Metastasis is the main cause of cancer death, yet the evolutionary processes behind it remain largely unknown. Here, through analysis of large panel-based genomic datasets from the AACR GENIE project, including 40,979 primary and metastatic tumors across 25 distinct cancer types, we explore how the evolutionary pressure of cancer metastasis shapes the selection of genomic drivers of cancer. The most commonly affected genes were TP53, MYC, and CDKN2A, with no specific pattern associated with metastatic disease. This suggests that, on a driver mutation level, the selective pressure operating in primary and metastatic tumors is similar. The most highly enriched individual driver mutations in metastatic tumors were mutations known to drive resistance to hormone therapies in breast and prostate cancer (ESR1 and AR), anti-EGFR therapy in non-small cell lung cancer (EGFR T790M), and imatinib in gastrointestinal cancer (KIT V654A). Specific mutational signatures were also associated with treatment in three cancer types, supporting clonal selection following anti-cancer therapy. Overall, this implies that initial acquisition of driver mutations is predominantly shaped by the tissue of origin, where specific mutations define the developing primary tumor and drive growth, immune escape, and tolerance to chromosomal instability. However, acquisition of driver mutations that contribute to metastatic disease is less specific, with the main genomic drivers of metastatic cancer evolution associating with resistance to therapy.

Cancer metastasis is the lethal developmental step in cancer, responsible for the majority of cancer deaths. To metastasise, cancer cells must acquire the ability to disseminate systemically and to escape an activated immune response. Here, we endeavoured to investigate if metastatic dissemination reflects acquisition of genomic traits that are selected for. We acquired mutation and copy number data from 8332 tumours representing 19 cancer types acquired from The Cancer Genome Atlas and the Hartwig Medical Foundation. A total of 827,344 non-synonymous mutations across 8332 tumour samples representing 19 cancer types were timed as early or late relative to copy number alterations, and potential driver events were annotated. We found that metastatic cancers had a significantly higher proportion of clonal mutations and a general enrichment of early mutations in p53 and RTK/KRAS pathways. However, while individual pathways demonstrated a clear time-separated preference for specific events, the relative timing did not vary between primary and metastatic cancers. These results indicate that the selective pressure that drives cancer development does not change dramatically between primary and metastatic cancer on a genomic level, and is mainly focused on alterations that increase proliferation.

Immunotherapy has revolutionized treatment of patients diagnosed with metastatic melanoma, where nearly half of patients receive clinical benefit. However, immunotherapy is also associated with immune-related adverse events, which may be severe and persistent. It is therefore important to identify patients that do not benefit from therapy early. Currently, regularly scheduled CT scans are used to investigate size changes in target lesions to evaluate progression and therapy response. This study aims to explore if panel-based analysis of circulating tumor DNA (ctDNA) taken at 3-week intervals may provide a window into the growing cancer, can be used to identify nonresponding patients early, and determine genomic alterations associated with acquired resistance to checkpoint immunotherapy without analysis of tumor tissue biopsies. We designed a gene panel for ctDNA analysis and sequenced 4–6 serial plasma samples from 24 patients with unresectable stage III or IV melanoma and treated with first-line checkpoint inhibitors enrolled at the Department of Oncology at Aarhus University Hospital, Denmark. TERT was the most mutated gene found in ctDNA and associated with a poor prognosis. We detected more ctDNA in patients with high metastatic load, which indicates that more aggressive tumors release more ctDNA into the bloodstream. Although we did not find evidence of specific mutations associated with acquired resistance, we did demonstrate in this limited cohort of 24 patients that untargeted, panel-based ctDNA analysis has the potential to be used as a minimally invasive tool in clinical practice to identify patients where the benefits of immunotherapy outweigh the drawbacks.

Immunotherapy has revolutionised cancer treatment. However, not all cancer patients benefit, and current stratification strategies based primarily on PD1 status and mutation burden are far from perfect. We hypothesised that high activation of an innate response relative to the adaptive response may prevent proper tumour neoantigen identification and decrease the specific anticancer response, both in the presence and absence of immunotherapy. To investigate this, we obtained transcriptomic data from three large publicly available cancer datasets, the Cancer Genome Atlas (TCGA), the Hartwig Medical Foundation (HMF), and a recently published cohort of metastatic bladder cancer patients treated with immunotherapy. To analyse immune infiltration into bulk tumours, we developed an RNAseq-based model based on previously published definitions to estimate the overall level of infiltrating innate and adaptive immune cells from bulk tumour RNAseq data. From these, the adaptive-to-innate immune ratio (A/I ratio) was defined. A meta-analysis of 32 cancer types from TCGA overall showed improved overall survival in patients with an A/I ratio above median (Hazard ratio (HR) females 0.73, HR males 0.86, P < 0.05). Of particular interest, we found that the association was different for males and females for eight cancer types, demonstrating a gender bias in the relative balance of the infiltration of innate and adaptive immune cells. For patients with metastatic disease, we found that responders to immunotherapy had a significantly higher A/I ratio than non-responders in HMF (P = 0.036) and a significantly higher ratio in complete responders in a separate metastatic bladder cancer dataset (P = 0.022). Overall, the adaptive-to-innate immune ratio seems to define separate states of immune activation, likely linked to fundamental immunological reactions to cancer. This ratio was associated with improved prognosis and improved response to immunotherapy, demonstrating potential relevance to patient stratification. Furthermore, by demonstrating a significant difference between males and females that associates with response, we highlight an important gender bias which likely has direct clinical relevance.

Immunotherapy has revolutionized cancer treatment. However, not all cancer patients benefit, and current stratification strategies based primarily on PD1 status and mutation burden is far from perfect. We hypothesized that high activation of an innate response relative to the adaptive response may prevent proper tumor neoantigen identification and decrease the specific anticancer response, both in the presence and absence of immunotherapy. To investigate this, we defined signatures of innate and adaptive immune response from bulk tumor RNAseq data, and compared the relative activation of both immune compartments. We acquired publicly available transcriptomic data from both primary and metastatic cancer cohorts from the Cancer Genome Atlas (TCGA), the Hartwig Medical Foundation (HMF), and from a recently published cohort of metastatic bladder cancer patients treated with immunotherapy. To analyse adaptive and innate immune infiltration into bulk tumors, we developed a model to estimate the overall level of innate and adaptive immune cells, based on previously published definitions. From these, we defined the overall adaptive-to-innate immune ratio (AIR) score as the ratio of average gene expression of genes associated with the adaptive and innate immune system, respectively. Pan-cancer analysis of primary tumor samples from TCGA showed improved progression free survival in patients with an AIR score above median (P &lt; 0.0001), and that patients without a progression event had overall a significantly higher AIR score (P &lt; 2*10-16). Interestingly, we found that the association was different for males and females for several cancer types, indicating a potential a gender bias in activation of the immune response (female P &lt; 2*10-16, male P = 1.1*10-14). For patients with metastatic disease, we found that responders to immunotherapy have a significantly higher AIR score than non-responders in HMF (female P = 0.0037, male P = 2.5*10-5) and a significantly higher score in complete responders in a separate metastatic bladder cancer dataset where response was primarily observed in male patients (P = 0.015). Furthermore, histological analysis revealed that tumors which had a significantly higher AIR score, were highly infiltrated by immune cells (P = 0.00047), providing orthogonal support that the AIR score associates with an anti-tumor immune response. Overall, the adaptive-to-innate immune ratio seems to define separate states of immune activation, likely linked to fundamental immunological reactions to cancer. Our score associates with both improved prognosis and improved response to immunotherapy, demonstrating potential use in patient stratification. Furthermore, by demonstrating a significant difference between males and females that associates with response, we highlight an important gender bias which likely has direct clinical relevance. Citation Format: Johanne Ahrenfeldt, Andreas B. Østergaard, Ditte S. Christensen, Judit Kisistók, Mateo Sokač, Nicolai J. Birkbak. High relative ratio of adaptive to innate tumor infiltrating immune cells predicts for immunotherapy response and associates with improved prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2724.

Metastatic disease is responsible for 90% of all cancer deaths. Understanding the process of how primary tumors achieve metastatic potential is of great importance and paramount to the development of precision medicine that may limit the aggressive distant spread of metastatic cancer. It is hypothesized that during cancer evolution, cells within the primary tumor obtain metastatic potential through acquisition of specific somatic alterations. However, the defining ability that allows metastasis remains unknown. By comparing genomic profiles of primary and metastatic cancers we wish to investigate if potential metastatic gate-keeper mutations exist, defined as alterations to individual genes or pathways that are required to facilitate metastatic dissemination.Here, we analyzed panel-based DNA sequencing datasets from the GENIE (Genomics Evidence Neoplasia Information Exchange) project, version 9.0. Analyses were performed on 174 shared cancer genes selected to include as many patients as possible while analyzing as many genes as possible. In total 39,036 patients had mutations or copy number alterations in one or more of the 174 shared genes across 25 different cancer types. Using bioinformatic tools, we compared genomic alterations in primary versus metastatic samples. Metastatic samples harbor a higher tumor mutation burden and increased levels of chromosomal instability. However, while we found a higher total level of driver mutations in metastatic samples, these appear primarily driven by a higher mutation burden, and corrected for this, we found a significantly lower level of drivers compared to primary. Overall, phylogenetic analysis showed that primary and metastatic samples clustered together by cancer type. Comparing two logistic regressions models, which was corrected for tumor mutation burden and genomic instability, we found that despite most genes show a relatively low difference in frequency between primary and metastatic disease, 55 of the 174 genes in this panel showed a small but significant overrepresentation in at least one cancer type in either primary or metastatic disease.With this analysis we demonstrate how the power of large datasets can be utilized to make novel inferences on cancer biology. We observed significant enrichment in overall mutation counts and copy number alterations in metastatic samples. However, we found limited genomic differences between primary and metastatic cancer within the same cancer types. This might suggest that acquisition of cancer driver mutations are initially mostly shaped by the tissue of origin where specific cancer driver mutations define the developing primary tumor, while acquisition of driver mutations that contribute to metastatic disease are less specific. It might indicate that the metastatic process is driven less by newly acquired metastatic features, but more by non-cancer features such as inflammation in the surrounding tissue. Citation Format: Ditte Sigaard Christensen, Johanne Ahrenfeldt, Mateo Sokač, Judit Kisistók, Nicholas McGranahan, Nicolai Juul Birkbak. Distinct aggressive biology drives the evolution of metastatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2186.

Immunotherapy has revolutionised cancer treatment. However, not all cancer patients benefit, and current stratification strategies based primarily on PD1 status and mutation burden is far from perfect. We hypothesised that high activation of an innate response relative to the adaptive response may prevent proper tumour neoantigen identification and decrease the specific anticancer response, both in the presence and absence of immunotherapy. To investigate this, we obtained transcriptomic data from three large publicly available cancer datasets, the Cancer Genome Atlas (TCGA), the Hartwig Medical Foundation (HMF), and a recently published cohort of metastatic bladder cancer patients treated with immunotherapy. To analyse immune infiltration into bulk tumours, we developed an RNAseq-based model based on previously published definitions to estimate the overall level of infiltrating innate and adaptive immune cells from bulk tumour RNAseq data. From these, the adaptive-to-innate immune ratio (A/I ratio) was defined. A meta-analysis of 32 cancer types from TCGA overall showed improved overall survival in patients with an A/I ratio above median (Hazard ratio (HR) females 0.73, HR males 0.86, P < 0.05). Of particular interest, we found that the association was different for males and females for eight cancer types, demonstrating a gender bias in the relative balance of the infiltration of innate and adaptive immune cells. For patients with metastatic disease, we found that responders to immunotherapy had a significantly higher A/I ratio than non-responders in HMF (P = 0.036) and a significantly higher ratio in complete responders in a separate metastatic bladder cancer dataset (P = 0.022). Overall, the adaptive-to-innate immune ratio seems to define separate states of immune activation, likely linked to fundamental immunological reactions to cancer. This ratio was associated with improved prognosis and improved response to immunotherapy, demonstrating potential relevance to patient stratification. Furthermore, by demonstrating a significant difference between males and females that associates with response, we highlight an important gender bias which likely has direct clinical relevance.

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