Performance of somatic structural variant calling in lung cancer using Oxford Nanopore sequencing technology.

BACKGROUND: Lung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and seven structural variant callers comprised of generic callers (SVIM, Sniffles2, DELLY in generic mode and cuteSV) and somatic callers (Severus, SAVANA, nanomonsv and DELLY in somatic modes). RESULTS: Different combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short-read sequencing. When compared to somatic structural variants detected with short-read sequencing, more events were detected with long-read sequencing. The mean recall of somatic variant events identified by long-read sequencing was higher for the somatic callers (72%) than generic callers (53%). Among the somatic callers when using the minimap2 aligner, SAVANA and Severus achieved the highest recall at 79.5% and 79.25% respectively, followed by nanomonsv with a recall of 72.5%. CONCLUSION: Long-read sequencing can identify somatic structural variants in clincal samples. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

Spatial intra-tumour heterogeneity and treatment-induced genomic evolution in oesophageal adenocarcinoma: implications for prognosis and therapy.

BACKGROUND: Oesophageal adenocarcinoma (OAC) is a highly heterogeneous cancer with poor survival. Standard curative treatment is chemotherapy with or without radiotherapy followed by oesophagectomy. Genomic heterogeneity is a feature of OAC and has been linked to treatment resistance. METHODS: Whole-genome sequencing data from 59 treatment-naïve and 18 post-treatment samples from 29 OAC patients was analysed. Twenty-seven of these were enrolled in the DOCTOR trial, sponsored by the Australasian Gastro-Intestinal Trials Group. Two biopsies from each treatment-naïve tumour were assessed to define 'shared' (between both samples) and 'private' (present in one sample) mutations. RESULTS: Mutational signatures SBS2/13 (APOBEC) and SBS3 (BRCA) were almost exclusively detected in private mutation populations of treatment-naïve tumours. Patients presenting these signatures had significantly worse disease specific survival. Furthermore, mutational signatures associated with platinum-based chemotherapy treatment as well as high platinum enrichment scores were only detected in post-treatment samples. Additionally, clones with high putative neoantigen binding scores were detected in some treatment-naïve samples suggesting immunoediting of clones. CONCLUSIONS: This study demonstrates the high intra-tumour heterogeneity in OAC, as well as indicators for treatment-induced changes during tumour evolution. Intra-tumour heterogeneity remains a problem for successful treatment strategies in OAC.

High-level tumour methylation of BRCA1 and RAD51C is required for homologous recombination deficiency in solid cancers.

In ovarian and breast cancer, promoter methylation of BRCA1 or RAD51C is a promising biomarker for PARP inhibitor response, as high levels lead to homologous recombination deficiency (HRD). Yet the extent and role of such methylation in other cancers is not clear. This study comprehensively investigated promoter methylation of eight homologous recombination repair genes across 23 solid cancer types. Here, we showed that BRCA1 methylated cancers were associated with reduced gene expression, loss of heterozygosity (LOH), TP53 mutations and genomic features of HRD. We identified BRCA1 methylation in 3% of the copy-number high subtype of endometrial cancer, and as a rare event in six other cancer types, including lung squamous cell, pancreatic, bladder and stomach cancer. RAD51C promoter methylation was widespread across multiple cancer types, but HRD features were only observed for cases which contained high-level tumour methylation and LOH of RAD51C. While RAD51C methylation was frequent in stomach adenocarcinoma (6%) and low-grade glioma (2.5%), it was mostly detected at a low tumour level, suggestive of heterozygous methylation, and was associated with CpG island methylator phenotype. Our findings indicate that high-level tumour methylation of BRCA1 and RAD51C should be explored as a PARP inhibitor biomarker across multiple cancers.

Germline variants alter immune surveillance.

Germline-derived epitopes shape tumor development through immunoediting.

Clinically significant changes in genes and variants associated with epilepsy over time: implications for re-analysis.

Despite the significant advances in understanding the genetic architecture of epilepsy, many patients do not receive a molecular diagnosis after genomic testing. Re-analysing existing genomic data has emerged as a potent method to increase diagnostic yields-providing the benefits of genomic-enabled medicine to more individuals afflicted with a range of different conditions. The primary drivers for these new diagnoses are the discovery of novel gene-disease and variants-disease relationships; however, most decisions to trigger re-analysis are based on the passage of time rather than the accumulation of new knowledge. To explore how our understanding of a specific condition changes and how this impacts re-analysis of genomic data from epilepsy patients, we developed Vigelint. This approach combines the information from PanelApp and ClinVar to characterise how the clinically relevant genes and causative variants available to laboratories change over time, and this approach to five clinical-grade epilepsy panels. Applying the Vigelint pipeline to these panels revealed highly variable patterns in new, clinically relevant knowledge becoming publicly available. This variability indicates that a more dynamic approach to re-analysis may benefit the diagnosis and treatment of epilepsy patients. Moreover, this work suggests that Vigelint can provide empirical data to guide more nuanced, condition-specific approaches to re-analysis.

Evaluation of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) Samples from Advanced Non-Small Cell Lung Cancer for Whole Genome, Whole Exome and Comprehensive Panel Sequencing.

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.

Computational immunogenomic approaches to predict response to cancer immunotherapies.

Cancer immunogenomics is an emerging field that bridges genomics and immunology. The establishment of large-scale genomic collaborative efforts along with the development of new single-cell transcriptomic techniques and multi-omics approaches have enabled characterization of the mutational and transcriptional profiles of many cancer types and helped to identify clinically actionable alterations as well as predictive and prognostic biomarkers. Researchers have developed computational approaches and machine learning algorithms to accurately obtain clinically useful information from genomic and transcriptomic sequencing data from bulk tissue or single cells and explore tumours and their microenvironment. The rapid growth in sequencing and computational approaches has resulted in the unmet need to understand their true potential and limitations in enabling improvements in the management of patients with cancer who are receiving immunotherapies. In this Review, we describe the computational approaches currently available to analyse bulk tissue and single-cell sequencing data from cancer, stromal and immune cells, as well as how best to select the most appropriate tool to address various clinical questions and, ultimately, improve patient outcomes.

Discrepancies in tumor mutation burden reporting from sequential endobronchial ultrasound transbronchial needle aspiration samples within single lymph node stations - brief report.

Introduction: Tumour 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. Methods: Individual 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). Results: Twenty 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. Conclusion: TMB 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.

The oesophageal adenocarcinoma tumour immune microenvironment dictates outcomes with different modalities of neoadjuvant therapy - results from the AGITG DOCTOR trial and the cancer evolution biobank.

A plateau in treatment effect can be seen for the current 'one-size-fits-all' approach to oesophageal adenocarcinoma (OAC) management using neoadjuvant chemoradiotherapy (nCRT) or chemotherapy (nCT). In OAC, the tumour microenvironment (TME) is largely immunosuppressed, however a subgroup of patients with an immune-inflamed TME exist and show improved outcomes. We aimed to understand the overall immune-based mechanisms underlying treatment responses and patient outcomes in OAC, and in relation to neoadjuvant therapy modality. This study included 107 patients; 68 patients were enrolled in the Australian Gastro-Intestinal Trials Group sponsored DOCTOR Trial, and 38 patients were included from the Cancer Evolution Biobank. Matched pre-treatment and post-treatment tumour biopsies were used to perform multi-modality analysis of the OAC TME including NanoString mRNA expression analysis, multiplex and single colour immunohistochemistry (IHC), and peripheral blood mononuclear cell analysis of tumour-antigen specific T cell responses. Patients with the best clinicopathological outcomes and survival had an immune-inflamed TME enriched with anti-tumour immune cells and pathways. Those with the worst survival showed a myeloid T regulatory cell enriched TME, with decreased CD8+ cell infiltration and increased pro-tumour immune cells. Multiplex IHC analysis identified that high intra-tumoural infiltration of CD8+ cells, and low infiltration with CD163+ cells was associated with improved survival. High tumour core CD8+ T cell infiltration, and a low tumour margin infiltration of CD163+ cells was also associated with improved survival. nCRT showed improved survival compared with nCT for patients with low CD8+, or high CD163+ cell infiltration. Poly-functional T cell responses were seen with tumour-antigen specific T cells. Overall, our study supports the development of personalised therapeutic approaches based on the immune microenvironment in OAC. Patients with an immune-inflamed TME show favourable outcomes regardless of treatment modality. However, in those with an immunosuppressed TME with CD163+ cell infiltration, treatment with nCRT can improve outcomes. Our findings support previous studies into the TME of OAC and with more research, immune based biomarker selection of treatment modality may lead in improved outcomes in this deadly disease.

The clinical utility and costs of whole-genome sequencing to detect cancer susceptibility variants-a multi-site prospective cohort study.

BACKGROUND: Many families and individuals do not meet criteria for a known hereditary cancer syndrome but display unusual clusters of cancers. These families may carry pathogenic variants in cancer predisposition genes and be at higher risk for developing cancer. METHODS: This multi-centre prospective study recruited 195 cancer-affected participants suspected to have a hereditary cancer syndrome for whom previous clinical targeted genetic testing was either not informative or not available. To identify pathogenic disease-causing variants explaining participant presentation, germline whole-genome sequencing (WGS) and a comprehensive cancer virtual gene panel analysis were undertaken. RESULTS: Pathogenic variants consistent with the presenting cancer(s) were identified in 5.1% (10/195) of participants and pathogenic variants considered secondary findings with potential risk management implications were identified in another 9.7% (19/195) of participants. Health economic analysis estimated the marginal cost per case with an actionable variant was significantly lower for upfront WGS with virtual panel ($8744AUD) compared to standard testing followed by WGS ($24,894AUD). Financial analysis suggests that national adoption of diagnostic WGS testing would require a ninefold increase in government annual expenditure compared to conventional testing. CONCLUSIONS: These findings make a case for replacing conventional testing with WGS to deliver clinically important benefits for cancer patients and families. The uptake of such an approach will depend on the perspectives of different payers on affordability.

Performance of tumour microenvironment deconvolution methods in breast cancer using single-cell simulated bulk mixtures.

Cells within the tumour microenvironment (TME) can impact tumour development and influence treatment response. Computational approaches have been developed to deconvolve the TME from bulk RNA-seq. Using scRNA-seq profiling from breast tumours we simulate thousands of bulk mixtures, representing tumour purities and cell lineages, to compare the performance of nine TME deconvolution methods (BayesPrism, Scaden, CIBERSORTx, MuSiC, DWLS, hspe, CPM, Bisque, and EPIC). Some methods are more robust in deconvolving mixtures with high tumour purity levels. Most methods tend to mis-predict normal epithelial for cancer epithelial as tumour purity increases, a finding that is validated in two independent datasets. The breast cancer molecular subtype influences this mis-prediction. BayesPrism and DWLS have the lowest combined numbers of false positives and false negatives, and have the best performance when deconvolving granular immune lineages. Our findings highlight the need for more single-cell characterisation of rarer cell types, and suggest that tumour cell compositions should be considered when deconvolving the TME.

Circulating Tumor DNA: A Promising Biomarker for Predicting Recurrence in Patients with BRAF-Negative Melanoma.

For patients with BRAF wild-type stage III and IV melanoma, there is an urgent clinical need to identify prognostic biomarkers and biomarkers predictive of treatment response. Circulating tumor DNA (ctDNA) is emerging as a blood-based biomarker and has shown promising results for many cancers, including melanoma. The purpose of this study was to identify targetable, tumor-derived mutations in patient blood that may lead to treatment alternatives and improved outcomes for patients with BRAF-negative melanoma. Using a CAncer Personalized Profiling by deep Sequencing (CAPP-seq) pan-cancer gene panel, ctDNA from 150 plasma samples (n = 106 patients) was assessed, including serial blood collections for a subset of patients (n = 16). ctDNA variants were detected in 85% of patients, all in targetable pathways, such as vascular endothelial growth factor receptor, epidermal growth factor receptor, phosphatidylinositol 3-kinase/AKT, Bcl2/mammalian target of rapamycin (mTOR), ALK/MET, and cyclin-dependent kinase 4/6. Patients with stage IV melanoma with low ctDNA concentrations, <10 ng/mL, had significantly better disease-specific survival and progression-free survival. Patients with both a high concentration of ctDNA and any detectable ctDNA variants had the worst prognosis. In addition, these results indicated that longitudinal changes in ctDNA correlated with treatment response and disease progression determined by radiology. This study confirms that ctDNA may be used as a noninvasive liquid biopsy to identify recurrent disease and detect targetable variants in patients with late-stage melanoma.

C-reactive protein is a prognostic biomarker in pancreatic ductal adenocarcinoma patients.

AIM: The 5-year survival rate of pancreatic ductal adenocarcinoma (PDAC) is approximately 11% and has only improved marginally over the last three decades. For operable PDAC, resection and adjuvant FOLFIRINOX chemotherapy is standard of care. There is growing interest in perioperative regimens to improve outcomes. The non-randomized Phase II study "Gemcitabine and Abraxane for resectable Pancreatic cancer" (GAP) demonstrated the feasibility of perioperative gemcitabine/abraxane. Long-term survival in PDAC requires an effective immune response; hence, we undertook this translational study of the GAP trial cohort to identify immune-oncology biomarkers for clinical use. METHODS: We combined Nanostring nCounter technology with immunohistochemistry to investigate the correlation between gene expression and overall patient survival. Findings were investigated in samples from the International Cancer Genome Consortium (ICGC, n = 88) and the Australian Pancreatic Genome Initiative (APGI, n = 227). RESULTS: We confirmed that human equilibrative nucleoside transporter 1 (hENT1) expression was not a prognostic marker in PDAC but patients with high levels of hENT1 were more likely to live longer than 24 months post-surgery. Additionally, CD274 (PD-L1) and two novel biomarkers of survival, cathepsin W (CTSW) and C-reactive protein (CRP), were identified in the GAP cohort (n = 19). CRP expression was confirmed in data from the ICGC. Although PD-L1 and CTSW proteins were not significant across all three cohorts, results show that low CRP mRNA and protein expression are associated with longer overall survival in all three patient groups. CONCLUSION: PDAC patients with long survival have higher hENT1 expression levels. Furthermore, CRP expression is a biomarker of poor prognosis following perioperative chemotherapy and resection in PDAC patients and thus may be useful for identifying patients who could benefit from more aggressive adjuvant strategies.

Whole Genome Sequencing in Advanced Lung Cancer can be Performed Using Diff-Quik Cytology Smears Derived from Endobronchial Ultrasound, Transbronchial Needle Aspiration (EBUS TBNA).

INTRODUCTION: Maximising alternative sample types for genomics in advanced lung cancer is important because bronchoscopic samples may sometimes be insufficient for this purpose. Further, the clinical applications of comprehensive molecular analysis such as whole genome sequencing (WGS) are rapidly developing. Diff-Quik cytology smears from EBUS TBNA is an alternative source of DNA, but its feasibility for WGS has not been previously demonstrated. METHODS: Diff-Quik smears were collected along with research cell pellets. RESULTS: Tumour content of smears were compared to research cell pellets from 42 patients, which showed good correlation (Spearman correlation 0.85, P < 0.0001). A subset of eight smears underwent WGS, which presented similar mutation profiles to WGS of the matched cell pellet. DNA yield was predicted using a regression equation of the smears cytology features, which correctly predicted DNA yield > 1500 ng in 7 out of 8 smears. CONCLUSIONS: WGS of commonly collected Diff-Quik slides is feasible and their DNA yield can be predicted.

Generalising uncertainty improves accuracy and safety of deep learning analytics applied to oncology.

Uncertainty estimation is crucial for understanding the reliability of deep learning (DL) predictions, and critical for deploying DL in the clinic. Differences between training and production datasets can lead to incorrect predictions with underestimated uncertainty. To investigate this pitfall, we benchmarked one pointwise and three approximate Bayesian DL models for predicting cancer of unknown primary, using three RNA-seq datasets with 10,968 samples across 57 cancer types. Our results highlight that simple and scalable Bayesian DL significantly improves the generalisation of uncertainty estimation. Moreover, we designed a prototypical metric-the area between development and production curve (ADP), which evaluates the accuracy loss when deploying models from development to production. Using ADP, we demonstrate that Bayesian DL improves accuracy under data distributional shifts when utilising 'uncertainty thresholding'. In summary, Bayesian DL is a promising approach for generalising uncertainty, improving performance, transparency, and safety of DL models for deployment in the real world.

Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy.

Oesophageal adenocarcinoma is a poor prognosis cancer and the molecular features underpinning response to treatment remain unclear. We investigate whole genome, transcriptomic and methylation data from 115 oesophageal adenocarcinoma patients mostly from the DOCTOR phase II clinical trial (Australian New Zealand Clinical Trials Registry-ACTRN12609000665235), with exploratory analysis pre-specified in the study protocol of the trial. We report genomic features associated with poorer overall survival, such as the APOBEC mutational and RS3-like rearrangement signatures. We also show that positron emission tomography non-responders have more sub-clonal genomic copy number alterations. Transcriptomic analysis categorises patients into four immune clusters correlated with survival. The immune suppressed cluster is associated with worse survival, enriched with myeloid-derived cells, and an epithelial-mesenchymal transition signature. The immune hot cluster is associated with better survival, enriched with lymphocytes, myeloid-derived cells, and an immune signature including CCL5, CD8A, and NKG7. The immune clusters highlight patients who may respond to immunotherapy and thus may guide future clinical trials.

Evaluating Diff-Quik cytology smears for large-panel mutation testing in lung cancer-Predicting DNA content and success with low-malignant-cellularity samples.

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.

Australian Genomics: Outcomes of a 5-year national program to accelerate the integration of genomics in healthcare.

Australian Genomics is a national collaborative partnership of more than 100 organizations piloting a whole-of-system approach to integrating genomics into healthcare, based on federation principles. In the first five years of operation, Australian Genomics has evaluated the outcomes of genomic testing in more than 5,200 individuals across 19 rare disease and cancer flagship studies. Comprehensive analyses of the health economic, policy, ethical, legal, implementation and workforce implications of incorporating genomics in the Australian context have informed evidence-based change in policy and practice, resulting in national government funding and equity of access for a range of genomic tests. Simultaneously, Australian Genomics has built national skills, infrastructure, policy, and data resources to enable effective data sharing to drive discovery research and support improvements in clinical genomic delivery.

Efficient detection and monitoring of pediatric brain malignancies with liquid biopsy based on patient-specific somatic mutation screening.

BACKGROUND: Brain cancer is the leading cause of cancer-related death in children. Early detection and serial monitoring are essential for better therapeutic outcomes. Liquid biopsy has recently emerged as a promising approach for detecting these tumors by screening body fluids for the presence of circulating tumor DNA (ctDNA). Here we tested the limits of liquid biopsy using patient-specific somatic mutations to detect and monitor primary and metastatic pediatric brain cancer. METHODS: Somatic mutations were identified in 3 ependymoma, 1 embryonal tumor with multilayered rosettes, 1 central nervous system neuroblastoma, and 7 medulloblastoma patients. The mutations were used as liquid biomarkers for serial assessment of cerebrospinal fluid (CSF) samples using a droplet digital PCR (ddPCR) system. The findings were correlated to the imaging data and clinical assessment to evaluate the utility of the approach for clinical translation. RESULTS: We developed personalized somatic mutation ddPCR assays which we show are highly specific, sensitive, and efficient in detection and monitoring of ctDNA, with a positive correlation between presence of ctDNA, disease course, and clinical outcomes in the majority of patients. CONCLUSIONS: We demonstrate the feasibility and clinical utility of personalized mutation-based liquid biopsy for the surveillance of brain cancer in children. However, even with this specific and sensitive approach, we identified some potential false negative analyses. Overall, our results indicate that changes in ctDNA profiles over time demonstrate the great potential of our specific approach for predicting tumor progression, burden, and response to treatment.

Intratumoral CD16+ Macrophages Are Associated with Clinical Outcomes of Patients with Metastatic Melanoma Treated with Combination Anti-PD-1 and Anti-CTLA-4 Therapy.

PURPOSE: This study characterizes intratumoral macrophage populations within baseline melanoma biopsies from patients with advanced melanoma who received either anti-PD-1 monotherapy or a combination with anti-CTLA-4. Particularly, FcγRIIIa (CD16)-expressing macrophage densities were investigated for associations with response and progression-free survival. EXPERIMENTAL DESIGN: Patients with advanced melanoma who received either anti-PD-1 monotherapy or combination anti-PD-1 and anti-CTLA-4 were retrospectively identified. Macrophage populations were analyzed within baseline melanoma biopsies via multiplex IHC in relation to treatment outcomes. RESULTS: Patients who responded to combination immune checkpoint inhibitor contained higher CD16+ macrophage densities than those who did not respond (196 vs. 7 cells/mm2; P = 0.0041). There was no diffidence in CD16+ macrophage densities in the PD-1 monotherapy-treated patients based on response (118 vs. 89 cells/mm2; P = 0.29). A significantly longer 3-year progression-free survival was observed in combination-treated patients with high intratumoral densities of CD16+ macrophages compared with those with low densities (87% vs. 42%, P = 0.0056, n = 40). No association was observed in anti-PD-1 monotherapy-treated patients (50% vs. 47%, P = 0.4636, n = 50). Melanoma biopsies with high densities of CD16+ macrophages contained upregulated gene expression of critical T-cell recruiting chemokines (CXCL9, CXCL10, and CXCL11). CONCLUSIONS: Our data demonstrate that tumor microenvironments enriched with CD16+ macrophages are favorable for response to combination anti-PD-1 and anti-CTLA-4 therapy but not anti-PD-1 monotherapy. These data provides a potential biomarker of response for combination immunotherapies in patients with metastatic melanoma. See related commentary by Smithy and Luke, p. 2345.