Nonsynonymous Mutation Burden Research Articles

Abstract 5563: Novel approaches to measuring tumor-mutational burden provide insights into tumor-immune interaction in primary melanoma

Abstract Background: Tumor mutation burden (TMB) has been widely explored in metastatic melanoma as a proxy of neoantigenic load. In contrast, the role of TMB on the biology of primary melanoma disease progression is less understood. In this study, we explored the associations between the immune context of melanoma subtypes and TMB as measured by several standard and novel criteria. Methods: Whole-genome-sequencing and multiplex immunohistochemistry (mIHC) were used to characterize the genomic and immune landscape of a cohort of 116 primary melanomas, including cutaneous non-acral (n=59), acral (n=39) and mucosal (n=18) subtypes, as well as 5 mucosal metastases. mIHC was used to identify intratumoral CD8+ T-cells, memory T-cells, macrophages, dendritic cells, B-cells and PD-L1 expression. Standard measures of TMB -total mutational burden (tTMB) and non-synonymous (ns) mutational burden (nsTMB)- as well as novel measures that incorporate multiplicity and clonality -ns persistent mutation burden (ns-pTMB), and ns mutation dosage (ns-dosTMB) were calculated, and their association with immune profiles and clinical-pathological factors established. Results: In cutaneous non-acral melanomas, ns-pTMB and ns-dosTMB were positively associated with CD8+ T cell proportions (p=0.02 for both comparisons). Clonal, but not subclonal ns-pTMB from mutations present in single-copy regions of the genome were positively associated with higher tumor-resident CD103+CD8 T-cell (p=0.01) and B-cell proportions (p=0.02). Higher single-copy ns-pTMB was also associated with tumors presenting early/intermediate regression compared to late regression. In mucosal melanomas, clonal ns-dosTMB had the strongest positive association with the presence of macrophages (CD68, p=0.005). Additionally, macrophages (p=0.01), tissue resident memory T-cells (p=0.02), PDL1+ cells (p=0.03) and B-cells (p=0.048) were found to be positively associated with clonal ns-pTMB from mutations present in multiple copies, which was also positively associated with the presence of lymphatic invasion (p=0.03). Mucosal patients who recurred had lower levels of single-copy ns-pTMB (p=0.03). In acral melanomas, all measures of TMB were positively associated with the presence of dendritic cells (CD11c), with no particular role for clonality observed. In both cutaneous non-acral (p=0.046) and acral melanomas (p=0.03), but not mucosal (p=0.4), clonal ns-dosTMB was found positively associated with tumor mitotic rate. Conclusion: Novel TMB measures reveal associations between tumor and immune context that are not captured by standard TMB measures alone in primary melanomas. Different TMB measures are linked to distinct immune populations across melanoma subtypes that harbor unique genomic and immune landscapes. Clonal mutations play a dominant role in the associations of TMB with immune cell populations. Citation Format: Eva R. Shteinman, Nigel Maher, Jordan W. Conway, Grace H. Attrill, Felicity Newell, Nic Waddell, Nicholas Hayward, John V. Pearson, Georgina V. Long, Richard A. Scolyer, James S. Wilmott, Ismael A. Vergara. Novel approaches to measuring tumor-mutational burden provide insights into tumor-immune interaction in primary melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5563.

Abstract C061: Therapeutic profiling, patient response prediction, and tumor evolution in pancreatic cancer organoids

Abstract Pancreatic cancer (PC) is characterized by an aggressive biology and high tumor heterogeneity causing considerable variations in therapy response. Patient-derived organoids (PDOs) reflect parental tumor features and represent a powerful preclinical tool to predict drug response and harness personalized treatment. We have derived >100 PDO lines from treatment-naïve and pretreated PC patient primary tumor and metastases with a reliable efficacy and previously developed a pharmacotyping-guided prediction model to prognosticate patient therapy response (Beutel, 2021). Following up our initial feasibility trial, we now validated the model accuracy in real-life in a higher number of PC patients (43 cases). Additionally, a limited set of 7 PDO pairs were derived from the same patients at two distinct timepoints, followed by pharmacotyping and whole exome sequencing (WES). Our model allowed overall a successful drug-response prediction in naïve patients with an accuracy of 85.7% for first and second-line regimens. Prediction power was nevertheless lower in pretreated patients with a precision of 57.1% for subsequent chemotherapy lines. Intriguingly, a trend was observed towards a better performance of our system in prognosticating chemoresponsiveness vs. unresponsiveness (89.5% vs. 68.8%). Retrospective analysis of patient clinical data finally showed that the administration of a regimen predicted to be efficient ultimately translated into a longer progression-free survival. Importantly, the implementation of an automated pipetting system and the subsequent miniaturization of drug screenings enhanced our process capacity, conferring the possibility to extend our panel to a second list of approved targeted substances and significantly reducing the time before pharmacotyping. The access to longitudinal biopsies allowed to conduct WES on 14 PDOs to capture a comprehensive genetic profiling over the time of treatment, notably revealing a CHEK2-mutated patient responding over time upon PARP inhibitor maintenance therapy, in line with our PDO-based prediction, further highlighting the robustness of our method and algorithm. WES revealed a lower mutational burden and amount of nonsynonymous mutations upon chemotherapy, while tracking clonal evolution also revealed therapy-linked changes. Finally, to decipher the molecular mechanisms driving PC chemoresistance with an unprecedented level of accuracy, we took advantage of our phenotypically and therapeutically-profiled PDO living biobank and employed a true single-nucleus multiome approach to fully capture the transcriptome, as well as the chromatin accessibility landscape, of chemotherapy responsive and non-responsive PC PDOs. Overall, we report a robust and clinically-relevant preclinical tool for drug-response prediction, paving the way towards a PDO therapeutic profiling-guided true precision medicine in clinical routine. The identification of gene-regulatory networks and expression signatures driving chemoresistance may dramatically improve patient stratification and thus, foster true precision oncology. Citation Format: Johann Gout, Yazid J. Resheq, Jessica Lindenmayer, Thomas Ettrich, Lukas Perkhofer, Thomas Seufferlein, Alexander Kleger. Therapeutic profiling, patient response prediction, and tumor evolution in pancreatic cancer organoids [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C061.

ASXL1 Truncating Mutations Drive Leukemic Resistance to T Cell Attack

Restoration of graft-versus leukemia activity underlies the efficacy of donor lymphocyte infusion (DLI), a curative immunotherapy for leukemic relapse following allogeneic stem cell transplant (SCT). We found that while specific exhausted T cell subsets defined DLI response, no pattern of T cell dysfunction appeared in nonresponders (NRs) [PMID: 34758319]. We hypothesized that leukemic molecular pathways define DLI resistance (DLIr). We performed whole exome sequencing on bone marrow samples collected before and after DLI from 11 patients (pts) with relapsed chronic myeloid leukemia (CML) at Dana-Farber Cancer Institute. We used MuTect2 to discover somatic alterations using genomic DNA from recipient-derived mesenchymal stromal cells and donor peripheral blood cells as germline sources. The burden of nonsynonymous mutations and mutational spectra was similar between responders (Rs) and non-responders (NRs). Known non-Philadelphia (Ph) chromosome cancer drivers were found in 0/7 Rs and 4/4 NRs (RUNX1 (1/4), IKZF1 (2/4), and truncating exon 12 ASXL1 mutations (ASXL1 m) (3/4)). We profiled 6 more DLI-treated pts with relapsed CML from the MD Anderson Cancer Center with a targeted mutation panel that identified ASXL1 m in 4/5 NRs. Altogether, we found ASXL1 m in 78% (7/9) of NRs and 0% (0/10) of Rs (p=7e-4, two-sided Fisher's test), suggesting ASXL1 m as a driver of DLIr. To discover molecular pathways of DLIr, we interrogated unpublished non T-cell single cell (sc)RNA-seq data in our DLI cohort (8 R, 6 NR). Leukemic cells were identified for patients (n=8) with sex-mismatched SCT by male sex-defining genes, which correlated with Ph chromosomal positivity (Pearson correlation = 0.85). These cells were primarily confined to the myeloid population, so we performed a scRNA myeloid reclustering (138,152 cells) with Harmony batch correction and identified 5 populations enriched in R vs NR; 4 clusters in NR, and 1 monocyte cluster in R (p=0.039, 0.005, 0.038, 0.043, and 0.025, respectively). These NR clusters were enriched in progenitor cell identities, notably the LSC17 [PMID: 27926740] signature (p<2e-16). Interrogation of immune pathways in the LSC cluster showed downregulation of HLA-I and multiple antigen processing/presentation (APP) genes in NRs (p<2e-16), while HLA-II remained unchanged. Thus, ASXL1 m may mediate immune escape through suppression of HLA-I expression and antigen presentation. To directly test this hypothesis, we CRISPR corrected the endogenous ASXL1 m (Y591*) in a BCR-ABL-driven leukemic cell line (K562). This wildtype reversion (ASXL1 c) increased HLA-I expression at the RNA (RNA-seq; HLA-B/C, log2foldchange= -4.77, q=7e-42) and protein level (flow cytometry; 49.0% vs 1.62%, q=2e-4); here too, HLA-II expression remained unaffected by ASXL1 mutation status. Gene-set enrichment analysis also showed increased APP expression in ASXL1 c K562 (NES=-1.75, q=0.01). We then sought to identify whether correction of ASXL1m acted through known regulators of HLA-I. Treatment with IFNɣ or EPZ011989, an inhibitor of enhancer of zeste-homolog 2 (EZH2), resulted in greater HLA-I in K562 ASXL1 c (85.0% vs 50.2% and 89.5% vs 39.3%, respectively, q<0.001) suggesting that ASXL1 cacts orthogonally to IFNɣ or EZH2. ASXL1 c also mediated increased T-cell cytotoxicity towards K562 ASXL1 c vs ASXL1 m without (43% vs 16%, q=2e-4) and with IFNɣ pre-treatment (71% vs 34%, q=1e-6) at 10:1 target to effector ratios. Finally, to study other disease contexts, we examined published sc chromatin accessibility and scRNA-seq data from a chronic myelomonocytic leukemia cohort [PMID: 35301312] and an acute myeloid leukemia cohort [PMID:32649887], respectively. We found both chromatin and transcriptional states enriched in ASXL1m samples to have decreased accessibility and expression, respectively, of HLA-I and APP genes (p<2E-16). In summary, we integrated molecular analyses with immuno-functional studies to define a novel oncogenetic pathway of immune evasion. Specifically, we link DLIr to ASXL1 m that suppresses transcription of HLA-I and antigen presentation machinery in myeloid diseases; moreover, its correction restores anti-leukemic CD8+ T-cell cytotoxicity. Ongoing studies will examine additional clinical contexts and the epigenetic mechanisms by which ASXL1m regulates HLA-I expression.

A gut microbiota rheostat to forecast response to PDL1-VEGF blockade in mesothelioma.

e20534 Background: Targeting of the immune inhibitory PD1-PDL1 axis has proven clinically effective in mesothelioma, despite a low somatic mutation burden, and high rate of CDKN2A deletion. Tumour responses to anti PD1 or PDL1 immune checkpoint inhibition are heterogeneous, and the factors underpinning sensitivity remain poorly understood. We therefore addressed this knowledge gap through multi-omic interrogation of tumours from patients enrolled into arm 4 of the Mesothelioma Stratified Therapy umbrella trial (NCT03654833, MiST4), a multi-centre single arm phase IIA trial of atezolizumab and bevacizumab in patients with relapsed mesothelioma. Methods: Next generation sequencing of whole exomes (mesotheliomas and matched germline DNA), transcriptomes, and 16sRNA to profile gut microbiota were undertaken. Spatial phenotyping of the immune landscape employed multiplex immunofluorescence analysis using a 19x depth 4 panel detection. Tumour proportion score (TPS) for PDL1 was assessed using the 22C3 clone, and BAP1, p16ink4a assessed by immunohistochemistry. The MIST4 cohort was dichotomised by best tumour response (50:50) into those patients exhibiting any tumour reduction (R) versus those without (NR). Machine learning (boosting and bagging) was employed to decipher correlates of response. Results: Tumour responses correlated with progression-free survival (PFS, p = 0.0003). Neither PDL1 TPS or CDKN2A expression were predictive. The NR group exhibited a greater degree of genomic instability with higher somatic copy number burden (p = 0.02), homologous recombination deficiency (HRD, p = 0.03), and uniparental disomy (UPD, p = 0.01). Notably the burden of nonsynonymous mutations and neoantigens did not differ significantly between groups. The NR group was transcriptionally enriched for epithelial mesenchymal transition (p < 0.05). Conversely, 16s RNA sequencing revealed higher gut microbial diversity in the R group compared with NR (Shannon index p = 0.009) with R-group enrichment of the type 2 enterotype (provotella 33% vs 9%). R-group enriched genera comprised prevotella, butyricicoccus, bilophilla, Eubacterium ventriosum, whereas the NR group was enriched for erysipelatoclostidium. The log ratio of genera, ie. Log[GR/GNR] was 2-log higher for the R group (p < 0.0001) vs NR group, and was highly predictive of response (with an area under the receiver operator curve of 0.99). Log[GR/GNR] positively correlated with tumour CD8 T cell infiltration (r = 0.6, p = 0.05) and PFS (p = 0.04), but negatively with CD68 monocyte infiltration (p = 0.05), UPD (p = 0.008) and HRD (p = 0.05). Conclusions: We propose a model in which interacting tumour intrinsic and extrinsic factors correlate with response to PDL1-VEGF inhibition in patients with mesothelioma. Gut microbiota composition represents a new, potentially modifiable target with potential to improve immunotherapy outcomes in patients with mesothelioma. Clinical trial information: NCT03654833 .

Social, Genetics and Histopathological Factors Related to Titin (TTN) Gene Mutation and Survival in Women with Ovarian Serous Cystadenocarcinoma: Bioinformatics Analysis

Several factors may increase the risk of development of ovarian cancer. In this study, we investigated the relationship between social, genetic, and histopathologic factors in women with ovarian serous cystadenocarcinoma and titin (TTN) mutations, whether the TTN gene mutation may be a predictor, and its impact on mortality and survival in these patients. A total of 585 samples from patients with ovarian serous cystadenocarcinoma were collected from The Cancer Genome Atlas and PanCancer Atlas through the cBioPortal for analysis of social, genetic, and histopathological factors. Logistic regression was used to investigate whether TTN mutation could be a predictor, and the Kaplan-Meier method was applied to analyze survival time. TTN mutation frequency did not differ between age at diagnosis, tumor stage, and race, and was related to increased Buffa hypoxia score (p = 0.004), mutation count (p < 0.0001), Winter hypoxia Score (p = 0.030), nonsynonymous tumor mutation burden (TMB) (p < 0.0001), and reduced microsatellite instability sensor score (p = 0.010). The number of mutations (p < 0.0001) and winter hypoxia score (p = 0.008) were positively associated with TTN mutations, and nonsynonymous TMB (p < 0.0001) proved to be a predictor. Mutated TTN affects the score of genetic variables involved in cancer cell metabolism in ovarian cystadenocarcinoma.

Abstract 4256: cBioPortal for Cancer Genomics

Abstract cBioPortal for Cancer Genomics is an open-source platform for interactive, exploratory analysis of large-scale clinico-genomic data sets. cBioPortal provides a suite of user-friendly visualizations and analyses, including OncoPrints, mutation “lollipop” plots, variant interpretation, group comparison, survival analysis, expression correlation analysis, alteration enrichment analysis, cohort and patient-level visualization. The public site (https://www.cbioportal.org) is accessed by &amp;gt;35,000 unique visitors each month and hosts data from &amp;gt;350 studies spanning individual labs and large consortia. In addition, at least 74 instances of cBioPortal are installed at academic institutions and companies worldwide. To better support all users, we unified our documentation (https://docs.cbioportal.org) and added a user guide and an ongoing series of ‘how-to’ videos to address common questions. In 2022 we added 32 studies (&amp;gt;38,000 samples) to the public site. In addition, we added a nonsynonymous tumor mutation burden (TMB) value for all samples and enhanced the TCGA PanCancer Atlas studies with DNA methylation and treatment data. All data is available in the cBioPortal Datahub: https://github.com/cBioPortal/datahub. We also host a dedicated instance for AACR Project GENIE, enabling access to the GENIE cohort of &amp;gt;165,000 clinically sequenced samples from 19 institutions (https://genie.cbioportal.org). The GENIE Biopharma Collaborative (BPC) enables the collection of comprehensive clinical annotations, including response, outcome, and treatment history. The first BPC cohorts are now available: ~2,000 non-small cell lung cancer samples and ~1,500 colorectal cancer samples. Support for multimodal data analysis has been a major focus, including several new integrations with external tools. Single cell data is now available in the CPTAC GBM study and can be visualized throughout cBioPortal, and via integration with cellxgene. On the patient page, H&amp;E and mIF images can be visualized via integration with Minerva, and the genomic overview now integrates IGV. We continue to enhance existing features. In the study view, users can now add charts comparing categorical vs continuous data, and the plots tab includes a heatmap option. We replaced the existing fusion data type with a generalized structural variant data type that supports detailed information including breakpoints and orientation, to enable new visualizations and analyses. Pathway level analysis has been extended with a new integration with NDEx. cBioPortal is fully open source (https://github.com/cBioPortal/). Development is a collaborative effort among groups at Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Children’s Hospital of Philadelphia, Princess Margaret Cancer Centre, Caris Life Sciences, Bilkent University and The Hyve. We welcome open source contributions from others in the cancer research community. Citation Format: Ino de Bruijn, Tali Mazor, Adam Abeshouse, Diana Baiceanu, Stephanie Carrero, Elena Garcia Lara, Benjamin Gross, David M. Higgins, Prasanna K. Jagannathan, Priti Kumari, Ritika Kundra, Bryan Lai, Xiang Li, James Lindsay, Aaron Lisman, Divya Madala, Ramyasree Madupuri, Angelica Ochoa, Yusuf Ziya Özgül, Oleguer Plantalech, Sander Rodenburg, Baby Anusha Satravada, Robert Sheridan, Lucas Sikina, Jessica Singh, S Onur Sumer, Yichao Sun, Pim van Nierop, Avery Wang, Manda Wilson, Hongxin Zhang, Gaofei Zhao, Sjoerd van Hagen, Ugur Dogrusoz, Allison Heath, Adam Resnick, Trevor J. Pugh, Chris Sander, Ethan Cerami, Jianjiong Gao, Nikolaus Schultz. cBioPortal for Cancer Genomics. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4256.

Abstract 6762: Tumor immune microenvironment &amp;genomic features of non-small cell lung carcinomas in patients with HIV (PWH)

Abstract Introduction: Lung cancer is the leading cause of cancer-related death among PWH with a relative risk that is over 3-fold higher compared to the uninfected population. In addition, HIV-infected patients with non-small cell lung cancer (NSCLC) have a significantly worse prognosis. The determinants for these associations remain uncertain. Methods: We investigated the immune contexture of 18 primary NSCLCs from PWH and 19 clinicopathologically matched NSCLCs from HIV-negative cases represented in tissue microarrays using 37-plex Imaging Mass Cytometry (IMC) panels including cell phenotype markers (CK,CD4,CD8,CD20,CD45RO,CD25,etc), immunomodulatory targets (PD-L1,PD-L2,B7-H3,B7-H4,B2M,etc) and DNA damage response/repair (DDR) indicators (γH2AX, RAD51,BRCA1,53BP1,etc). The samples were analyzed using single-cell tissue segmentation and spatial analysis. A subset of cases was also studied using whole exome DNA sequencing (WES) and mRNA sequencing (RNAseq). Results: NSCLCs from PWH showed comparable levels of tumor infiltrating lymphocytes (TILs) relative to HIV-negative cases with a trend towards a lower CD4+/CD8+ cell ratio. However, CD4+ and CD8+ TILs in PWH showed higher levels of markers associated with T-cell activation and dysfunction including GZB, CD25, Ki-67, PD-1, LAG-3, and TIM-3 than non-HIV tumors. The epithelial tumor cells in HIV-associated cases showed higher levels of the immunomodulatory ligands PD-L1, CD47, B7-H4 and VISTA; and altered levels of the DDR markers γH2AX, BRCA1 and 53BP1 relative to the non-HIV controls. Differences were also seen in tumor-associated macrophages consistent with an immune regulatory environment. The spatial analysis of tumor and immune cells revealed a distinct topographic distribution of these cells in HIV-associated malignancies. WES analysis showed a higher nonsynonymous tumor mutational burden in HIV-associated tumors (400 vs 202 mean mutations/exome) with increased predicted HLA class-I neoantigens and a numerically higher immunoediting score than the non-HIV group. Exploratory analysis identified enrichment in RYR2 and KIAA1671 gene mutations in HIV-associated malignancies. RNAseq revealed distinct mRNA expression profiles of HIV-positive and negative NSCLCs with a fraction of transcripts showing differential expression associated with tumor suppressor functions, interleukin signaling and DDR. Conclusion: NSCLCs in PWH display profound immunological and genomic alterations suggesting defective immunosurveillance. Our study reveals novel characteristics of HIV-associated NSCLC with possible clinical implications for this growing and understudied population. Citation Format: Shruti Desai, Kishu Ranjan, Syim Salahuddin, Ramsey Yusuf, Jianlei Gu, Daiwei Tang, Yong Kong, Barani Kumar Rajendran, Hongyu Zhao, Yuval Kluger, Sarah Goldberg, Brinda Emu, Kurt Alex Schalper. Tumor immune microenvironment &amp;genomic features of non-small cell lung carcinomas in patients with HIV (PWH) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6762.

83P The efficacy of combining adoptive immunotherapy by human Vγ2Vδ2 T cells and PD-1 checkpoint blockade against human prostate cancer

Human Vγ2Vδ2 T cells play important roles in microbial and tumor immunity by monitoring foreign- and self-prenyl pyrophosphate metabolites in isoprenoid biosynthesis. Accumulation of isoprenoid metabolites after bisphosphonate treatment allows Vγ2Vδ2 cells to recognize and kill tumors independently of their MHC expression or burden of non-synonymous mutations. Clinical trials with more than 400 patients show that adoptive immunotherapy with Vγ2Vδ2 T cells has few side effects but has resulted in only a few partial and complete remissions.

342. GENOMIC ANALYSIS OF RESPONSE TO NEOADJUVANT CHEMOTHERAPY IN OESOPHAGEAL ADENOCARCINOMA

Abstract Oesophageal adenocarcinoma (OAC) is the ninth most common cancer worldwide, with a mortality of &amp;gt;500,000 deaths yearly. Neoadjuvant chemotherapy (NAC) followed by surgery is the standard of care (SOC) for locally advanced OAC. Although almost all patients receive chemotherapy as SOC, but &amp;lt;20% respond and benefit from chemotherapy before surgery. The OAC genome is complex and heterogeneous between patients, and it is not yet understood whether specific mutational patterns may result in chemotherapy sensitivity or resistance. To identify associations between genomic events and response to NAC in OAC, a comparative genomic analysis was performed in 65 patients using whole-genome sequencing. We defined response to NAC using Mandard Tumour Regression Grade TRG), with responders classified as TRG1–2 (n = 27) and non-responders classified as TRG4–5 (n = 38). We report a higher non-synonymous mutation burden in responders (median 2.08/Mb vs 1.70/Mb, P = 0.036) and elevated copy number variation (CNV) in non-responders (282 vs 136/patient, P &amp;lt; 0.001). We identified CNVs unique to each group, with cell cycle (CDKN2A, CCND1), c-Myc (MYC), RTK/PIK3 (KRAS, EGFR) and gastrointestinal differentiation (GATA6) pathway genes being specifically altered in non-responders. Of particular interest was the identification of the Neuron Navigator-3 (NAV3), a known tumour suppressor downstream of EGFR, which was mutated exclusively in 22% of non-responders. Our work characterises genetic features and mutations that are uniquely associated with response to NAC. We envision a treatment pipeline that incorporates driver mutation profiling in OAC, combining response prediction with targeted therapies to enhance response to NAC and improve survival outcomes.

O086 Genomic analysis of response to neoadjuvant chemotherapy in oesophageal adenocarcinoma

Abstract Introduction Oesophageal adenocarcinoma (OAC) is the ninth most common cancer worldwide with a mortality of over 500,000 deaths yearly. Neoadjuvant chemotherapy (NAC) followed by surgery is the standard of care (SOC) for locally advanced OAC. Although almost all patients receive chemotherapy as SOC, fewer than 20% obtain a clinically meaningful response and benefit before surgery. The OAC genome is complex and heterogeneous between patients, and it is not yet understood whether specific mutational patterns result in chemotherapy sensitivity or resistance. Methods To identify associations between genomic events and response to NAC in OAC, a comparative genomic analysis was performed in 65 patients using whole-genome sequencing. We defined response to NAC using Mandard Tumour Regression Grade TRG), with responders classified as TRG1-2 (n=27) and non-responders classified as TRG4- 5 (n=38). Results We report a higher non-synonymous mutation burden in responders (median 2.08/Mb vs 1.70/Mb, P=0.036) and elevated copy number variation (CNV) in non-responders (282 vs 136/patient, P&amp;lt;0.001). We identified CNVs unique to each group, with cell cycle (CDKN2A, CCND1), c-Myc (MYC), RTK/PIK3 (KRAS, EGFR) and gastrointestinal differentiation (GATA6) pathway genes being specifically altered in non-responders. Of particular interest was the identification of the Neuron Navigator-3 (NAV3), a known tumour suppressor downstream of EGFR, which was mutated exclusively in 22% of non-responders. Conclusion We characterise genetic features and mutations that are uniquely associated with response to NAC. We envision a treatment pipeline that incorporates driver mutation profiling in OAC, combining response prediction with targeted therapies enhancing response to NAC and improving survival outcomes. Take-home message Developing a method of determining an OAC patient's response to neoadjuvant chemotherapy before treatment is administered is desperately needed and will improve patient outcome and quality of life. We identified a number of aberrations in the genome that were unique to non-responders to chemotherapy compared to responders, particularly a known tumour suppressor gene namely Neuron Navigator-3, suggesting that these events may contribute to chemoresistance in these patients. Our work characterises pre-existing genomic alterations that have potential as biomarkers for resistance or sensitivity to NAC.

Role of immunotherapy in metastatic EGFRm NSCLC: Is it relevant?

EGFR-TKIs have changed the landscape of metastatic NSCLC treatment with a significant improvement in survival of EGFRm patients compared to wild-type EGFR. Even with the newer third generation EGFR TKIs like, Osimertinib, which has proven efficacy against the resistance mutation of EGFRm T790M, progression eventually occurs. There are limited treatment options for patients with metastatic EGFRm NSCLC with other acquired resistance. Therefore, novel therapeutic combination strategies are being researched to overcome potential resistance to EGFR-TKI-targeted therapy. The ICIs targeting the programmed cell death-1 pathway in patients with EGFRm NSCLC were greatly anticipated based on preclinical studies showing increased PD-L1 expression. In clinical settings, this increased expression did not translate into a survival benefit. Treatment with ICIs failed to positively affect EGFRm patients because of multiple reasons: nonsynonymous tumor mutational burden, lower PD-L1 expression in tumors, and cancer cells utilizing alternate immune escape mechanisms. The NCCN guidelines currently do not recommend immunotherapy in patients with metastatic EGFRm NSCLC. Recently, a subgroup analysis in the IMpower150 study provided a signal for overall survival of atezolizumab with bevacizumab plus chemotherapy in EGFRm-TKI progressed patients. Based on these encouraging findings, several combinations of ICIs and EGFR-TKIs are being evaluated in TKI-failed EGFRm patients. These regimens might provide a favorable therapeutic effect by combining higher response rates of TKIs and durable disease control of ICIs. However, further research is warranted to understand the exact underlying molecular and cellular mechanisms responsible for the clinical benefits. In this article, we explored the TKI failed metastatic EGFRm NSCLC, reviewed the available clinical data of ICI use in metastatic EGFRm NSCLC, and discussed its emerging role as a combination regimen in this patient population.

O-OGC06 Genomic analysis of response to neoadjuvant chemotherapy in oesophageal adenocarcinoma

Abstract Background Oesophageal adenocarcinoma (OAC) is the ninth most common cancer worldwide, with an estimated mortality of over 500,000 deaths yearly. Neoadjuvant chemotherapy (NAC) followed by surgery is the standard of care (SOC) for locally advanced OAC. Although almost all patients receive chemotherapy as SOC, fewer than 20% obtain a clinically meaningful response and benefit before surgery. The OAC genome is complex and heterogeneous between patients, and it is not yet understood whether specific mutational patterns may result in chemotherapy sensitivity or resistance. Methods To identify associations between genomic events and response to NAC in OAC, a comparative genomic analysis was performed in 65 patients using whole-genome sequencing. We defined response to NAC using Mandard Tumour Regression Grade (TRG), with responders classified as TRG1-2 (n = 27) and non-responders classified as TRG4-5 (n = 38). Results We report a higher non-synonymous mutation burden in responders (median 2.08/Mb vs 1.70/Mb, P = 0.036) and elevated copy number variation (CNV) in non-responders (282 vs 136/patient, P&amp;lt;0.001). We identified CNVs unique to each group, with cell cycle (CDKN2A, CCND1), c-Myc (MYC), RTK/PIK3 (KRAS, EGFR) and gastrointestinal differentiation (GATA6) pathway genes being specifically altered in non-responders. Of particular interest was the identification of the Neuron Navigator-3 (NAV3), a known tumour suppressor downstream of EGFR, which was mutated exclusively in non-responders with a frequency of 22%. Conclusions Our work characterises genetic features and mutations that are uniquely associated with response to NAC. We envision a treatment pipeline that incorporates driver mutation profiling in OAC, combining response prediction with targeted therapies to enhance response to NAC and improve survival outcomes.

Genomic Analysis of Response to Neoadjuvant Chemotherapy in Esophageal Adenocarcinoma.

Simple SummaryEsophageal adenocarcinoma (EAC) is a cancer with very poor survival outcomes. Patients are treated with pre-operative chemotherapy or chemoradiotherapy before surgery. However, four out of every five patients do not respond to pre-operative therapy and these patients (non-responders) have significantly worse outcomes. Identifying non-responders prior to therapy would allow alternative treatment pathways to be offered to these patients. In this study, we analyze whole genome sequences of pre-treatment biopsies from 65 patients and find that non-responders display chromosomal instability and increased gene copy number alterations. We report a distinct profile of copy number alterations in non-responders compared to responders, predominantly in genes involved in cell cycle control and RTK/Ras signaling. Mutations in the tumor suppressor NAV3 are also found exclusively in non-responders. These genetic profiles present potential drug targets for investigation in EAC patients who would not respond to pre-operative chemotherapy.Neoadjuvant therapy followed by surgery is the standard of care for locally advanced esophageal adenocarcinoma (EAC). Unfortunately, response to neoadjuvant chemotherapy (NAC) is poor (20–37%), as is the overall survival benefit at five years (9%). The EAC genome is complex and heterogeneous between patients, and it is not yet understood whether specific mutational patterns may result in chemotherapy sensitivity or resistance. To identify associations between genomic events and response to NAC in EAC, a comparative genomic analysis was performed in 65 patients with extensive clinical and pathological annotation using whole-genome sequencing (WGS). We defined response using Mandard Tumor Regression Grade (TRG), with responders classified as TRG1–2 (n = 27) and non-responders classified as TRG4–5 (n =38). We report a higher non-synonymous mutation burden in responders (median 2.08/Mb vs. 1.70/Mb, p = 0.036) and elevated copy number variation in non-responders (282 vs. 136/patient, p < 0.001). We identified copy number variants unique to each group in our cohort, with cell cycle (CDKN2A, CCND1), c-Myc (MYC), RTK/PIK3 (KRAS, EGFR) and gastrointestinal differentiation (GATA6) pathway genes being specifically altered in non-responders. Of note, NAV3 mutations were exclusively present in the non-responder group with a frequency of 22%. Thus, lower mutation burden, higher chromosomal instability and specific copy number alterations are associated with resistance to NAC.

Leveraging Big Data of Immune Checkpoint Blockade Response Identifies Novel Potential Targets

We here report a large-scale comparative meta-analysis of genomics and gene expression signatures of immune checkpoint blockade (ICB) responses in over 3,500 patients across 12 tumor types. Non-synonymous tumor mutational burden (nsTMB), as well as 22 out of 39 reported gene expression signatures, were significantly associated with pan-cancer ICB responses. Strikingly, the predictive value of a de novo gene expression signature (PredictIO_100), composed of the top 100 genes most significantly associated with ICB responses at pan-cancer level, was superior to nsTMB and other gene expression signatures. Two genes within PredictIO_100, F2RL1 (encoding protease-activated receptor-2) and RBFOX2 (encoding RNA binding motif protein 9), were concurrently associated with worse ICB clinical outcomes, T cell dysfunction in ICB-naive patients and resistance to dual PD-1/CTLA-4 blockade in preclinical models. Our study underlines the relative impact of candidate biomarkers of ICB responses and identifies F2RL1 and RBFOX2 as potential therapeutic targets to overcome ICB resistance.

The pan-cancer landscape of crosstalk between epithelial-mesenchymal transition and immune evasion relevant to prognosis and immunotherapy response

An emerging body of evidence has recently recognized the coexistence of epithelial-mesenchymal transition (EMT) and immune response. However, a systems-level view and survey of the interplay between EMT and immune escape program, and their impact on tumor behavior and clinical outcome across various types of cancer is lacking. Here, we performed comprehensive multi-omics analyses to characterize the landscape of crosstalk between EMT and immune evasion and their clinical relevance across 17 types of solid cancer. Our study showed the presence of complex and dynamic immunomodulatory crosstalk between EMT and immune evasion shared by pan-cancer, and the crosstalk was significantly associated with cancer prognosis and immunotherapy response. Integrative quantitative analyses of genomics and immunogenomics revealed that cellular composition of immune infiltrates, non-synonymous mutation burden, chromosomal instability and oncogenic gene alterations are associated with the balance between EMT and immune evasion. Finally, we proposed a scoring model termed EMT-CYT Index (ECI) to quantify the EMT-immunity axis, which was a superior predictor of prognosis and immunotherapy response across different malignancies. By providing a systematic overview of crosstalk between EMT and immune evasion, our study highlights the potential of pan-cancer EMT-immunity crosstalk as a paradigm for dissecting molecular mechanisms underlying cancer progression and guiding more effective and generalized immunotherapy strategies.

The mutagenic impact of melphalan in multiple myeloma.

The introduction of whole genome and exome sequencing partnered with advanced bioinformatic pipelines has allowed the comprehensive characterization of mutational processes (i.e., mutational signatures) in individual cancer patients. Studies focusing on multiple myeloma have defined several mutational processes, including a recently identified mutational signature (called "SBS-MM1") directly caused by exposure to high-dose melphalan (i.e., autologous stem cell transplant). High-dose melphalan exposure increases both the overall and nonsynonymous mutational burden detected between diagnosis and relapse by ~10-20%. Nevertheless, most of these mutations are acquired within the heterochromatin and late-replicating regions, rarely involving key myeloma driver genes. In this review, we summarize key studies that made this discovery possible, and we discuss potential clinical implications.

Genomic landscape of extraordinary responses in metastatic breast cancer

Extreme responders to anticancer therapy are rare among advanced breast cancer patients. Researchers, however, have yet to investigate treatment responses therein on the whole exome level. We performed whole exome analysis to characterize the genomic landscape of extreme responders among metastatic breast cancer patients. Clinical samples were obtained from breast cancer patients who showed exceptional responses to anti-HER2 therapy or hormonal therapy and from those who did not. Matched breast tumor tissue (somatic DNA) and blood samples (germline DNA) were collected from a total of 30 responders and 15 non-responders. Whole exome sequencing using Illumina HiSeq2500 was performed for all 45 patients (90 samples). Somatic single nucleotide variants (SNVs), indels, and copy number variants (CNVs) were identified for the genomes of each patient. Group-specific somatic variants and mutational burden were statistically analyzed. Sequencing of cancer exomes for all patients revealed 1839 somatic SNVs (1661 missense, 120 nonsense, 43 splice-site, 15 start/stop-lost) and 368 insertions/deletions (273 frameshift, 95 in-frame), with a median of 0.7 mutations per megabase (range, 0.08 to 4.2 mutations per megabase). Responders harbored a significantly lower nonsynonymous mutational burden (median, 26 vs. 59, P = 0.02) and fewer CNVs (median 13.6 vs. 97.7, P = 0.05) than non-responders. Multivariate analyses of factors influencing progression-free survival showed that a high mutational burden and visceral metastases were significantly related with disease progression. Extreme responders to treatment for metastatic breast cancer are characterized by fewer nonsynonymous mutations and CNVs.

PD-1 checkpoint blockade enhances adoptive immunotherapy by human Vγ2Vδ2 T cells against human prostate cancer

ABSTRACT Human Vγ2Vδ2 (also termed Vγ9Vδ2) T cells play important roles in microbial and tumor immunity by monitoring foreign- and self-prenyl pyrophosphate metabolites in isoprenoid biosynthesis. Accumulation of isoprenoid metabolites after bisphosphonate treatment allows Vγ2Vδ2 T cells to recognize and kill tumors independently of their MHC expression or burden of non-synonymous mutations. Clinical trials with more than 400 patients show that adoptive immunotherapy with Vγ2Vδ2 T cells has few side effects but has resulted in only a few partial and complete remissions. Here, we have tested Vγ2Vδ2 T cells for expression of inhibitory receptors and determined whether adding PD-1 checkpoint blockade to adoptively transferred Vγ2Vδ2 T cells enhances immunity to human PC-3 prostate tumors in an NSG mouse model. We find that Vγ2Vδ2 T cells express PD-1, CTLA-4, LAG-3, and TIM-3 inhibitory receptors during the 14-day ex vivo expansion period, and PD-1, LAG-3, and TIM-3 upon subsequent stimulation by pamidronate-treated tumor cells. Expression of PD-L1 on PC-3 prostate cancer cells was increased by co-culture with activated Vγ2Vδ2 T cells. Importantly, anti-PD-1 mAb treatment enhanced Vγ2Vδ2 T cell immunity to PC-3 tumors in immunodeficient NSG mice, reducing tumor volume nearly to zero after 5 weeks. These results demonstrate that PD-1 checkpoint blockade can enhance the effectiveness of adoptive immunotherapy with human γδ T cells in treating prostate tumors in a preclinical model.

Prognostic value of immune scores in the microenvironment of colorectal cancer.

Cancer immunotherapy has become an important means of cancer treatment; however, the complex composition and heterogeneity of the colorectal cancer (CRC) microenvironment pose a huge challenge to cancer immunotherapy. Using data downloaded from The Cancer Genome Atlas database, the differences in the microenvironment between cases with low and high immune scores were examined at the multiomics level using bioinformatics approaches. It was revealed that the samples with high immune scores had good cytolytic immune responses and relatively abundant stromal cells, as well as significant infiltration of 22 immune cell subsets and a high non-synonymous mutation burden and neoantigen burden. All of these characteristics contribute to a good prognosis. To better understand the impact of immune-related genes on prognosis, differentially expressed genes between the low and high immune score samples were identified and it was concluded that serpin family Emember 1 (SERPINE1) and ubiquitin C-terminal hydrolase L1 (UCHL1) may be potential therapeutic targets. The relationship between the immune score and the infiltration of 22 immune cells and the difference in SERPINE1 expression were verified by analyzing the GSE17536 and GSE21510 data sets downloaded from the Gene Expression Omnibus database. The present study analyzed the unique properties of immune cells in the CRC microenvironment, which are of great significance for understanding CRC immune mechanism and may also provide novel ideas for the targeted design of cancer immunotherapy.

Characterization of gene expression profiles of esophageal cancer patients with different nonsynonymous tumor mutation burden.

BackgroundNonsynonymous tumor mutation burden (NSTMB) could affect the prognosis of esophageal cancer (EC) patients, but differentially expressed genes between EC patients with different NSTMB have not been explored. Our study aimed to compare differentially expressed genes between EC patients with different NSTMB (high vs. low).MethodsRNA‐seq data for EC patients were downloaded from The Cancer Genome Atlas (TCGA). The edgeR package was used to identify differentially expressed genes between patients with different NSTMB. Cell type identification by estimating relative subsets of known RNA transcripts (CIBERSORT) software was employed to underscore immune cell differences between patients with different NSTMB.ResultsIn total, we discovered 2215 differentially expressed genes between patients with different NSTMB, among which 842 genes were upregulated and 1373 downregulated in patients with high NSTMB. The differentially expressed genes were enriched in pathways such as heme binding and structural molecule activity. We built a logistic model that may be used to predict patients' NSTMB. We found that tumors with high NSTMB had a significantly higher percentage of resting natural killer (NK) cells than those with low NSTMB (P = 0.028). The percentages of regulatory T (Treg) and CD8+ T cells were also higher in those with high NSTMB, although it was not statistically significant (P = 0.064 for Treg cells and P = 0.12 for CD8+ T cells).ConclusionsNSTMB may cause changes in gene expression and immune cell infiltration in EC patients, and affect the overall survival of EC patients.Key points Significant findings of the study This study found differentially expressed genes and differences in infiltration of immune cells between esophageal cancer (EC) with different NSTMB. What this study adds This study highlights differences between EC patients with different NSTMB.