Background: Pancreatic ductal adenocarcinoma (PDAC) has a high incidence of perineural invasion (PNI), a pathological feature of the cancer invasion of nerves. PNI is associated with a poor prognosis, local recurrence and cancer pain. It has been suggested that interactions between nerves and the tumor microenvironment (TME) play a role in PDAC tumorigenesis. Methods: Here, we used Nanostring GeoMx Digital Spatial Profiler to analyze the whole transcriptome of both cancer and nerve cells in the microenvironment of PNI and non-PNI foci from 13 PDAC patients. Conclusions: We identified previously reported pathways involved in PNI, including Axonal Guidance and ROBO-SLIT Signaling. Spatial transcriptomics highlighted the role of PNI foci in influencing the immune landscape of the TME and similarities between PNI and nerve injury response. This study revealed that endocannabinoid and polyamine metabolism may contribute to PNI, cancer growth and cancer pain. Key members of these pathways can be targeted, offering potential novel research avenues for exploring new cancer treatment and/or pain management options in PDAC.

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is often the only source of tumor tissue from patients with advanced, inoperable lung cancer. EBUS-TBNA aspirates are used for the diagnosis, staging, and genomic testing to inform therapy options. Here we extracted DNA and RNA from 220 EBUS-TBNA aspirates to evaluate their suitability for whole genome (WGS), whole exome (WES), and comprehensive panel sequencing. For a subset of 40 cases, the same nucleic acid extraction was sequenced using WGS, WES, and the TruSight Oncology 500 assay. Genomic features were compared between sequencing platforms and compared with those reported by clinical testing. A total of 204 aspirates (92.7%) had sufficient DNA (100 ng) for comprehensive panel sequencing, and 109 aspirates (49.5%) had sufficient material for WGS. Comprehensive sequencing platforms detected all seven clinically reported tier 1 actionable mutations, an additional three (7%) tier 1 mutations, six (15%) tier 2–3 mutations, and biomarkers of potential immunotherapy benefit (tumor mutation burden and microsatellite instability). As expected, WGS was more suited for the detection and discovery of emerging novel biomarkers of treatment response. WGS could be performed in half of all EBUS-TBNA aspirates, which points to the enormous potential of EBUS-TBNA as source material for large, well-curated discovery-based studies for novel and more effective predictors of treatment response. Comprehensive panel sequencing is possible in the vast majority of fresh EBUS-TBNA aspirates and enhances the detection of actionable mutations over current clinical testing.

Pancreatic Ductal Adenocarcinoma (PDAC) has a high incidence of perineural invasion (PNI), a pathological feature of cancer invasion of nerves. PNI is associated with poor prognosis, metastasis, local recurrence and cancer pain. It has been suggested that interactions between nerves and the tumour microenvironment (TME) play a role in the PDAC tumorigenesis, however our ability to study these interactions in patient samples has been technologically limited. Here we used Nanostring GeoMx Digital Spatial Profiler to analyze the whole transcriptome of the cancer and nerve compartments in PNI and non-PNI foci from 13 PDAC patients. We identified previously reported pathways involved in PNI, including Axonal Guidance, ROBO-SLIT Signaling supporting the study approach. Spatial transcriptomics highlighted the potential role of nerve and cancer cells in PNI foci in influencing the immune landscape of the TME and suggested similarities between PNI and nerve injury-response. This study revealed novel pathways, Endocannabinoid and Polyamine metabolism, which may contribute to PNI and cancer pain. These findings require additional in vitro and/or in vivo investigations to dissect the mechanism that Endocannabinoids and Polyamines may play in PNI and cancer growth. These pathways can be targeted providing a potential novel approach to treat PDAC.

Introduction: Chronic lymphocytic leukemia (CLL) is the most common hematological malignancy and remains incurable. IGHV mutational status is an independent predictor of outcome with chemoimmunotherapy, however the mechanism(s) underpinning the superior prognosis of M-CLL are still to be elucidated. Clonal T cell expansions are well described in CLL. Neoantigens are immunogenic peptides unique to malignant cells, which are presented to host T cells via HLA-I/II, and if harnessed may have potential as a novel immunotherapeutic strategy. It is believed CLL has a low tumor mutational burden (TMB) due to few somatic mutations (~1/Mb) and hence few somatic neoantigens. However, traditional concepts of TMB fail to recognize that the IGH and IGκ/λ chains of the B cell receptor (BCR) also become highly mutated during B cell maturation. BCR mutations in B cell malignancies can create ‘BCR neoantigens’ (Khodadoust, Nature 2017 / Blood 2019). There is no large-scale analysis of HLA-I/II somatic and BCR neoantigens in CLL. Methods: Pre-therapy PBMCs from 23 patients with CLL (M17:F6, median 69 yrs, M-CLL=10, U-CLL=13) were tested. Cytogenetics and patient characteristics were similar between M-CLL and U-CLL. Samples underwent paired WES and RNAseq. Somatic mutations were called by Strelka2 and somatic neoantigens by pVACseq (TESLA guidelines; Wells, Cell 2020). BCR neoantigens were called from full-length BCR sequences by pVACbind. Neoantigen transcriptome expression was confirmed in all cases. Results: Importantly, expression of genes important for CLL antigen presentation was almost universally preserved. Furthermore, consistent with T cells controlling disease progression, central memory/effector T cells were expanded in both M-CLL and U-CLL by CIBERSORTx. Next, the somatic mutational landscape was characterized. WES revealed a median 1.06 somatic mutations/Mb, with frequency of driver mutations as expected (Knisbacher, Nature 2022). Only a median 22% of mutations/case were expressed, with expression of driver mutations only modestly increased in U-CLL vs M-CLL (1 vs 0, p=0.024), suggesting that enrichment of driver mutations in U-CLL only partially explains its inferior prognosis. Strikingly, unlike somatic mutations, all BCR mutations were expressed, with 12x > BCR mutations expressed in M-CLL vs U-CLL (37 vs 3, p<0.0001). Furthermore, in M-CLL expressed BCR mutations were 3x > somatic mutations, whereas BCR mutations were 3x < somatic mutations in U-CLL. Neoantigens were then assessed (Figure 1). Combining somatic + BCR neoantigens, there were a median 24 neoantigens/case. Somatic neoantigens included those found in driver mutations (ATM, XPO1, SF3B1, TP53, NOTCH1). Expression of driver neoantigens were retained in sequential patient samples and new driver neoantigens also acquired. Importantly, public neoantigens (i.e., neoantigens shared across CLL patients) in TP53 and XPO1 were detected. Notably, the frequency of BCR neoantigens was higher than somatic neoantigens, with differences most marked and enriched for HLA-II (HLA-I: 5 vs 2, p<0.0001 and HLA-II: 17 vs 3, p<0.0001). Strikingly, there were 2x > BCR neoantigens in M-CLL vs U-CLL (HLA-I: 6 vs 2, p<0.001; HLA-II: 23 vs 15, p=0.032). Interestingly, the nature of BCR neoantigens between M-CLL and U-CLL was different. Consistent with M-CLL B cells undergoing somatic hypermutation, IGHV mutations strongly positively correlated with numbers of V region BCR neoantigens (R 2=0.784, p<0.0001), and weakly negatively correlated with V(D)J recombination region BCR neoantigens (R 2=0.3992, p<0.005). As expected, there was no correlation between the number of IGHV mutations and somatic neoantigens. Conclusions: The reported low TMB in CLL does not reflect the true frequency of neoantigens, as it fails to account for BCR neoantigens. These contribute ~80% of the neoantigen pool and are predominantly presented by HLA-II. The majority of BCR neoantigens in M-CLL are within the V region, whereas in U-CLL, BCR neoantigens are largely restricted to the V(D)J recombination site. The known enrichment of driver mutations in U-CLL coupled with the increase of BCR neoantigens in M-CLL, are the likely mechanisms behind the different survival outcomes between M-CLL and U-CLL. The presence of public neoantigens in driver mutations opens up the possibility of off-the-shelf neoantigen specific immunotherapy and warrants further investigation.

Introduction: The TROG99.03 represents the only randomised phase III trial of combined modality therapy (CMT) in limited-stage follicular lymphoma ‘LSFL’, reporting a prolonged progression-free survival (PFS) in the CMT arm (MacManus, JCO, 2018). Here, we report extended follow up of this study providing mature data of patients treated with a rituximab-containing CMT regimen and the development of a new gene-expression based prognostic score. Methods: Patients with LSFL, grade 1–3a were randomised (1:1) to either involved-field radiotherapy alone (IFRT) (30–36Gy) or to CMT consisting of identical IFRT followed by 6 cycles of CVP. Reflecting evolving clinical practice, from 2006 onwards (i.e., ‘modern-era’), PET staging was increasingly utilised, and rituximab added to the CMT arm. Digital multiplex gene expression by Nanostring was performed on diagnostic biopsies based on genes previously identified to differentiate LSFL from advanced stage FL ‘ASFL’ (AM Staiger, Blood, 2020). Results: 150 patients were recruited between 2000 and 2012 with 31/75 patients in each arm recruited in the ‘modern-era’. At median follow-up 11.3 years, PFS remained superior for CMT compared to RT (HR 0.6; p = 0.043). Although no significant difference in OS was observed (HR 0.45, p = 0.11), compared with IFRT, patients in the CMT arm experienced fewer composite (deaths and histological transformation ‘HT’) events (HR 0.25; p = 0.045). With additional follow up no new non-malignant late toxicities were observed and incidence of secondary malignancies were similar between both arms (11 IFRT vs. 10 CMT, p = 0.99). Patients treated with a rituximab regimen (i.e., IFRT+R-CVP) had a markedly superior PFS compared to those treated without rituximab (i.e., IFRT, or IFRT+CVP), 8 year PFS rates 81% versus 52%, HR 0.42 p = 0.013 (Figure 1). Amongst PET staged patients the difference between R-CVP/IFRT versus IFRT increased (HR 0.35 p =0.027) suggesting this effect was not due to stage migration. No clinical factors were significantly associated with PFS on multivariate analysis. Nor were prognostic associations found for expression level of any individual genes. However, by penalised Cox regression an 8-gene Lasso-weighted prognosticator was identified, termed the ‘Bio-LSFL-score’. Genes (CACNA2D2, CD69, GZMB, IL7R, MYCT1, SLP1, TNFRSF14, TNFRSF25) reflected both B-cells and the microenvironment. The Bio-LSFL-score was highly significant for PFS (HR 0.25, p < 0.0001) with 100% patients in the high-risk group relapsing before 8 years. Conclusions: Particularly when incorporating rituximab, LSFL patients demonstrated significant increases in PFS and reduction in the rates of death and/or HT when treated with CMT compared with IFRT alone. A novel gene expression prognosticator was identified which in this trial cohort showed ‘ASFL-like’ behaviour by identifying LSFL patients unlikely to experience durable remissions. Keywords: diagnostic and prognostic biomarkers, indolent non-Hodgkin lymphoma, radiation therapy Conflicts of interests pertinent to the abstract C. Cheah Consultant or advisory role: Roche, Janssen, Gilead, Astra Zeneca, Lilly, TG Therapeutics, Beigene, Novartis, Menarini, Daizai, Abbvie, Genmab, BMS Research funding: BMS, Roche, Abbvie, MSD, Lilly J. F. Seymour Consultant or advisory role: Abbvie, Astra Zeneca, Celgene/BMS, Genentech, Genor Bio, Gilead, Janssen, Morphosys, Roche, Sunesis, TG Therapeutics Research funding: Celgene/BMS M. K. Gandhi Research funding: Beigene, Janssen

Supplementary Figure S1. Representative hematoxylin and eosin stained sections from sequenced LGSC; Supplementary Figure S2. Age distribution analysis of patients from the Australian Ovarian Cancer Study. Includes patients with advanced stage, serous epithelial ovarian cancer (n = 684); Supplementary Figure S3. RAS pathway mutations in LGSC; Supplementary Figure S4. Verification of EIF1AX mutations; Supplementary Figure S5. Characterization of the AOCS2 cell line; Supplementary Figure S6. Functional effect of EIF1AX mutations and gene suppression in a LGSC cell line; Supplementary Figure S7. (a) EIF1AX and NRAS function in the mTOR and RAS/ERK signaling pathways to regulate protein translation, cell proliferation and cell survival

Supplemental Material - Group Authorship from EIF1AX and NRAS Mutations Co-occur and Cooperate in Low-Grade Serous Ovarian Carcinomas

Introduction: Follicular lymphoma (FL) is the most common indolent NHL. Recently, we demonstrated in limited and advanced stage FL (LSFL, ASFL), that patients with longer remissions had raised clonally expanded intratumoral CD8+ T cells (Tobin, JCO 2019). Durable remissions occur in ∼50% of LSFL patients whereas ASFL is incurable. However, little is known regarding the immunological features associated with this difference. We hypothesized HLA-I neoantigen (neoAg)-specific CD8+ T cells may play a role. Methods: The discovery cohort comprised 101 patients with diagnostic paraffin embedded tissue from the TROG99.03 LSFL clinical trial (MacManus, JCO 2018), in which stage I/II patients were randomized to involved field radiation (IFRT) only or combined modality therapy between 2000 and 2012 (PET from 2006). Contemporaneous validation cohorts were (a) AusLSFL: 60 PET staged, stage I FL patients from Australia (treatment miscellaneous), and (b) CanLSFL: 60 PET staged, stage I FL patients drawn principally from Canada (IFRT only). Digital gene expression (NanoString), targeted sequencing (330 genes), and germline HLA-typing was performed. Mutations observed by sequencing were used to predict neoAgs in TROG99.03 tissues using 8 algorithms (PVACseq) and filtered according to strong binding affinity to HLA-I over wild-type (TESLA consortium guidelines; Wells, Cell 2020). Results: CD8A gene expression was tested for prognostic significance. In TROG99.03, elevated intratumoral CD8A (by MaxStat) was associated with ∼2-fold improvement in PFS for all patients: HR 0.45 (CI: 0.77–0.26, p = 0.0053) and stage I only patients: HR 2.4 (CI: 1.2–4.6, p = 0.036). In keeping with a relationship between CD8+ T cell infiltration and tumor antigen presentation, raised expression of NLRC5 (a transcriptional HLA-I activator) was also associated with superior PFS: HR 0.48 (CI: 0.99–0.24, p = 0.024). CD8A significance was confirmed in both validation cohorts (whereas NLRC5 was validated in AusLSFL only). In keeping with recent IHC CD8 protein data (Los-de Vries, Bld Adv 2022), CD8A gene expression was raised in stage I LSFL vs. 68 ASFL patients treated with immunochemotherapy (p = 0.02). Mutational profiling was concordant with published LSFL data, with CREBBP and KMT2DA most frequent. NeoAg calling methods including functional assays for neoAg peptide binding were confirmed in a separate cohort of fresh FL tissues. 59% of TROG99.03 tissues had ≥1 neoantigens detected. Importantly, unsupervised hierarchical clustering showed 2-fold enrichment of samples with neoantigens among those with high vs. low HLA-I. Conclusions: Raised CD8A is associated with favorable prognosis in LSFL. Our data suggests disease control involves populations of expanded HLA-I neoAg-specific T cells. These findings have implications for novel immunotherapeutic strategies designed to increase the rate of durable remissions. The research was funded by: National Health and Medical Research Council, Australia; Leukaemia Foundation; Mater Foundation Keywords: Diagnostic and Prognostic Biomarkers, Indolent non-Hodgkin lymphoma, Microenvironment Conflicts of interests pertinent to the abstract. C. Keane Honoraria: Takeda, Roche, AZ, MSD, Beigene C. Cheah Consultant or advisory role: Roche, Janssen, Gilead, AstraZenecca, Lilly, TG therapeutics, Beigene, Novartis, Menarini, Daizai, Abbvie, Genmab. BMS Honoraria: BMS, Roche, Abbvie; MSD, Lilly R. Kridel Research funding: Abbvie Educational grants: Eisai M. K. Gandhi Research funding: Beigene, Janssen

IntroductionTumour Mutation Burden (TMB) is a potential biomarker for immune cancer therapies. Here we investigated parameters that might affect TMB using duplicate cytology smears obtained from endobronchial ultrasound transbronchial needle aspiration (EBUS TBNA)-sampled malignant lymph nodes.MethodsIndividual Diff-Quik cytology smears were prepared for each needle pass. DNA extracted from each smear underwent sequencing using large gene panel (TruSight Oncology 500 (TSO500 - Illumina)). TMB was estimated using the TSO500 Local App v. 2.0 (Illumina).ResultsTwenty patients had two or more Diff-Quik smears (total 45 smears) which passed sequencing quality control. Average smear TMB was 8.7 ± 5.0 mutations per megabase (Mb). Sixteen of the 20 patients had paired samples with minimal differences in TMB score (average difference 1.3 ± 0.85). Paired samples from 13 patients had concordant TMB (scores below or above a threshold of 10 mutations/Mb). Markedly discrepant TMB was observed in four cases, with an average difference of 11.3 ± 2.7 mutations/Mb. Factors affecting TMB calling included sample tumour content, the amount of DNA used in sequencing, and bone fide heterogeneity of node tumour between paired samples.ConclusionTMB assessment is feasible from EBUS-TBNA smears from a single needle pass. Repeated samples of a lymph node station have minimal variation in TMB in most cases. However, this novel data shows how tumour content and minor change in site of node sampling can impact TMB. Further study is needed on whether all node aspirates should be combined in 1 sample, or whether testing independent nodes using smears is needed.

Supplemental materials and methods

Figure S1. Liver ILC1s express high levels of adenosine-related molecules. Figure S2. A2AR-deficient NK cells display enhanced competitive proliferation. Figure S3. NK cell specific deletion of the A2AR provides improved proliferative capacity. Figure S4. Tumor-infiltrating leukocytes from NK cell specific A2AR deletion.

Murine models offer a valuable tool to recapitulate genetically defined subtypes of AML, and to assess the potential of compound mutations and clonal evolution during disease progression. This is of particular importance for difficult to treat leukemias such as FLT3 internal tandem duplication (ITD) positive AML. While conditional gene targeting by Cre recombinase is a powerful technology that has revolutionized biomedical research, consequences of Cre expression such as lack of fidelity, toxicity or off-target effects need to be taken into consideration. We report on a transgenic murine model of FLT3-ITD induced disease, where Cre recombinase expression alone, and in the absence of a conditional allele, gives rise to an aggressive leukemia phenotype. Here, expression of various Cre recombinases leads to polyclonal expansion of FLT3ITD/ITD progenitor cells, induction of a differentiation block and activation of Myc-dependent gene expression programs. Our report is intended to alert the scientific community of potential risks associated with using this specific mouse model and of unexpected effects of Cre expression when investigating cooperative oncogenic mutations in murine models of cancer.

Supplementary Table S1. Patient characteristics; Supplementary Table S2. Ki67 proliferation index; Supplementary Table S3. WES and WGS performance statistics; Supplementary Table S4. Amplicon sequencing primers; Supplementary Table S5. High confidence variants from exome and whole genome sequencing; Supplementary Table S6. Summary of SNVs and indels by sample; Supplementary Table S7. Significantly mutated genes (MuSiC output); Supplementary Table S8. Somatic variants in recurrently mutated genes; Supplementary Table S9. Validation cohort variants; Supplementary Table S10. TP53 variants in validation cohort; Supplementary Table S11. EIF1AX mutations reported in cancer

BACKGROUND:Cytology smears are commonly collected during endobronchial ultrasound-guided transbronchial needle aspiration (EBUS TBNA) procedures but are rarely used for molecular testing. Studies are needed to demonstrate their great potential, in particular for the prediction of malignant cell DNA content and for utility in molecular diagnostics using large gene panels.METHODS:A prospective study was performed on samples from 66 patients with malignant lymph nodes who underwent EBUS TBNA. All patients had air-dried, Diff-Quik cytology smears and formalin-fixed, paraffin-embedded cell blocks collected for cytopathology and molecular testing. One hundred eighty-five smears were evaluated by microscopy to estimate malignant cell percentage and abundance and to calculate smear size and were subjected to DNA extraction. DNA from 56 smears from 27 patients was sequenced with the TruSight Oncology 500 assay (Illumina).RESULTS:Each microscopy parameter had a significant effect on the DNA yield. An algorithm was developed that predicted a >50-ng DNA yield of a smear with an area under the curve of 0.86. Fifty DNA samples (89%) with varying malignant yields were successfully sequenced. Low-malignant-cell content (<25%) and smear area (<15%) were the main reasons for failure. All standard-of-care mutations were detected in replicate smears from individual patients, regardless of malignant cell content. Tier 1/2 mutations were discovered in two cases where standard-of-care specimens were inadequate for sequencing. Smears were scored for tumor mutation burden.CONCLUSIONS:Microscopy of Diff-Quik smears can triage samples for comprehensive panel sequencing, which highlights smears as an excellent alternative to traditional testing with cell blocks.

BACKGROUND:Malignant pleural mesothelioma (MPM) has a poor overall survival with few treatment options. Whole genome sequencing (WGS) combined with the immune features of MPM offers the prospect of identifying changes that could inform future clinical trials.METHODS:We analysed somatic mutations from 229 MPM samples, including previously published data and 58 samples that had undergone WGS within this study. This was combined with RNA-seq analysis to characterize the tumour immune environment.RESULTS:The comprehensive genome analysis identified 12 driver genes, including new candidate genes. Whole genome doubling was a frequent event that correlated with shorter survival. Mutational signature analysis revealed SBS5/40 were dominant in 93% of samples, and defects in homologous recombination repair were infrequent in our cohort. The tumour immune environment contained high M2 macrophage infiltrate linked with MMP2, MMP14, TGFB1 and CCL2 expression, representing an immune suppressive environment. The expression of TGFB1 was associated with overall survival. A small subset of samples (less than 10%) had a higher proportion of CD8 T cells and a high cytolytic score, suggesting a 'hot' immune environment independent of the somatic mutations.CONCLUSIONS:We propose accounting for genomic and immune microenvironment status may influence therapeutic planning in the future.

Motivation Changes in telomere length have been observed in cancer and can be indicative of mechanisms involved in carcinogenesis. Most methods used to estimate telomere length require laboratory analysis of DNA samples. Here, we present qmotif, a fast and easy tool that determines telomeric repeat sequences content as an estimate of telomere length directly from whole-genome sequencing.Results qmotif shows similar results to quantitative PCR, the standard method for high-throughput clinical telomere length quantification. qmotif output correlates strongly with the output of other tools for determining telomere sequence content, TelSeq and TelomereHunter, but can run in a fraction of the time-usually under a minute.Availability and implementation qmotif is implemented in Java and source code is available at https://github.com/AdamaJava/adamajava, with instructions on how to build and use the application available from https://adamajava.readthedocs.io/en/latest/.Supplementary information Supplementary data are available at Bioinformatics Advances online.

Background Researching the murine epigenome in disease models has been hampered by the lack of an appropriate and cost-effective DNA methylation array. Until recently, investigators have been limited to the relatively expensive and analysis intensive bisulphite sequencing methods. Here, we performed a comprehensive, comparative analysis between the new Mouse Methylation BeadChip (MMB) and reduced representation bisulphite sequencing (RRBS) in two murine models of colorectal carcinogenesis, providing insight into the utility to each platforms in a real world environment. Results We captured 1.47×10 6 CpGs by RRBS and 2.64×10 5 CpGs by MMB, mapping to 13,778 and 13,365 CpG islands, respectively. RRBS captured significantly more CpGs per island (median 41 for RRBS versus 2 for MMB). We found that 64.4% of intra-island CpG methylation variability can be captured by measuring approximately one quarter of CpG island (CGI) CpGs. MMB was more precise in measuring DNA methylation, especially at sites that had low RRBS coverage. This impacted differential methylation analysis, with more statistically significantly differentially methylated CpG sites identified by MMB in all experimental conditions, however the difference was minute when appropriate thresholding for the magnitude of methylation change (0.2 beta value difference) was applied, providing confidence that both techniques can identify similar differential DNA methylation. Gene ontology enrichment analysis of differentially hypermethylated gene promoters identified similar biological processes and pathways by both RRBS and MMB across two murine model systems. Conclusion MMB is an effective tool for profiling the murine methylome that performs comparably to RRBS, identifying similar differentially methylated pathways. Although MMB captures a similar proportion of CpG islands, it does so with fewer CpGs per island. We show that subsampling informative CpGs from CpG islands is an appropriate strategy to capture whole island variation. Choice of technology is experiment dependent and will be predicated on the underlying biology being probed.

Broad activation of host T-cell immunity by immune checkpoint blockade, has revolutionized the treatment of some but not all B-cell lymphoproliferative disorders (LPDs). The challenge for next generation immunotherapeutics, is to successfully induce anti-tumor specific T-cell immunity across a range of B-LPDs, without provoking immune-related adverse events. An emerging strategy is to target neoantigens. Neoantigens are immunogenic peptides, unique to malignant cells, that are presented to T-cells via human leukocyte antigens. Neoantigens most commonly arise from non-synonymous mutations but can also be derived from tumor specific alterations along the protein biosynthesis pathway. B-cell LPDs uniquely express a clonal B-cell receptor (BCR) idiotype, consisting of immunoglobulin genes that undergo recombination and somatic hypermutation. Notably, the BCR idiotype can also give rise to 'immunoglobulin neoantigens'. Here, we provide an overview of current strategies to identify and validate immunoglobulin and non-immunoglobulin neoantigens as well as summarizing studies investigating neoantigens within B-cell LPDs.

Background: Next-generation sequencing is used in cancer research to identify somatic and germline mutations, which can predict sensitivity or resistance to therapies, and may be a useful tool to reveal drug repurposing opportunities between tumour types. Multigene panels are used in clinical practice for detecting targetable mutations. However, the value of clinical whole-exome sequencing (WES) and whole-genome sequencing (WGS) for cancer care is less defined, specifically as the majority of variants found using these technologies are of uncertain significance. Patients and methods: We used the Cancer Genome Interpreter and WGS in 726 tumours spanning 10 cancer types to identify drug repurposing opportunities. We compare the ability of WGS to detect actionable variants, tumour mutation burden (TMB) and microsatellite instability (MSI) by using in silico down-sampled data to mimic WES, a comprehensive sequencing panel and a hotspot mutation panel. Results: We reveal drug repurposing opportunities as numerous biomarkers are shared across many solid tumour types. Comprehensive panels identify the majority of approved actionable mutations, with WGS detecting more candidate actionable mutations for biomarkers currently in clinical trials. Moreover, estimated values for TMB and MSI vary when calculated from WGS, WES and panel data, and are dependent on whether all mutations or only non-synonymous mutations were used. Our results suggest that TMB and MSI thresholds should not only be tumour-dependent, but also be sequencing platform-dependent. Conclusions: There is a large opportunity to repurpose cancer drugs, and these data suggest that comprehensive sequencing is an invaluable source of information to guide clinical decisions by facilitating precision medicine and may provide a wealth of information for future studies. Furthermore, the sequencing and analysis approach used to estimate TMB may have clinical implications if a hard threshold is used to indicate which patients may respond to immunotherapy.

Researching the murine epigenome in disease models has been hampered by the lack of appropriate and cost-effective DNA methylation arrays. Here we perform a comprehensive, comparative analysis between the Mouse Methylation BeadChip (MMB) and reduced-representation bisulfite sequencing (RRBS) in two mu-rine models of colorectal carcinogenesis. We evaluate the coverage, variability, and ability to identify differ-ential DNA methylation of RRBS and MMB. We show that MMB is an effective tool for profiling the murine methylome that performs comparably with RRBS, identifying similar differentially methylated pathways. Although choice of technology is experiment dependent and will be predicated on the underlying biology be-ing probed, these analyses provide insights into the relative strengths and weaknesses of each approach.