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• NEOPREDICT-Lung: Neoadjuvant Immunotherapy for Resectable NSCLC

  Links via: DOI: https://doi.org/10.1038/s41591-024-02965-0 PubMed: https://pubmed.ncbi.nlm.nih.gov/38689060/ Journal: https://www.nature.com/articles/s41591-024-02965-0 Abstract Antibodies targeting the immune checkpoint molecules PD-1, PD-L1 and CTLA-4 administered alone or in combination with chemotherapy are standard of care in most patients with metastatic non-small cell lung cancers. When given prior to curative surgery, tumor responses and improved event-free survival are achieved. New antibody combinations may be more efficacious and tolerable. In an ongoing, open-label phase II study, 60 biomarker-unselected, treatment-naïve patients with resectable non-small cell lung cancer were randomized to receive two preoperative doses of nivolumab (anti-PD-1) with or without relatlimab (anti-LAG-3) antibody therapy. The primary study endpoint was feasibility of surgery within 43 days, which was met by all patients. Curative resection was achieved in 95% of patients. Secondary endpoints included pathological and radiographic response rates, pathologically complete resection rates, disease-free and overall survival rates, and safety. Major pathological (≤10% viable tumor cells) and objective radiographic responses were achieved in 27% and 10% (nivolumab), and 30% and 27% (nivolumab and relatlimab) of patients, respectively. In 100% (nivolumab) and 90% (nivolumab and relatlimab) of patients tumors and lymph nodes were pathologically completely resected. With 12 months median duration of follow-up, disease-free survival and overall survival rates at 12 months were 89% and 93% (nivolumab), and 93% and 100% (nivolumab and relatlimab). Both treatments were safe with grade ≥ 3 treatment-emergent adverse events reported in 10% and 13% of patients per study arm. Exploratory analyses provided insights into biological processes triggered by preoperative immunotherapy. This study establishes the feasibility and safety of dual targeting of PD-1 and LAG-3 prior to lung cancer surgery.

  Study EGAS00001007753

• Intra-tumor heterogeneity of localized lung adenocarcinomas defined by multi-region sequencing

  Background: Intra-tumor heterogeneity (ITH) may have profound impacts on biopsy strategy, characterization of actionable targets, treatment planning, and drug resistance. ITH of lung cancers has not been well studied. Methods: We performed multi-region whole exome sequencing (average sequencing depth 277x) on 48 tumor regions from 11 resected lung adenocarcinomas (8 stage I, 2 stage II and one stage III tumors) followed by deep sequencing validation (average sequencing depth 863x). Results: All tumors showed clear evidence of spatial ITH. On average, 76% of all mutations and 20/21 known cancer gene mutations were present in all regions of individual tumors (trunk mutations). Copy number analysis did not show substantial difference in large-scale chromosome aberrations. A canonical KRAS p.G12C mutation was detected in only 1 of 4 tumor regions (branch mutations) at exome depth but detected in all four tumor regions (trunk mutations) at increased sequencing depth. In addition, many heterogeneous branch mutations defined by exome sequencing were detectable in all regions of individual tumors with increasing sequencing depth. Significant differences in mutational spectrum were observed in 6 tumors indicating that specific mutational processes were likely operative at different times during development of these tumors. With a median follow up of 21 months post surgery, 3 patients have relapsed and all 3 patients presented with significantly larger fractions of subclonal mutations in their primary tumors. Conclusions: Although multi-region sampling is still required to fully assess ITH complexity, single biopsy analysis at appropriate depth might be sufficient to identify the majority of known cancer gene mutations in localized lung adenocarcinomas. Larger subclonal mutation fractions may be associated with increased likelihood of postsurgical relapse in patients with localized lung adenocarcinomas. Studies on larger cohort, ideally with comprehensive clinical annotation and repeat biopsy at relapse are needed to fully understand the clinical impact of ITH.

  Study EGAS00001000930

• Multiple Myeloma Total Therapy trial patient sequencing

  The study of multiple myeloma (MM) genomics has identified many abnormalities that are associated with poor progression free survival (PFS) and overall survival (OS). Copy number abnormalities have been extensively studied in many datasets with long follow-up, however, the prognostic impact of mutations have not been extensively studied and available datasets have generally had a relatively short follow-up. These analyses have identified a range of mutations that are associated with prognosis, making it important to extend these observations in larger studies with robust diagnostic technologies. Samples from newly diagnosed MM patients enrolled in Total Therapy trials (n=225) were sequenced on a targeted panel consisting of 140 genes and additional regions of interest for copy number, as well as tiling of the Ig and MYC loci for detection of translocations. Samples were sequenced to a median depth of 452x using 2x75 bp paired end reads. Reads were aligned to hg19 and mutations called using Strelka and filtered with fpfilter. Translocations were called by Manta, and copy number determined by read depth ratio and loss of heterozygosity comparison with a patient matched non-tumor sample. DNA was obtained from either CD138+ cells from the bone marrow of multiple myeloma patients (tumor) or from stem cell harvests or peripheral blood cells from the same patient (control). 100 ng of DNA was fragmented, end-repaired, and adapters ligated using the HyperPlus kit (KAPA Biosystems). After PCR amplification the libraries were hybridized with probes against either a targeted panel consisting of 140 genes and chromosomal regions (Nimblegen) using SeqCap reagents (Nimblegen). Hybridized libraries underwent further amplification before being sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads There are 450 (225 tumor and 225 germline) samples in this study. 263 are available as part of this dataset. The remaining 187 are available with dataset accession id EGAD00001004117.

  Study EGAS00001003223

• Molecular features of adenomas predicting metachronous colorectal cancer: a nested-case control study

  "Background & Aims: Current morphological features defining advanced adenomas (size ≥10 mm, high grade dysplasia or >25% villous component) cannot optimally distinguish individuals at high-risk or low-risk of metachronous colorectal cancer (me-CRC), which may result in suboptimal surveillance. Certain DNA copy number alterations are associated with adenoma-to-carcinoma progression (cancer-associated events; CAEs). We aimed to evaluate whether CAEs can better predict an individual’s risk of me-CRC than the morphological advanced adenoma features. Methods: In this nested case-control study, 529 individuals with a single adenoma at their first colonoscopy were selected from a Norwegian adenoma cohort. DNA copy number profiles were determined, by means of low-coverage whole genome sequencing. We assessed the prevalence of CAEs in advanced and non-advanced adenomas and its association with me-CRC. For the latter, cases (with CRC) were matched to controls (without CRC), with the same follow-up period as cases, as well as age and sex. Subsequently, odds ratios (OR) for the association of the presence of an advanced adenoma or a molecularly-defined high-risk adenoma with me-CRC were calculated. Results: Molecular high-risk features were observed in 85/267 (32%) of advanced adenomas and in 27/262 (10%) of non-advanced adenomas. Me-CRC was more strongly associated with advanced adenomas (OR 3.58; 95% CI 2.27-5.72) than with molecular high-risk adenomas (OR 1.90; 95% CI 1.14–3.16). After adjusting for other variables, only advanced adenoma remained significantly associated with me-CRC (OR 3.39; 95% CI 2.10–5.55). Conclusion: Molecularly-defined high-risk adenomas were associated with me-CRC, but the association of advanced adenoma with me-CRC was stronger. " Project goal: Evaluate the value of DNA copy numbers alterations detected in a baseline adenoma, in the prediction of risk of metachronous CRC

  Study EGAS00001007039

• ImmunAID

  The ImmunAID study is a multi-center research program aimed at improving the diagnosis and understanding of systemic autoinflammatory diseases. The study integrates immunological, and molecular data from patients across several European cohorts. Its objective is to identify biomarkers and biological pathways that characterize disease mechanisms and help differentiate between inflammatory conditions. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779295. The project has generated genomic datasets, which are available through the European Genome-phenome Archive (EGA). In addition, it has produced several non-genomic datasets, listed below. All datasets have been fully anonymized in accordance with applicable ethical and regulatory frameworks. These non-genomic data are available upon request. To request access to these datasets, please contact: immunaid2024@gmail.com Your request will be studied by the Data Access Committee, and data will be made available upon approval. Non-genomic datasets available: Flow cytometry (general immune phenotype) — Dataset ID: ICKD2021569, size: 23 GB, 342 patients Somascan proteomics data — Dataset ID: ICKD2021570, size: 59 MB, 444 patients ELISA panel (Ferritin, CRP, HO1, IL-1B, IL-6, IL-8, IL-10, IL-12, IL-18, IFN-γ, TNF-α) — Dataset ID: ICKD2021571, size: 295 KB, 439 patients Mass spectrometry (MS/MS) — Dataset ID: ICKD2021572, size: 1.8 TB, 447 patients ELISA (CRP/ SAA) — Dataset ID: ICKD2021573, size: 321 KB, 443 patients Flow cytometry (inflammasome activity) — Dataset ID: ICKD2021574, size: 899 KB, 307 patients Plasma lipidomics — Dataset ID: ICKD2021575, size: 1.1 MB, 427 patients Urine lipidomics — Dataset ID: ICKD2021576, size: 833 KB, 368 patients ELISA (alarmins) — Dataset ID: ICKD2021577, size: 129 KB, 108 patients ELISA (IL-18 / IL-1) — Dataset ID: ICKD2021578, size: 271 KB, 330 patients Flow cytometry (NK cell alterations) — Dataset ID: ICKD2021579, size: 14 GB, 216 patients Chemokine measurements — Dataset ID: ICKD2021580, size: 489 KB, 404 patients Luminex (multiple analyte measurements) — Dataset ID: ICKD2021581, size: 759 KB, 369 patients

  Study EGAS50000001393

• DAC for EGA study: "ctDNA residual disease analyses during perioperative nivolumab or nivolumab plus ipilimumab in resectable diffuse pleural mesothelioma"

  This DAC regulates access to the whole-exome sequence data for the study "ctDNA residual disease analyses during perioperative nivolumab or nivolumab plus ipilimumab in resectable diffuse pleural mesothelioma".

  Dac EGAC50000000706

• DAC: LUMC NeuroD AON off target analysis

  In this study, we used three different splice-switching AONs targeting three different human transcripts to study their transcriptome-wide, hybridization-dependent off-target effects with short read RNAseq. Using the computational tools rMATS and Whippet, in control human induced pluripotent stem cells

  Dac EGAC50000000726

• Refractory Classic Hodgkins Lymphoma (cHL) sWGS

  Associated with the study: Blood-based Monitoring of Relapsed/Refractory Hodgkin Lymphoma Patients Predict Responses to Anti-PD-1 Treatment. 26 ctDNA Samples from 4 patients followed longitudinally. sWGS performed for copy number aberration (CNA) analysis.

  Dataset EGAD50000001163

• ATAC-seq in LCLs derived from constitutional MLH1 epimutation carriers and non-carrier relatives

  ATAC-seq performed in LCLs derived from constitutional MLH1 epimutation carriers and non-carrier relatives to profile alterations in chromatin accessibility associated with constitutional MLH1 epimutation.

  Dataset EGAD50000000714

• scRNA-seq of bulk and sorted NK

  Here we performed single-cell RNA sequencing to characterize NK cell subsets. Sorted NK cell subsets representing discrete stages of NK cell differentiation as well as bulk NK cells were sequenced.

  Dataset EGAD50000000020