24%), and other tumors (Copy-number low-like) (N = 32, 36%). NRF2 nuclear immunostaining did not correlate with NRF2 target genes expression. The 3 tumors with highest NRF2 target genes expression harbored oncogenic KEAP1 or NFE2L2 mutations. Low NQO1 mRNA and protein levels were observed in the TP53 mutated subgroup compared to others tumors (p < .05) and in silico analyses of The Cancer Genome Atlas data further indicated that NQO1 mRNA levels were lower in serous compared to endometrioid copy-number high EC. CONCLUSION: In contrast with previous reports based on immunohistochemistry, our study indicates that NRF2 activation is a rare event in EC, associated with NFE2L2 or KEAP1 mutations. The subset of aggressive EC with low NQO1 mRNA level might represent a specific subgroup, which could be sensitive to combination therapies targeting oxidative stress.