Chemotherapy weakly contributes to predicted neoantigen expression in ovarian cancer

addressref=aff1]Timothy O’Donnell addressref=aff2]Elizabeth L. Christie addressref=aff1]Arun Ahuja addressref=aff1]Jacqueline Buros addressref=aff1]B. Arman Aksoy addressref=aff2]David D. L. Bowtell addressref=aff3]Alexandra Snyderthanks: addressref=aff1]Jeff Hammerbacherthanks:


[id=aff1]Mount Sinai School of Medicine, New York, USA \address[id=aff2]Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Australia \address[id=aff3]Deptartment of Medicine, Memorial Sloan-Kettering Cancer Center, Weill Cornell Medical College, New York, USA



Patients with highly mutated tumors, such as melanoma or smoking-related lung cancer, have higher rates of response to immune checkpoint blockade therapy, perhaps due to increased neoantigen expression. Many chemotherapies including platinum compounds are known to be mutagenic, but the impact of standard treatment protocols on mutational burden and resulting neoantigen expression in most human cancers is unknown.


We sought to quantify the effect of chemotherapy treatment on computationally predicted neoantigen expression for 12 high grade serous ovarian carcinoma (HGSC) patients with pre- and post-chemotherapy samples collected in the Australian Ovarian Cancer Study. We additionally analyzed 16 patients from the cohort with post-treatment samples only, including five primary surgical samples exposed to neoadjuvant chemotherapy. Our approach integrates tumor whole genome and RNA sequencing with class I MHC binding prediction and mutational signatures of chemotherapy exposure extracted from two preclinical studies.


The mutational signatures for cisplatin and cyclophosphamide identified in a preclinical model had significant but inexact associations with the relevant exposure in the clinical samples. In an analysis stratified by tissue type (solid tumor or ascites), relapse samples collected after chemotherapy harbored a median of 90% more expressed neoantigens than untreated primary samples, a figure that combines the effects of chemotherapy and other mutagenic processes operative during relapse. Neoadjuvant-treated primary samples showed no detectable increase over untreated samples. The contribution from chemotherapy-associated signatures was small, accounting for a mean of 5% (range 0–16) of the expressed neoantigen burden in relapse samples. In both treated and untreated samples, most neoantigens were attributed to COSMIC Signature (3), associated with BRCA disruption, Signature (1), associated with a slow mutagenic process active in healthy tissue, and Signature (8), of unknown etiology.


Relapsed HGSC tumors harbor nearly double the predicted expressed neoantigen burden of primary samples, but mutations associated with chemotherapy signatures account for only a small part of this increase. The mutagenic processes responsible for most neoantigens are similar between primary and relapse samples. Our analyses are based on mutations detectable from whole genome sequencing of bulk samples and do not account for neoantigens present in small populations of cells.

Keywords: cancer, neoantigens, mutation signature, platinum chemotherapy, somatic mutations


Many chemotherapies including platinum compounds (Hannan 1989), cyclophosphamide (Anderson 1995), and etoposide (Nakanomyo 1986) exert their effect through DNA damage, and recent studies have found evidence for chemotherapy-induced mutations in post-treatment acute myeloid leukaemia (Ding 2012), glioma (Johnson 2013), and esophageal adenocarcinoma (Murugaesu 2015). Successful development of immune checkpoint-mediated therapy(Chen 2013) has focused attention on the importance of T cell responses to somatic mutations in coding genes that generate neoantigens (Schumacher 2015). Studies based on bulk-sequencing of tumor samples followed by computational peptide-class I MHC affinity prediction (Lundegaard 2007) have suggested that tumors with more mutations and predicted mutant MHC I peptide ligands are more likely to respond to checkpoint blockade immunotherapy (Allen 2015, Rizvi 2015). Ovarian cancers fall into an intermediate group of solid tumors in terms of mutational load present in pre-treatment surgical samples(Lawrence 2013). However, the effect of standard chemotherapy regimes on tumor mutation burden and resulting neoantigen expression in ovarian cancer is poorly understood.

Investigators associated with the Australian Ovarian Cancer Study (AOCS) performed whole genome and RNA sequencing of 79 pre-treatment and 35 post-treatment cancer samples from 92 HGSC patients, including 12 patients with both pre- and post-treatment samples (Patch 2015). The samples were obtained from solid tissue resections, autopsies, and ascites drained to relieve abdominal distension. Treatment regimes varied but primary treatment always included platinum-based chemotherapy. In their analysis, Patch et al. reported that post-treatment samples harbored more somatic mutations than pre-treatment samples and exhibited evidence of chemotherapy-associated mutations. Here we extend these results by quantifying the mutations and predicted neoantigens attributable to chemotherapy-associated mutational signatures. We find that, while neoantigen expression increases after treatment and relapse, only a small part of the increase is due to mutations associated with chemotherapy signatures.


Clinical sample information

We grouped the AOCS samples into three sets — “primary/untreated,” “primary/treated,” and “relapse/treated” — according to collection time point and chemotherapy exposure. The primary/untreated group consists of 75 primary debulking surgical samples and 4 samples of drained ascites. The primary/treated group consists of 5 primary debulking surgical samples obtained from patients pretreated with chemotherapy prior to surgery (neoadjuvant chemotherapy). The relapse/treated group consists of 24 relapse or recurrence ascites samples, 5 metastatic samples obtained in autopsies of two patients, and 1 solid tissue relapse surgical sample, all of which were obtained after prior exposure to one or more lines of chemotherapy. In summary, these groupings yield 79 primary/untreated samples, 5 primary/treated samples, and 30 relapse/