Patients who undergo Epstein-Barr virus (EBV) seromismatch (D+/R−) transplants have a higher risk for the development of post-transplant lymphoproliferative disorder (PTLD). Adult renal transplant recipients at a single institution were prospectively monitored for EBV during the first year post-transplant. Over a 2-year period, 34 patients (7.78%) were identified as being EBV D+/R− recipients. Patients who developed symptoms or had persistent viremia were pre-emptively administered rituximab. Six recipients were discharged without monitoring on the protocol. Of those six, three (50%) developed PTLD and all three lost their grafts. Twenty (60.6%) of the 34 recipients developed viremia during the first year post-transplant. Of the recipients who became viremic, six (30%) received rituximab. None of the six who received rituximab-developed PTLD. We found that recipients who were not monitored on the protocol were more likely to have PTLD and graft loss compared to those who were (p = 0.008). Post-transplant monitoring of adults who undergo EBV D+/R− kidney transplants for viremia and symptoms associated with EBV infection may prompt intervention which reduces the incidence of PTLD within the first year. Use of rituximab in preventing PTLD among patients with primary EBV infection requires further prospective study to determine its overall safety and efficacy.

The microbiome affects cancer, from carcinogenesis to response to treatments. New evidence suggests that microbes are also present in many tumors, though the scope of how they affect tumor biology and clinical outcomes is unclear. A broad survey of tumor microbiome samples across several independent datasets is needed to identify robust correlations for follow-up testing. We created a tool to carefully identify the tumor microbiome within RNAseq datasets and then applied it to samples collected through the Oncology Research Information Exchange Network (ORIEN) and The Cancer Genome Atlas (TCGA). We showed how the processing removes contaminants and batch effects to yield microbe abundances consistent with non-high-throughput sequencing-based approaches. We sought to establish clinical relevance by correlating the microbe abundances with various clinical and tumor measurements, such as age and tumor hypoxia. This process leveraged the two datasets and raised up only the concordant (significant and in the same direction) associations. We identify associations with survival and clinical variables that are highly cancer-specific, and relatively few associations with immune composition. Finally, we explore potential mechanisms by which microbes and tumors may interact using a network approach. Alistipes, a common gut commensal, showed the highest network degree centrality and was associated with genes related to metabolism and inflammation. The exotic tool can support discovery of microbes in tumors in a way that leverages the many existing and growing number of RNAseq datasets.

BackgroundImmune checkpoint inhibitor therapy, or ICI, is currently the most successful treatment option for patients with renal cell carcinoma (RCC). However, only 20% of patients have a durable response,1 driving a significant need to improve treatment outcomes. The tumor microbiome has recently been shown to play a role in chemotherapy-based treatment outcomes, but, to our knowledge, no study has explored its role in response to ICIs.2–4MethodsTumor samples were collected from 22 patients with RCC as a part of the Total Cancer Care program at The Ohio State University Comprehensive Cancer Center. Raw RNA-seq reads from these biopsies, as well as data on the responses to ICI therapy were collected. Response evaluation was based on RECIST v1.1 criteria with complete or partial response, or stable disease classified as ”Responders,”, and progressive disease classified as ”Non-responsders”. The RNA-seq reads were processed through a pipeline developed by the Spakowicz lab, known as ExoTIC (Exogenous sequences in Tumor and Immune Cells), to carefully identify exogenous sequences.5 6 Reads that don’t align to the human reference genome are meticulously filtered of (1) common laboratory contaminants, (2) taxa that inversely correlate with input RNA quantity, and (3) taxa commonly found in the negative controls of microbiome experiments. DESeq2 was used to perform a differential abundance analysis on the comparison groups at every taxonomic level.ResultsThe 22 patients with RCC range from 22 to 74 years of age at diagnosis, are 72.7% male, and 54.5% responded to ICIs. Exogenous taxa are identified in the tumor RNAseq, including bacteria, fungi, and viruses (figure 1). Within the tumors responsive to immunotherapy, there was found to be a significant enrichment of certain microbial species, including Bacillus thuringiensis, Comamonas testosteroni, Colletotrichum higginsianum, and Elaeis guineesis. Comparatively, the cohort of non-responsive tumors was found to have a significant enrichment of Candidatus Promineofilum breve, Clostridioides difficile, Nocardia cyriacigeorgica, Streptomyces sp. CdTB01, and Streptomyces venezuelae (figure 2).Abstact 942 Figure 1Relative abundances of exogenous taxa found in tumor RNAseq are shown in a stacked bar plotAbstact 942 Figure 2Differential abundance analysis of taxa found within tumor RNAseq data by the exotic pipeline. Colored points represent significantly (pvalue < 0.05) enriched taxa with a high (>2.5) fold-difference in abundance between the groupsConclusionsWe found that prior to ICI treatment the tumor microbiome of patients with RCC whose tumors responded to immunotherapy vary from those that did not respond to treatment. This implies that a therapeutic target to modify the tumor microbiome to improve treatment outcomes. Future research will evaluate whether these correlations are causally associated with outcomes and will evaluate their effect on the tumor microenvironment including immune cell infiltration.AcknowledgementsThe authors acknowledge the support and resources of the Ohio Supercomputing Center (PAS1695).ReferencesCiccarese C, Di Nunno V, Iacovelli R, Massari F. Future perspectives for personalized immunotherapy in renal cell carcinoma. Expert opinion on biological therapy. Taylor & Francis. 2017;17(9):1049–1052.Geller LT, Barzily-Rokni M, Danino T, Jonas OH, Shental N, Nejman D, Gavert N, Zwang Y, Cooper ZA, Shee K, Thaiss CA, Reuben A, Livny J, Avraham R, Frederick DT, Ligorio M, Chatman K, Johnston SE, Mosher CM, Brandis A, Fuks G, Gurbatri C, Gopalakrishnan V, Kim M, Hurd MW, Katz M, Fleming J, Maitra A, Smith DA, Skalak M, Bu J, Michaud M, Trauger SA, Barshack I, Golan T, Sandbank J, Flaherty KT, Mandinova A, Garrett WS, Thayer SP, Ferrone CR, Huttenhower C, Bhatia SN, Gevers D, Wargo JA, Golub TR, Straussman R. Potential role of intratumor bacteria in mediating tumor resistance to the chemotherapeutic drug gemcitabine. Science 2017 September 15;357(6356):1156–1160. PMID: 28912244.Nejman D, Livyatan I, Fuks G, Gavert N, Zwang Y, Geller LT, Rotter-Maskowitz A, Weiser R, Mallel G, Gigi E, Meltser A, Douglas GM, Kamer I, Gopalakrishnan V, Dadosh T, Levin-Zaidman S, Avnet S, Atlan T, Cooper ZA, Arora R, Cogdill AP, Khan MAW, Ologun G, Bussi Y, Weinberger A, Lotan-Pompan M, Golani O, Perry G, Rokah M, Bahar-Shany K, Rozeman EA, Blank CU, Ronai A, Shaoul R, Amit A, Dorf-man T, Kremer R, Cohen ZR, Harnof S, Siegal T, Yehuda-Shnaidman E, Gal-Yam EN, Shapira H, Baldini N, Langille MGI, Ben-Nun A, Kaufman B, Nissan A, Golan T, Dadiani M, Levanon K, Bar J, Yust-Katz S, Barshack I, Peeper DS, Raz DJ, Segal E, Wargo JA, Sandbank J, Shental N, Straussman R. The human tumor microbiome is composed of tumor type–specific intracellular bacteria. Science 2020 May 29;368(6494):973–980.Poore GD, Kopylova E, Zhu Q, Carpenter C, Fraraccio S, Wandro S, Kosciolek T, Janssen S, Metcalf J, Song SJ, Kanbar J, Miller-Montgomery S, Heaton R, Mckay R, Patel SP, Swafford AD, Knight R. Microbi-ome analyses of blood and tissues suggest cancer diagnostic approach. Nature 2020;579(7800):567–574. PMID: 32214244.Malalur, Pannaga, Mo, Xiaokui, Hoyd, Rebecca, Hays, John, Carbone, David, Spakowicz, Daniel. Investigating intra-tumor microbes, blood microbes, and CEA for development of non-invasive biomarkers in colorectal cancer. Journal of Clinical Oncology 2021;39(15_suppl): 3551–3551.Malalur PG, Mo X, Hoyd R, Carbone DP, Spakowicz D. Intra-tumoral microbes and overall survival in colorectal cancer patients. Journal of Clinical Oncology 2020;38(15_suppl):4083–4083.Ethics ApprovalData were obtained through an IRB-approved Honest Broker protocol (2015H0185) supporting the Total Cancer Care protocol 2013H0199.

1311 Figure 1 A stacked bar plot showing the relative abundances of exogenous taxa found in tumor RNAseq. Taxa are shown on the phylum level and are ordered by the relative abundance of < i >Uroviricota Abstract 1311 Figure 2 Differential abundance analysis of taxa found within tumor RNAseq data by the exotic pipeline. Colored points represent significantly (p-value < 0.05) enriched taxa with a high (>1.00) fold-difference in abundance between the groups