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The role of mass spectrometry-based serum proteomics signatures in predicting clinical outcomes in cancer patients treated with immune checkpoint inhibitors(ICI)Background Although immune checkpoint inhibitors (ICI) have changed the therapeutic scheme for multiple cancers, only a subset of patients experiences durable benefit. As current tumor markers such as PD-L1 show limited reliability in predicting clinical outcomes, we have explored the predictive role of markers representative of the host immune response on a systemic level present in the circulating proteome. Mass spectrometry allows for analysis of the proteome without the specific identification of individual proteins and protein isoforms. Here, we analyzed the most recent studies using mass spectrometry-based serum proteomics in predicting response to ICI treatment. Method A systematic literature search on Pubmed and major oncology scientific meetings was conducted up to November 18, 2020. Result Classifier algorithms trained with data sets from advanced stages of lung cancer (Primary Immune Response, Host Immune Classifier) and melanoma (BDX008, Immune Checkpoint Blockade) were used to stratify patients into groups with favorable and unfavorable treatment outcome. Patients with unfavorable predictive markers had worse prognosis when treated with ICI-single agent therapy. For patients treated with ICI alone or with chemotherapy as frontline or beyond, mass spectrometry-based serum proteomic signatures were shown to be a reliable predictive marker for survival outcomes (hazard ratios 0.15-0.5) independent of PD-L1 expression level. Conclusion Mass spectrometry-based serum proteomic tests reliably identify patients expected to have a worse prognosis. These patients can benefit from frontline aggressive treatment strategy combining ICI and chemotherapy rather than the standard of care ICI monotherapy. Cancer type Advanced stage NSCLCTreatmentLine of therapyClassifiernumber of patients included (n)number of patients in each classifier, n(%)Survival outcome (OS, month)HR [95%CI]referenceAdvanced stage NSCLCImmunotherapy (nivolumab)2nd linePIR116Not resistant75 (65%)17.30.48 [0.30-0.77], p=0.002Mirte Muller, et al.Resistant41(35%)6.0Sensitive32 (28%)11.10.58 [0.38-0.87], p=0.009Not sensitive84 (72%)4.3Immunotherapy ± ChemotherapyAll lines First line single agent immunotherapy (pembrolizumab) First line Combination (immunotherapy/chemotherapy) All lineHIC284Hot196 (69%)Not reached0.38 [0.27-0.53], p Citation Format: Yoonhee Choi, Jin Young Hwang, Won Kyung Hur, Myungwoo Nam, Leeseul Kim, Yeun Ho Lee, William Cheng, Eugene Kim, Emma Yu, Chan Mi Jung, William Han Bae, Young Kwang Chae. The role of mass spectrometry-based serum proteomics signatures in predicting clinical outcomes in cancer patients treated with immune check point inhibitors (ICI) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 673.

Background: Immune checkpoint inhibitor (ICI) treatment became the new treatment paradigm of a wide spectrum of cancers in the last decade. However, overcoming unresponsiveness to ICI remains an important high unmet need in the field of immuno-oncology. It is unclear whether another ICI can be an effective treatment option in patients with tumors refractory to combinatorial immunotherapy. Here we describe a case in whom a significant response to a PD-L1 inhibitor was demonstrated when used concurrently with radiation therapy. Notably, this patient was found to be unresponsive to the combined ICI treatment of PD-1 and CTLA-4 inhibitors. Case Presentation: A 42 y.o. male patient who presented with urinary frequency and hematospermia was diagnosed with stage IV small cell neuroendocrine cancer of prostate gland with osseous metastasis. He was treated with cisplatin plus etoposide for 4 cycles and was subsequently treated with topotecan for 4 cycles given progression of disease (PD). He was given the combination of ipilimumab and nivolumab after another PD. Treatment was discontinued 5 months later due to a lack of response. Two months later, the patient received radiation therapy: 3000 cGy to the prostate and lower pelvis and palliative radiation therapy to the left femur. The patient subsequently underwent multiple lines of treatment with no satisfactory response. Follow up imaging test was concerning for progression with new liver and lung lesions. The treatment was switched to atezolizumab and nab-paclitaxel combination regimen. Concurrently, the patient had stereotactic ablative radiotherapy (4000 cGy) to pelvic region, paraspinal region and para-aortic LNs. Repeated imaging test after two months of the treatment showed an increase in pulmonary nodule size and the treatment was continued despite PD. The repeated scan after 6 weeks revealed an exceptional response that was close to resolution of the metastasized lesion in the liver and significant decrease in size of pulmonary metastatic lesions. Conclusion:This case illustrates the abscopal effect of targeted radiation treatment when coupled with immunotherapy. Exceptional responses seen in non-radiated lesions including lungs and liver after radiation to pelvic lymph nodes while on PD-L1 inhibitors corroborates the concept of synergistic effect of radiation and immunotherapy. Intriguingly, this concurrent treatment approach maximizing the abscopal effect was effective in this case where combinatorial immunotherapy with nivolumab and ipilimumab was ineffective. Future clinical trials are warranted to validate these findings in a more systematic fashion. Citation Format: Leeseul Kim, William Cheng, Yeun Ho Lee, Myungwoo Nam, Won Kyung Hur, Jin Young Hwang, Yoonhee Choi, William H Bae, Cyra Y. Kang, Heayoon Shauna Cho, Emma Yu, Chan Mi Jung, Eugene Kim, Christmann Low, Young Kwang Chae. Exceptional response to PD-L1 inhibitor after radiation therapy in a patient with small cell neuroendocrine tumor of the prostate gland refractory to combination treatment with PD-1 and CTLA-4 inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 678.

We aimed to understand how TGF-β signaling pathway related gene mutation affects the tumor neoantigen burden and immune landscape in uterine corpus endometrial carcinoma (UCEC). cBioPortal was queried to obtain the UCEC The Cancer Genome Atlas (TCGA) cohort data (521 patients). TGF-β signaling pathway related gene mutation was defined as genetic variances in TGFBR1, TGFBR2, ACVR2A, ACVR1B, SMAD2, SMAD3, or SMAD4. The neoantigen counts were predicted using CloudNeo pipeline. CIBERSORT was used to predict tumor-infiltrating immune cells. In 521 UCEC patients, 124 had mutations in TGF-β signaling pathway related genes. These tumors with the mutations had significantly higher neoantigen counts, mutation counts, and cytolytic scores (a geometric mean of mRNA expression of perforin and granzyme), and a trend towards higher PD-L1 expression level (Table 1). When subdivided by molecular subtypes, similar patterns were seen in most groups. TGF-β signaling pathway gene mutation was significantly associated with tumor tissue infiltration by CD8 T cells (18.3% vs 10.5%; p< 0.05), active CD4 memory T cells(13.0% vs 7.5%; p Immune landscape of endometrial carcinoma according to TGF-β pathway related gene mutationnumber of valuesneoantigenmutation countcytolytic scorePD-L1 expressionAll521166.1964.5189.914.1TGF-β pathway related gene nonmutated39652.3219.415813.4TGF-β pathway related gene mutated124528.4**3350.0**293.2*16.3POLEmutAll85741.04925268.619.0nonmutated28158.9941.6183.517.7mutated571027.0**6881.0**310.4*19.6MSI-HAll167297.51455.0251.814.8nonmutated99157.1539.5207.714.7mutated68501.9**2787.0**315.915.0P53abnAll192134.7904.1202.616.8nonmutated14820.390.8142.215.6mutated44519.3**3640.0**407.218.5NSMPAll16111.5254.9131.59.7nonmutated15411.554.6133.39.6mutated712.960.491.612.1Values are expressed as mean.*p Citation Format: William H. Bae, Jin Young Hwang, Won Kyung Hur, Myungwoo Nam, Yoonhee Choi, Leeseul Kim, Yeun Ho Lee, William Cheng, Eugene Kim, Emma Yu, Chan Mi Jung, Heayoon S. Cho, Jeff Chuang, Victor Wang, Young Kwang Chae. Immune landscape of endometrial carcinoma and its association with neoantigen landscape and TGF-β signaling pathway related genes mutation status [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 451.

Background: Within serous ovarian cancer (SOC), high-grade serous carcinoma (HGSC) demonstrates a worse prognosis compared to low-grade serous carcinoma (LGSC). Molecular analysis of SOC has revealed a distinct pattern of mutations found between the two pathologic subtypes, with TP53 as the main driver for HGSC. We analyzed the neoantigen and immune landscape of different SOC subtypes according to pathological grades and mutation status. Methods: The analysis was done using the SOC cohort of The Cancer Genome Atlas (TCGA). The neoantigen prediction was done through the CloudNeo pipeline. CIBERSORT was applied to derive the tumor-infiltrating immune cells. Patients were grouped by their pathological grades (high vs. low) and the molecular features (type 1 vs. 2). For further subgroup analysis, high-grade samples were stratified by their TP53 mutation status. Results: Among 585 SOC patients, a subset of 254 patients with available mutation counts and predicted neoantigen counts were included. There was no significant difference in neoantigen count between low and high grades (median 50.50 vs. 62.50, p=0.84). However, there was a trend for differential numbers in the neoantigen count between type 1 and type 2 (median 29 vs. 66.50, p=0.07). No notable differences were detected in immune landscapes of low vs. high grade and type 1 vs. type 2. Conclusions: Our study is the first to describe the neoantigen and immune landscape of SOC. There were no significant differences in the immune landscape between the subtypes. It seems that molecular subtyping is more related to neoantigen differences than histologic subtyping. It is likely that the neoantigen differences are not defined by the histologic grade but rather by molecular trait. The immunologic characteristics of EMT low and high SOCNumber of ptientsNeoantigen countp-valueMutation countp-valueCytolytic scorep-valuePD-L1 expressionp-valueLow grade1250.500.84700.8757.120.4812.340.28High grade8062.5085.571.0919.66Type 117290.07114.60.98125.10.7824.940.77Type 222066.50115.3119.526.3High grade(TP53 wild type)744.000.06620.08163.20.0629.770.5High grade(TP53 mutated)7364.0086110.126.47TCGA cohort provided the data of low(GB, G1, G2) and high(G3, G4) grade SOCsType 1: Defined as mutations in KRAS, BRAF, PTEN, PIK3CA, CTNNB1 and ARID1A irrespective of histologic gradeType 2: Defined as mutation in TP53 irrespective of histologic gradeThe samples that had intersecting mutations were excluded in type 1 and type 2.The cytolytic activity score was defined as a geometric mean of mRNA expression of perforin and granzyme. Citation Format: Won Kyung Hur, Jin Young Hwang, Leeseul Kim, Myungwoo Nam, William H. Bae, Yoonhee Choi, Yeun Ho Lee, William Cheng, Heayoon S. Cho, Emma Yu, Chan Mi Jung, Eugene Kim, Christmann Low, Victor Wang, Jeff Chuang, Young Kwang Chae. The neoantigen and immune landscape of low and high grade serous ovarian cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 453.

TP53-mutation is a poor prognostic marker for uterine corpus endometrial carcinoma (UCEC). TGF-β is known to promote tumor progression via immune suppression, particularly NK and T cell-mediated cytotoxicity, in the tumor microenvironment. We aimed to analyze the impact of TGF-β signaling pathway-related gene mutation on the immune landscape and survival outcomes in TP53-mutated UCEC patients. cBioPortal was queried to obtain the UCEC The Cancer Genome Atlas cohort data (TCGA, 529 patients). The neoantigen counts were predicted using the CloudNeo pipeline. Survival outcomes were compared in the TGF-β signaling pathway-related gene mutated group, which were defined as genetic variances in TGFBR1, TGFBR2, ACVR2A, ACVR1B, SMAD2, SMAD3, or SMAD4, and the TGF-β signaling pathway-related gene non-mutated group. The cytolytic activity score was defined as a geometric mean of mRNA expression of perforin and granzyme. The duration of overall survival and disease-free survival were also obtained from cBioPortal. Out of the 529 UCEC patients, 192(36.3%) cancer tissues with TP53 mutations were analyzed for this study. 44 patients (22.9%) had more than one mutation in their TGF-β signaling pathway-related genes. TGF-β signaling pathway-related gene mutated group, when compared to a non-mutated group, was associated with significantly increased neoantigen counts (519.3 vs. 20.34 ; p Citation Format: William H. Bae, Jin Young Hwang, Won Kyung Hur, Myungwoo Nam, Yoonhee Choi, Leeseul Kim, Yeun Ho Lee, William Cheng, Eugene Kim, Emma Yu, Chan Mi Jung, Jeff Chuang, Victor Wang, Young Kwang Chae. TGF-β signaling pathway-related gene mutations are associated with increased neoantigen counts, enhanced cytolytic activity, and improved survival outcomes in TP53-mutated endometrial carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 452.