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Supplementary Tables 1-13

Supplementary Figure from Dietary Lactobacillus-Derived Exopolysaccharide Enhances Immune-Checkpoint Blockade Therapy

Microbes and their byproducts have been reported to regulate host health and immune functions. Here we demonstrated that microbial exopolysaccharide produced by Lactobacillus delbrueckii subsp. bulgaricus OLL1073R-1 (EPS-R1) induced CCR6+ CD8+ T cells of mice and humans. In mice, ingestion of EPS-R1 augmented antitumor effects of anti–CTLA-4 or anti–PD-1 monoclonal antibody against CCL20-expressing tumors, in which infiltrating CCR6+ CD8+ T cells were increased and produced IFNγ accompanied by a substantial immune response gene expression signature maintaining T-cell functions. Of note, the antitumor adjuvant effect of EPS-R1 was also observed in germ-free mice. Furthermore, the induction of CCR6 expression was mediated through the phosphorylated structure in EPS-R1 and a lysophosphatidic acid receptor on CD8+ T cells. Overall, we find that dietary EPS-R1 consumption induces CCR6+ CD8+ T cells in Peyer's patches, favoring a tumor microenvironment that augments the therapeutic effect of immune-checkpoint blockade depending on CCL20 production by tumors.Significance:Gut microbiota- and probiotic-derived metabolites are attractive agents to augment the efficacy of immunotherapies. Here we demonstrated that dietary consumption of Lactobacillus-derived exopolysaccharide induced CCR6+ CD8+ T cells in Peyer's patches and improved the tumor microenvironment to augment the therapeutic effects of immune-checkpoint blockade against CCL20-producing tumors.See related commentary by Di Luccia and Colonna, p. 1189.This article is highlighted in the In This Issue feature, p. 1171

Supplementary Table from Dietary Lactobacillus-Derived Exopolysaccharide Enhances Immune-Checkpoint Blockade Therapy

Supplementary Table Legends and Information, Supplementary Figures 1-11

Correlations of gene expression with IFN-gamma and IFN-gamma-inducible immune suppressive molecules in the tumor.

Tumors commonly harbor multiple genetic alterations, some of which initiate tumorigenesis. Among these, some tumor-specific somatic mutations resulting in mutated protein have the potential to induce antitumor immune responses. To examine the relevance of the latter to immune responses in the tumor and to patient outcomes, we used datasets of whole-exome and RNA sequencing from 97 clear cell renal cell carcinoma (ccRCC) patients to identify neoepitopes predicted to be presented by each patient's autologous HLA molecules. We found that the number of nonsilent or missense mutations did not correlate with patient prognosis. However, combining the number of HLA-restricted neoepitopes with the cell surface expression of HLA or β2-microglobulin(β2M) revealed that an A-neohi/HLA-Ahi or ABC-neohi/β2Mhi phenotype correlated with better clinical outcomes. Higher expression of immune-related genes from CD8 T cells and their effector molecules [CD8A, perforin (PRF1) and granzyme A (GZMA)], however, did not correlate with prognosis. This may have been due to the observed correlation of these genes with the expression of other genes that were associated with immunosuppression in the tumor microenvironment (CTLA-4, PD-1, LAG-3, PD-L1, PD-L2, IDO1, and IL10). This suggested that abundant neoepitopes associated with greater antitumor effector immune responses were counterbalanced by a strongly immunosuppressive microenvironment. Therefore, immunosuppressive molecules should be considered high-priority targets for modulating immune responses in patients with ccRCC. Blockade of these molecular pathways could be combined with immunotherapies targeting neoantigens to achieve synergistic antitumor activity. Cancer Immunol Res; 4(5); 463–71. ©2016 AACR.

HLA-restricted neoepitopes and expression of HLA/B2M

Microbes and their byproducts have been reported to regulate host health and immune functions. Here we demonstrated that microbial exopolysaccharide produced by Lactobacillus delbrueckii subsp. bulgaricus OLL1073R-1 (EPS-R1) induced CCR6+ CD8+ T cells of mice and humans. In mice, ingestion of EPS-R1 augmented antitumor effects of anti–CTLA-4 or anti–PD-1 monoclonal antibody against CCL20-expressing tumors, in which infiltrating CCR6+ CD8+ T cells were increased and produced IFNγ accompanied by a substantial immune response gene expression signature maintaining T-cell functions. Of note, the antitumor adjuvant effect of EPS-R1 was also observed in germ-free mice. Furthermore, the induction of CCR6 expression was mediated through the phosphorylated structure in EPS-R1 and a lysophosphatidic acid receptor on CD8+ T cells. Overall, we find that dietary EPS-R1 consumption induces CCR6+ CD8+ T cells in Peyer's patches, favoring a tumor microenvironment that augments the therapeutic effect of immune-checkpoint blockade depending on CCL20 production by tumors.Significance:Gut microbiota- and probiotic-derived metabolites are attractive agents to augment the efficacy of immunotherapies. Here we demonstrated that dietary consumption of Lactobacillus-derived exopolysaccharide induced CCR6+ CD8+ T cells in Peyer's patches and improved the tumor microenvironment to augment the therapeutic effects of immune-checkpoint blockade against CCL20-producing tumors.See related commentary by Di Luccia and Colonna, p. 1189.This article is highlighted in the In This Issue feature, p. 1171

Environmental carcinogenic exposures are major contributors to global disease burden yet how they promote cancer is unclear. Over 70 years ago, the concept of tumour promoting agents driving latent clones to expand was first proposed. In support of this model, recent evidence suggests that human tissue contains a patchwork of mutant clones, some of which harbour oncogenic mutations, and many environmental carcinogens lack a clear mutational signature. We hypothesised that the environmental carcinogen

An 80-year-old man with a history of cutaneous squamous cell carcinoma (SCC) was referred to our department for a solitary lung nodule. The nodule was surgically resected and diagnosed as SCC. Because the lung lesion and a previous skin lesion showed similar histological findings, the origin of the lung tumor was uncertain. Next-generation sequencing using a targeted driver oncogene panel was applied for the further examination. The lung lesion was diagnosed as primary lung SCC, as the two tumors possessed distinct somatic mutations in TP53. Recent advances in clinical sequencing have enabled us to obtain an accurate diagnosis in pathologically challenging cases.

Introduction: Programmed cell death-1 (PD-1) inhibitors effectively treat NSCLC and prolong survival. Robust biomarkers for predicting clinical benefits of good response and long survival with anti–PD-1 therapy have yet to be identified; therefore, predictive biomarkers are needed to select patients with benefits. Methods: We conducted a prospective study to explore whether serum antibody against NY-ESO-1 and/or XAGE1 cancer-testis antigens predicted primarily good clinical response and secondarily long survival with anti–PD-1 therapy for NSCLC. The serum antibody was detected by enzyme-linked immunosorbent assay, and tumor immune microenvironment and mutation burden were analyzed by immunohistochemistry and next-generation sequencing. Results: In the discovery cohort (n ¼ 13), six antibodypositive NSCLC cases responded to anti–PD-1 therapy (two complete and four partial responses), whereas seven antibody-negative NSCLC cases did not. Antibody positivity was associated with good response and survival, regardless of tumor programmed death ligand 1 (PD-L1) expression, mutation burden, and CD8þ T-cell infiltration. In the validation cohort (n ¼ 75), 17 antibody-positive NSCLC cases responded well to anti–PD-1 therapy as compared with 58 negative NSCLC cases (objective response rate 65% versus 19%, p ¼ 0.0006) and showed significantly prolonged progression-free survival and overall survival. Antibody titers highly correlated with tumor reduction rates. In the multivariate analysis, response biomarkers were tumor programmed death ligand 1 expression and antibody positivity, and only antibody positivity was a significantly better predictive biomarker of progression-free survival (hazard ratio ¼ 0.4, p ¼ 0.01) and overall survival (hazard ratio ¼ 0.2, p ¼ 0.004). Conclusions: Our results suggest that NY-ESO-1 and/or XAGE1 serum antibodies are useful biomarkers for predicting clinical benefits in anti–PD-1 therapy for NSCLC and probably for other cancers., This work was supported by grants from JSPS KAKENHI (15K09235, 16K18463, 16K21533, 18K15226, and 18K07306) to Drs. Oka, Ohue, and Kurose; by grants from the Takeda Science Foundation to Drs. Ohue and Kurose; by a grant from the Medical Research Encouragement Prize of The Japan Medical Association to Dr. Ohue; by a grant from the Okayama Health Foundation to Dr. Ohue; and by grants from Kawasaki Medical School to Drs. Oka, Ohue, and Kurose. Dr. Oka received collaborative research funds from the University of Tokyo and Thyas Co., Ltd. The Department of Immuno-Oncology is endowed by Pole Star Co., Ltd.

Patients with lung cancer with a history of treatment often undergo curative surgical resection. However, the impact of previous cancer treatment on the outcome of lung cancer remains unclear.We conducted a retrospective study of patients who underwent curative resection for non-small cell lung cancer between 1998 and 2011. We collected clinicopathologic data and patients were divided into groups by previous history of cancer treatment. Comparisons between groups, estimation of survival rates, and multivariate analyses were performed. Propensity score matching was used to create cohorts with reduced bias.Of 878 patients, 196 (22.3%) had previous extrathoracic malignancies, and stage I lung cancer was more frequent in this group (P.001). In multivariate analysis of the whole cohort, older patients, men, non-adenocarcinoma histologic type, more advanced pathologic stage of lung cancer, interstitial pneumonia, and previous extrathoracic malignancies were associated with appreciably worse prognosis. When propensity score matched cohorts were compared, prognosis was significantly worse in patients with previous extrathoracic malignancies than patients without (5-year survival rates, 75.3% vs 82.7%; P = .009), although recurrence was not frequently seen (5-year recurrence-free rates, 78.7% vs 83.0%; P = .491).Because treatment history of extrathoracic malignancy was not associated with postsurgical lung cancer recurrence, proposing curative resection could be justifiable if the previous cancer is deemed cured or controlled. However, the results showing that patients with previous cancer history have a worse survival rate than patients without should be taken into account when curative surgery is considered.

Histologic growth patterns are associated with patient prognosis, thus recognized as an important part of the WHO classification in lung adenocarcinoma (Travis et al. 2015, Moreira et al., 2020). The wide spectrum of growth patterns proves challenging for reproducible and quantitative scoring. Currently, scoring is based on manual identification of the predominant pattern and percentages of patterns in routine diagnostic slides. The lack of an automated method also limits our ability to investigate the immune microenvironment of growth patterns. To overcome the above challenges, we present a deep learning method, Pyramid Stream Networks, to precisely segment growth patterns at pixel level. Unlike existing methods, the proposed method captures different spatial scales of the histology information by novel attention strategies at different learning stages. This problem-oriented design yields precise boundaries for each pattern, enabling the investigation of growth pattern heterogeneity, and the relationship with tumor microenvironment components. Experiments were conducted on 49 haematoxylin and eosin whole slide images (WSIs) from TRACERx 100 cohort (AbdulJabbar et al., 2020). Each WSI was sparsely annotated by 3 senior pathologists. A total of 2968 annotated patches were split into 5 folds for cross validation. We compared our method with two state-of-the-art methods applied in semantic segmentation, attention U-net (Oktay et al. 2018) and DeepLabV3+ (Chen et al. 2018). When evaluated at patch level, our method outperformed the better comparison method, DeepLabV3+, by 3.43% and 2.99% in pixel-wise Dice and overall precision (OP) (Dice: 60.34% vs. 56,91%, OP: 65.43% vs. 62.44%). When applied to WSIs, the model correctly predicted the predominant pattern for 38 out of 49 samples, achieving an accuracy of 77.55%. Interestingly, in the 11 discordant cases, 10 showed high intra-tumor heterogeneity of growth patterns, measured by Shannon diversity, highlighting the impact of intra-tumor heterogeneity on growth pattern assessment. Additionally, we combined the identified growth patterns with lymphocytic distribution measured in (AbdulJabbar et al., 2020) and revealed a significantly increased immune infiltration in proximity to the solid pattern as compared to others, which is in line with previous findings (Tavernari et al., 2021). In summary, by leveraging image-analysis and artificial intelligence techniques, we propose a new method for precise growth pattern segmentation from routine histology samples of lung adenocarcinoma. It provides quantitative and reproducible scores of growth patterns, which can be developed into a decision support system for pathologists and clinicians. Furthermore, through pattern-specific spatial mapping, it enables future studies of intra-tumor heterogeneity, such as the preferential infiltration of lymphocyte subsets adjacent to diverse growth patterns. Citation Format: Xiaoxi Pan, Hanyun Zhang, Anca-Ioana Grapa, Khalid AbdulJabbar, Shan E. Ahmed Raza, HO KWAN ALVIN CHEUNG, Takahiro Karasaki, John Le Quesne, David A. Moore, Charles Swanton, Yinyin Yuan. Precise segmentation of growth patterns in TRACERx lung adenocarcinoma [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 5055.

Background: The adaptive immune system plays an important role in tumor evolution. A key source of cytotoxic T cell response in cancer is neoantigens, cancer cell specific mutations that result in mutant peptides that elicit a T cell mediated immune response. However, a mutation can only engender a neoantigen if the associated mutant peptide is presented to T cells by HLA molecules, and, as such, transcriptional repression or loss of the HLA genes can have important implications for immune evasion. Methods: We elucidate allele specific genomic and transcriptomic disruption to class I and II HLA genes. In whole exome sequencing (WES) data, our new tool (LOHHLA2.0) assesses loss of heterozygosity (LOH) status and somatic mutations. In RNA sequencing (RNAseq) data, LOHHLA2.0 quantifies allele specific expression and transcriptional repression referencing matched tumor adjacent normal samples. We applied LOHHLA2.0 to the TRACERx421 dataset, including 1554 WES tumor regions from 421 patients and 941 RNAseq regions from 357 tumor patients, 96 of which also had RNAseq from tumor adjacent normal samples. Results: We find that our method is more accurate than existing tools (RSEM) at calling gene level expression, e.g. in HLA-DPB1, RSEM under-calls HLA expression by a factor of two. 36% of TRACERx421 primary tumors harbored HLA LOH of at least one class I HLA gene, validating our previous findings in the TRACERx100 cohort. Strikingly, we found that 74% (71/96) of primary tumors with matched tumor adjacent normal tissue exhibited transcriptional repression of one or more class I HLA alleles, and 81% (78/96) exhibited class II allele transcriptional repression. Class I HLA transcriptional repression was more likely to occur subclonally than LOH. In a subset of tumors, we observed convergence upon disruption of the same allele through alternative mechanisms; with genomic loss in one tumor region and transcriptional repression in another region of the same tumor. Across the tumor regions, we found a concordance between HLA expression and immune infiltrate levels, with immune hot tumors exhibiting higher HLA class I expression. Conclusions: In this study, we find significant disruption to class I and II HLA expression adding to the diversity of immune evasion processes evident in early stage treatment naive NSCLC. Citation Format: Clare Puttick, Oriol Pich, Michelle Leung, Carlos Martinez-Ruiz, Robert Bentham, Rachel Rosenthal, Sonya Hessey, James R. Black, Emilia L. Lim, Katey Enfield, Emma Colliver, Krijn Dijkstra, Crispin T. Hiley, Takahiro Karasaki, Ariana Huebner, Maise Al Bakir, Thomas B. Watkins, Alexander M. Frankell, Simone Zaccaria, Mariam Jamal-Hanjani, Nicholas McGranahan, Charles Swanton. Pervasive allele specific transcriptional repression of the class I and II HLA genes in TRACERx non-small cell lung 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 1394.

Introduction: High dimensional imaging approaches such as imaging mass cytometry (IMC) are becoming widely used in cancer research. Such methods allow simultaneous observation of many cell types and their functional states and can provide valuable spatial information on cancer disease states when applied to clinical tissue samples. For example, in-situ immune and tumor cell interactions can be interrogated in their spatial context within the tumor microenvironment (TME). Analysis methods for the resultant complex data are not well formalized, and bespoke methods are usually required to fully capitalize on the underlying richness of information made available by IMC. Deep learning [DL] approaches, while highly accurate for other imaging modalities, have been slow to be adopted in IMC, as public resources for deep learning tasks in IMC are not abundant. Methods: We developed multiple DL and ML-based analysis pipelines for the following tasks in IMC data processing: [1] nucleus and necrotic tissue segmentation, [2] quantitative nuclear and cellular morphometry, [3] identification of cell type-specific niches. We applied these protocols to images and derived single cell spatial data from the TRACERx IMC cohort (n=81 non-small cell lung cancer patients, 561 images). Results: [1] We created a 120 image, 46,000+ labelled nucleus segmentation dataset for IMC data with representative images from lung adenocarcinoma, squamous cell carcinoma and other tissues. We achieved state-of-the-art performance in nuclear instance segmentation using a custom U-net++ neural network architecture trained using this dataset, which we benchmarked against traditional image processing methods, as well as publicly available deep learning architectures. Subsequently, we exploited transfer learning to retrain this model on a restricted dataset of labelled necrotic domains, which produced predictions in good agreement with independent pathologist assessment. [2] We developed an IMC morphometry pipeline utilizing ML-informed partitions of nuclear and cellular shape descriptors through which we performed cell-type specific morphometric characterization of all mapped cells in the non-small cell lung cancer TME, and which enabled a comparative analysis of the morphometries of each distinct cellular phenotype. [3] We established a high throughput density-based spatial clustering pipeline capable of identifying locally enriched niches of a given cell type of interest, as well as probing the composition and phenotypes of other cells within these niches. Conclusions: These approaches enhanced the quality as well as the breadth of spatial information derivable from TRACERx IMC data. Applying such tools to other clinical and pre-clinical datasets can improve our understanding of the spatial organization of cells both in non-small cell lung cancer and other cancer types. Citation Format: Alastair Magness, Katey Enfield, Mihaela Angelova, Emma Colliver, Emer Daly, Kristiana Grigoriadis, Claudia Lee, Oriol Pich, Philip Hobson, Dina Levi, Takahiro Karasaki, David Moore, Julian Downward, Erik Sahai, Mariam Jamal-Hanjani, Charles Swanton, TRACERx Consortium. Machine learning-enhanced image and spatial analytic pipelines for imaging mass cytometry applied to the TRACERx non-small cell lung cancer study [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 1926.

Murine tissues harbour signature, resident γδ T cell compartments with profound yet differential impacts on carcinogenesis. γδ T cell knockout mice have heightened susceptibility to carcinogenesis. However, it is now clear in the murine setting that IFNγ-producing γδ T cells reject tumours whilst IL-17-producing γδ T cells promote them. Nonetheless, many human γδ T cell compartments are distinct from that in mice and vice versa. The extent to which human tissues and tumours harbour resident γδ T cells, their effector function and their role in cancer is less clear. Although a large scale in silico study of 5000+ patients with cancer found that intratumoural γδ T cells were the most important correlate of survival, smaller studies have found that these cells to be associated with either survival or progression. Many historical studies have however been limited by the availability of technologies to rigorously identify, isolate, and examine tissue-resident γδ T cells. To address these issues, we present data from stage I-III non-small cell lung cancers and paired non-tumour (NT) tissue obtained at primary surgery from 25 patients enrolled in the TRACERx Study. Using flow cytometry and quantitative T cell receptor sequencing, we demonstrate that NT lung tissues harbour a resident population of Vδ1 γδ T cells, entirely distinct to blood. Compared with NT lung tissues, resident-memory and effector-memory Vδ1 T cells are enriched in tumours. RNA sequencing revealed that intratumoural Vδ1 T cells are skewed towards cytolysis and T-helper-1 functions, akin to intratumoural NK and CD8+ T cells. Importantly, we found no evidence of T-helper-17 skew that has been implicated in tumour promotion in murine models. Ongoing remission after surgery was significantly associated with the presence of CD103+ tissue-resident Vδ1 T cells in non-malignant lung tissues and the presence of CD45RA-/CD27+ effector-memory Vδ1 T cells in tumours. Moreover, patients with a greater proportion of intratumoural Vδ1 T cell clones shared with paired NT tissues were more likely to remain in remission, consistent with the cells’ proposed immunosurveillance function in steady state epithelial tissues. Whilst immunotherapies modulating αβ T cells have been successful for some patients, including those with non-small cell lung cancer, clinical trials of γδ T cells have so far demonstrated poor efficacy in solid cancers. These trials have hitherto exclusively utilised Vδ2 T cells, a subset which is found predominantly in peripheral blood and more commonly associated, albeit still rarely, with IL-17 production. The first-in-human clinical trial of Vδ1 T cell immunotherapy has just opened for patients with acute myeloid leukaemia. Thus, our findings have immediate translational relevance and support the utilisation of these as-yet-untapped Vδ1 T cells in solid cancer immunotherapy. Citation Format: Yin Wu, Dhruva Biswas, Ieva Usaite, Angelova Mihaela, Stefan Boeing, Takahiro Karasaki, Selvaraju Veeriah, Justyna Czyzewska-Khan, James Reading, Andrew Georgiou, Maise Al-Bakir, Nicholas McGranahan, Mariam Jamal-Hanjani, Allan Hackshaw, TRACERx Consortium, Sergio Quezada, Adrian Hayday, Charles Swanton. V-delta-1 T cells are resident in the human lung and associate with survival in patients with non-small cell lung cancer in the TRACERx Study [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 5636.

BackgroundNot all non-small cell lung cancer (NSCLC) patients possess drug-targetable driver mutations, and response rates to immune checkpoint blockade therapies also remain unsatisfactory. Therefore, more effective treatments are still needed. Here, we report the results of a phase 2 clinical trial of adoptive cell therapy using zoledronate-expanded autologous Vγ9Vδ2 T-cells for treatment-refractory NSCLC.MethodsNSCLC patients who had undergone at least two regimens of standard chemotherapy for unresectable disease or had had at least one treatment including chemotherapy or radiation for recurrent disease after surgery were enrolled in this open-label, single-arm, multicenter, phase 2 study. After preliminary testing of Vγ9Vδ2 T-cell proliferation, autologous peripheral blood mononuclear cells were cultured with zoledronate and IL-2 to expand the Vγ9Vδ2 T-cells. Cultured cells (>1×109) were intravenously administered every 2 weeks for six injections. The primary endpoint of this study was progression-free survival (PFS), and secondary endpoints included overall survival (OS), best objective response rate (ORR), disease control rate (DCR), safety and immunomonitoring. Clinical efficacy was defined as median PFS significantly >4 months.ResultsTwenty-five patients (20 adenocarcinoma, 4 squamous cell carcinoma and 1 large cell carcinoma) were enrolled. Autologous Vγ9Vδ2 T-cell therapy was administered to all 25 patients, of which 16 completed the foreseen course of 6 injections of cultured cells. Median PFS was 95.0 days (95% CI 73.0 to 132.0 days); median OS was 418.0 days (179.0–479.0 days), and best overall responses were 1 partial response, 16 stable disease (SD) and 8 progressive disease. ORR and DCR were 4.0% (0.1%–20.4%) and 68.0% (46.5%–85.1%), respectively. Severe adverse events developed in nine patients, mostly associated with disease progression. In one patient, pneumonitis and inflammatory responses resulted from Vγ9Vδ2 T-cell infusions, together with the disappearance of a massive tumor.ConclusionsAlthough autologous Vγ9Vδ2 T-cell therapy was well tolerated and may have an acceptable DCR, this trial did not meet its primary efficacy endpoint.Trial registration numberUMIN000006128

A standard treatment for patients with early-stage non-small cell lung cancer (NSCLC) who undergo surgery, and subsequently develop local failure or intrathoracic oligo-recurrence, has not yet been established. The present study aimed to assess the feasibility of stereotactic body radiotherapy (SBRT) for this subgroup of patients. Consequently, a retrospective analysis was conducted of patients with NSCLC recurrence who were treated with SBRT, and previously underwent curative surgical resection between October 2011 and October 2016. Post-SBRT survival [overall survival (OS); progression-free survival (PFS); and local control (LC)] and toxicity were analyzed. Prognostic factors for OS were identified using univariate and multivariate analysis. A total of 52 patients and 59 tumors were analyzed. The median follow-up time was 25 months (35 months for surviving patients), and median OS following salvage SBRT was 32 months. The 1- and 3-year OS rates were 84.4 and 67.8%, respectively. 1- and 3-year PFS rates were 80.8 and 58.7%, respectively. Only 4 patients (7.7%) developed local failure. Median LC was 71 months and 1- and 3-year LC rate were 97.9 and 94.9%, respectively. A total of 4 patients experienced grade 3 or higher adverse events (AEs) and two experienced grade 5 AEs (pneumonitis and hemoptysis). Central tumor location and the possibility of re-operation were independent prognostic factors for OS. The present study indicated that post-operative salvage SBRT is a promising therapeutic option for patients with NSCLC with locoregional or intrathoracic oligo-recurrence. We regard toxicity was also acceptable. However, further research is required on the appropriate selection of subjects, and stratification of the analysis by certain risk factors would increase the accuracy of the conclusions.

Treatment with molecular targeted agents together with immune checkpoint inhibitors will most likely improve the efficacy of current cancer immunotherapy. Because molecular targeted agents not only directly affect cancer cells, but also influence immune cells and modulate the tumor microenvironment, a better understanding of the overall immunological effects of these drugs will contribute to the rational design of combination therapies. Therefore, this study performed extensive immune monitoring of patients' peripheral blood mononuclear cells (PBMCs) to investigate the immunological effects of the molecular targeted agents sunitinib, everolimus and temsirolimus, which have been widely used for the treatment of renal cell carcinoma (RCC). Immunophenotyping and functional analysis of PBMCs revealed that these molecular targeted agents exerted different immunological effects on patients with RCC. Sunitinib decreased the percentage of early‑stage myeloid‑derived suppressor cells (eMDSCs) and increased natural killer cells, but did not affect the phenotypes and effector functions of CD4+ or CD8+ T cells. Everolimus decreased effector regulatory T cells, but also decreased IL‑2‑producing CD4+ T cells and increased dysfunctional CD8+ T cells. Conversely, temsirolimus decreased programmed cell death protein 1+CD8+ T cells and eMDSCs, but increased interferon‑γ and tumor necrosis factor‑α double producers at the same time as decreasing dysfunctional CD8+ T cells, albeit not significantly. In conclusion, although everolimus and temsirolimus are mTOR inhibitors, their effects on overall T‑cell functions are very different. Therefore, although it may increase the risk of immune‑related toxicity, temsirolimus is expected to offer the best outcome when combined with other immunomodulators for the development of cancer immunotherapy.

Objectives A better understanding of antitumor immunity will help predict the prognosis of gastric cancer patients and tailor the appropriate therapies in each patient. Therefore, we propose a novel immunological classification of gastric cancer. Methods We performed whole‐exome sequencing (WES), RNA‐Seq and flow cytometry in 29 gastric cancer patients who received surgery. The TCGA data set of 323 gastric cancer patients and RNA‐Seq data of 45 patients who received pembrolizumab (Kim et al. Nat Med 2018; 24: 1449–1458) were also analysed. Results Immunogram analysis of cancer–immunity interaction of gastric cancer revealed immune signatures of four main types, designated Hot1, Hot2, Intermediate and Cold. Immunologically hot tumors displayed a dysfunctional T‐cell signature, while cold tumors had an exclusion signature. Ex vivo tumor‐infiltrating lymphocyte analysis documented T‐cell dysfunction with the expression of checkpoint molecules and impaired cytokine production. The T‐cell function was more profoundly damaged in Hot1 than Hot2 tumors. Patients in Hot2 subtypes had better survival in our cohort and TCGA cohort. Although these immunological subtypes overlapped to some degree with the molecular subtypes in the TCGA, intratumoral immune responses cannot be predicted solely based on histological or molecular subtyping of gastric cancer. Molecular and immunological classifications complement each other to predict the responses to anti‐PD‐1 therapy and have the potential to be a biomarker for the treatment of gastric cancer. Conclusion The immunological classification of gastric cancer resulted in four subtypes. Hot tumors were further divided into two subtypes, between which the functional status of T cells was different., In this study, an integrative immunogenomic analysis of gastric cancer was performed. The immunological classification of gastric cancer resulted in immune signatures of four main types, designated Hot1, Hot2, Intermediate and Cold, in which the functional status of T cells was different. Early administration of anti‐PD‐1 therapy might be recommended for patients with Hot1 tumors.

Physical biomarkers to stratify patients with lung cancer into subtypes predictive of outcome beyond tumor-related characteristics are underexplored. This study was designed to investigate the clinical utility of preoperative sarcopenia based on respiratory strength and pectoralis muscle mass to predict the risk of death.This retrospective study included 346 consecutive patients undergoing curative-intent resection of non-small cell lung cancer from 2009 to 2013. Respiratory strength and muscle mass were assessed by peak expiratory flow rate and pectoralis muscle index (pectoralis muscle area/body mass index) using preoperative spirometry and chest axial images, respectively. Sarcopenia cutoff points were defined by gender-specific medians of peak expiratory flow rates and pectoralis muscle indices. Survival was compared between patients with sarcopenia and patients without.Sarcopenia was present in 98 patients (28.3%) and was significantly associated with advancing age (P .001). Patients with sarcopenia exhibited worse 5-year overall survival compared with patients without sarcopenia (69.9% vs 87.2%, P .001). Multivariate analysis revealed that sarcopenia was an independent adverse prognostic factor (hazard ratio, 1.88; 95% confidence interval, 1.09-3.24; P = .023) after adjustment for gender, age, smoking status, coronary heart disease, diffusing capacity for carbon monoxide, neutrophil-to-lymphocyte ratio, albumin, histologic type, and pathologic stage.Preoperative sarcopenia as identified by the criteria of low respiratory strength and reduced pectoralis muscle mass is significantly associated with poor overall survival. This may help to develop more individualized management strategies and optimize longitudinal care for patients.

The importance of neoantigens for cancer immunity is now well‐acknowledged. However, there are diverse strategies for predicting and prioritizing candidate neoantigens, and thus reported neoantigen loads vary a great deal. To clarify this issue, we compared the numbers of neoantigen candidates predicted by four currently utilized strategies. Whole‐exome sequencing and RNA sequencing (RNA‐Seq) of four non‐small‐cell lung cancer patients was carried out. We identified 361 somatic missense mutations from which 224 candidate neoantigens were predicted using MHC class I binding affinity prediction software (strategy I). Of these, 207 exceeded the set threshold of gene expression (fragments per kilobase of transcript per million fragments mapped ≥1), resulting in 124 candidate neoantigens (strategy II). To verify mutant mRNA expression, sequencing of amplicons from tumor cDNA including each mutation was undertaken; 204 of the 207 mutations were successfully sequenced, yielding 121 mutant mRNA sequences, resulting in 75 candidate neoantigens (strategy III). Sequence information was extracted from RNA‐Seq to confirm the presence of mutated mRNA. Variant allele frequencies ≥0.04 in RNA‐Seq were found for 117 of the 207 mutations and regarded as expressed in the tumor, and finally, 72 candidate neoantigens were predicted (strategy IV). Without additional amplicon sequencing of cDNA, strategy IV was comparable to strategy III. We therefore propose strategy IV as a practical and appropriate strategy to predict candidate neoantigens fully utilizing currently available information. It is of note that different neoantigen loads were deduced from the same tumors depending on the strategies applied.

Introduction Two strategies for selecting neoantigens as targets for non–small cell lung cancer vaccines were compared: (1) an “off-the-shelf” approach starting with shared mutations extracted from global databases and (2) a personalized pipeline using whole-exome sequencing data on each patient’s tumor. Methods The Catalogue of Somatic Mutations in Cancer database was used to create a list of shared missense mutations occurring in more than 1% of patients. These mutations were then assessed for predicted binding affinity to HLA alleles of 15 lung cancer patients, and potential neoantigens (pNeoAgs) for each patient were selected on this basis. In the personalized approach, pNeoAgs were selected from missense mutations detected by whole-exome sequencing of the patient’s own samples. Results The list of shared mutations included 22 missense mutations for adenocarcinoma and 18 for squamous cell carcinoma (SCC), resulting in a median of 10 off-the-shelf pNeoAgs for each adenocarcinoma (range 5–13) and 9 (range 5–12) for each SCC. In contrast, a median of 59 missense mutations were identified by whole-exome sequencing (range 33–899) in adenocarcinoma and 164.5 (range 26–232) in SCC. This resulted in a median of 46 pNeoAgs (range 13–659) for adenocarcinoma and 95.5 (range 10–145) for SCC in the personalized set. We found that only one or two off-the-shelf pNeoAgs were included in the set of personalized pNeoAgs—and then in only three patients, with no overlap seen in the remaining 12 patients. Conclusions Use of an off-the-shelf pipeline is feasible but may not be satisfactory for most patients with non–small cell lung cancer. We recommend identifying personal mutations by comprehensive genome sequencing for developing neoantigen-targeted cancer immunotherapies.

Traditional classifications of gastric cancer are based on gross appearance, anatomical sites, histological types, and etiologies. Recent advances in NGS technologies have made comprehensive molecular characterizations of gastric cancer possible. Four subtypes were proposed by the TCGA project, namely, EBV, MSI, GS, and CIN. These molecular subtypes are clinically relevant and contribute to the stratification of patients for targeted therapies and immunotherapies. However, understanding the landscape of the tumor-immune microenvironment is critical for improving the efficacy of current immunotherapies or developing novel combination immunotherapies. To this end, we performed whole-exome sequencing, RNA-Seq, and flow cytometry in 29 patients with primary gastric adenocarcinomas. We focused on factors related to the cancer-immunity cycle and tumor cell proliferation and metabolism using 9 selected gene sets, innate immunity, priming and activation, T cells, IFNγ response, inhibitory molecules, Tregs, recognition of tumor cells, proliferation, and glycolysis. By integrating them, we generated an immunogram for each patient to visualize the state of cancer-immune system interactions and have investigated the tumor-immune microenvironment in gastric cancer. Our results demonstrate that the anti-tumor immune response in gastric cancer is heterogeneous. Based on Immunogram analysis, the hierarchical clustering of gastric cancers from 29 patients resulted in 4 novel immunological subtypes, designated Hot 1, Hot 2, Intermediate, and Cold. Hot 1 and Hot 2 were distinguished from one another by glycolysis, which was low in the latter. These immunological subtypes overlapped to some degree with the molecular subtypes in the TCGA. All 4 MSI tumors in our cohort were included in the Hot 1 group, and all 3 EBV tumors in the Hot 2 group, whereas 4 of the 6 mesenchymal tumors fell into the Intermediate group. Immunologically hot tumors displayed a dysfunctional T cell signature, while cold tumors had an exclusion signature. We also determined the phenotypes and functions ex vivo of tumor-infiltrating T cells by flow cytometry. T cell dysfunction was confirmed by documenting very low percentages of polyfunctional CD8+ T cells producing ≥2 of the cytokines IFNγ, TNFα and IL-2 in the Hot 1 subtype. T cell function was entirely lacking in 2 of 11 Cold subtype tumors. These dysfunctional T cells could be recoverable in most patients if appropriate signals are supplied or immunosuppressive signals blocked. Applying our immunogram analysis to the TCGA cohort also resulted in its classification into four subtypes, validating the overlap between molecular and immunological subtypes. Overall survival in patients with a Hot 1 tumor was worse than for Hot 2 subtypes under conventional therapy not including checkpoint blockade, suggesting that early administration of anti-PD-1 therapy should be recommended for patients with Hot 1 tumors. Citation Format: Yasuyoshi Sato, Ikuo Wada, Akihiro Hosoi, Yukari Kobayashi, Koji Nagaoka, Takahiro Karasaki, Hirokazu Matsushita, Koichi Yagi, Hiroharu Yamashita, Shunji Takahashi, Yasuyuki Seto, Kazuhiro Kakimi. Novel immunological classification of gastric cancer by integrative analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2050.

Background: Only a fraction of non-small cell lung cancer (NSCLC) patients possess targetable driver mutations, and the response rates of immune checkpoint blockades are still unsatisfactory. Therefore, the development of more effective therapies is needed for treatment-refractory NSCLC. We conducted a phase I clinical study of autologous γδ T cell therapy for NSCLC patients and reported safety and feasibility. Here, we report the result of phase II clinical trial of adoptive γδ T cell transfer therapy for treatment-refractory NSCLC patients. Methods: Patients with NSCLC who had undergone at least two regimens of standard chemotherapy for unresectable disease or who had undergone at least one treatment including chemotherapy or radiation for recurrent disease after surgery were enrolled in this open-label, single-arm, multicenter, phase II study. After preliminary testing of γδ T cell proliferative capacity, mononuclear cells of the patient collected by peripheral blood leukapheresis were cultured with zoledronic acid and IL-2. Expanded autologous γδ T cells (>1 × 109) were transferred intravenously every two weeks for a total of six injections. If the patient perceived some clinical benefit, the patient could continue further treatments until the disease became progressive. The primary endpoint of this study was progression-free survival (PFS), and the secondary endpoints included overall survival (OS), best objective response rate (ORR), disease control rate (DCR), and safety. The clinical efficacy of the treatment was determined if the median PFS is significantly longer than 3 months. Results: Autologous γδ T cell therapy was given for 25 patients, and 16 patients completed the 6 courses of the treatment. Among the 25 patients, 20 had adenocarcinoma, 4 squamous cell carcinoma and 1 large cell carcinoma. The median PFS was 95.0 days (95% CI 73.0-132.0 days). The median OS was 418.0 days (179.0-479.0 days). The best overall responses were 1 partial response (PR), 16 stable disease (SD) including 4 patients whose time to progression was longer than 180 days, and 8 progressive disease (PD). ORR and DCR were 4.0% (0.1-20.4%) and 68.0% (46.5-85.1%), respectively. Severe adverse events (SAE) were developed in 9 patients during the study, including pleural effusion, anorexia, cough, dyspnea, respiratory failure, pneumonitis, ascites, tumor pain, and intracranial hemorrhage. Most of them were associated with disease progression; however, a case of pneumonitis was related to γδ T cell therapy. Conclusion: Although the trial did not meet its primary efficacy endpoint, the results of this study indicate that autologous γδ T cell therapy was well tolerated and may have an acceptable disease control rate. Considering the unique mechanism of action towards tumor cells, γδ T cell therapy may be a candidate counterpart of combination therapy for treatment-refractory NSCLC. Citation Format: Kazuhiro Kakimi, Hirokazu Matsushita, Takamichi Izumi, Keita Masuzawa, Takahiro Karasaki, Shinnosuke Ikemura, Kentaro Kitano, Ichiro Kawata, Tadashi Manabe, Tomohiro Takehara, Toshiaki Ebisudani, Kazuiro Nagayama, Hiroyuki Yasuda, Masaaki Sato, Kenzo Soejima, Jun Nakajima. Autologous γδ T cell therapy for treatment-refractory non-small-cell lung cancer: An open-label, single-arm, multicenter, phase II study [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1069.

BackgroundThere is increasing evidence for the benefit of poly ADP ribose polymerase (PARP) inhibitors in a subset of high-grade serous ovarian carcinoma (HGSC) patients, especially those with homologous recombination (HR)-deficient tumors. However, new treatment strategies, such as immune checkpoint inhibition, are required for patients with HR-proficient tumors.MethodsA total of 80 cases of HGSC were analyzed in this study. Whole exome and RNA sequencing was performed for these tumors. Methylation arrays were also carried out to examineBRCA1andRAD51Cpromoter methylation status. Mutations, neoantigen load, antigen presentation machinery, and local immune profile were investigated, and the relationships of these factors with clinical outcome were also analyzed.ResultsAs expected, the numbers of predicted neoAgs were lower in HR-proficient (n=46) than HR-deficient tumors (n=34). However, 40% of the patients with HR-proficient tumors still had higher than median numbers of neoAgs and better survival than patients with lower numbers of neoAgs. Incorporation of human leukocyte antigen (HLA)-class I expression status into the survival analysis revealed that patients with both high neoAg numbers and high HLA-class I expression (neoAghiHLAhi) had the best progression-free survival (PFS) in HR-proficient HGSC (p=0.0087). Gene set enrichment analysis demonstrated that the genes for effector memory CD8 T cells, TH1 T cells, the interferon-γ response, and other immune-related genes, were enriched in these patients. Interestingly, this subset of patients also had better PFS (p=0.0015) and a more T-cell-inflamed tumor phenotype than patients with the same phenotype (neoAghiHLAhi) in HR-deficient HGSC.ConclusionsOur results suggest that immune checkpoint inhibitors might be an alternative to explore in HR-proficient cases which currently do not benefit from PARP inhibition.

Limited success of immune-based therapies in glioma might be in part due to the lack of enough neoantigens (neoAgs) that can be targeted by immune effector cells. In addition, gliomas also show dynamic clonal evolution over time, possibly leading to immunoediting during progression. In this study, we evaluated neoAg expression change and its relation to immune microenvironment using matched primary and recurrent tumor samples from 25 glioma patients [8 IDH-wildtype glioblastoma (GBM), 9 IDH-mutant astrocytoma (LGG-A), and 8 oligodendroglioma (LGG-O)]. Predicted neoAgs (p-neoAgs) deriving from missense mutations were identified by whole-exome sequencing (WES) analysis and the MHC class I binding prediction algorism NetMHCpan2.8. Expressed neoAgs (e-neoAgs) among the p-neoAgs were determined by incorporating RNA sequencing (RNA-seq) data. The ratio of e-neoAgs to p-neoAgs (“neoAg expression ratio”) on each sample significantly decreased at recurrence (p = 0.003) and was particularly strong in neoAg with a higher affinity for MHC class I. Similar results were obtained for GBM, LGG-A, and LGG-O, when separately analyzed. RNA-seq-based differential gene expression analyses including gene ontology analysis and pair-designed gene set enrichment analysis illustrated that the cases with strongly reduced neoAg expression ratio compared to primary counterpart (top 8), but not those without (bottom 8), retained gene expression related to antigen presentation machinery and gained immune effector cells at recurrence. These in silicofindings were consistent with immunohistochemistry for CD8 and MHC class I on tumor samples. These data may suggest that the tumor cells with reduced neoAg expression survived at recurrence as a result of persistent anti-tumor immune responses in some gliomas under the standard treatment. Reduced neoAg expression and impaired APM during progression may play complementary roles in the immune evasion of gliomas.

Immune-based therapies have shown limited efficacy in glioma thus far. This might be at least in part due to insufficient numbers of neoantigens, thought to be targets of immune attack. In addition, we hypothesized that dynamic genetic and epigenetic tumor evolution in gliomas might also affect the mutation/neoantigen landscape and contribute to treatment resistance through immune evasion. Here, we investigated changes in the neoantigen landscape and immunologic features during glioma progression using exome and RNA-seq of paired primary and recurrent tumor samples obtained from 25 WHO grade II–IV glioma patients (glioblastoma, IDH-wild-type, n = 8; grade II–III astrocytoma, IDH-mutant, n = 9; and grade II–III oligodendroglioma, IDH-mutant, 1p/19q-codeleted, n = 8). The number of missense mutations, predicted neoantigens, or expressed neoantigens was not significantly different between primary and recurrent tumors. However, we found that in individual patients the ratio of expressed neoantigens to predicted neoantigens, designated the “neoantigen expression ratio,” decreased significantly at recurrence (P = 0.003). This phenomenon was particularly pronounced for “high-affinity,” “clonal,” and “passenger gene–derived” neoantigens. Gene expression and IHC analyses suggested that the decreased neoantigen expression ratio was associated with intact antigen presentation machinery, increased tumor-infiltrating immune cells, and ongoing immune responses. Our findings imply that decreased expression of highly immunogenic neoantigens, possibly due to persistent immune selection pressure, might be one of the immune evasion mechanisms along with tumor clonal evolution in some gliomas.

BACKGROUND: Limited success of immune-based therapies in glioma might be in part due to the lack of enough neoantigens (neoAgs) that can be targeted by immune effector cells. In addition, gliomas also show dynamic clonal evolution over time, possibly leading to immunoediting during progression. Here we conducted multiomics analysis on glioma primary and recurrent pair samples to evaluate temporal changes of glioma-immune system interactions and clarify the immune evasion mechanism characteristic of gliomas. MATERIALS AND METHODS: In total, 25 WHO grade II-IV glioma cases with primary and recurrent pair samples were enrolled [8 IDH-wildtype glioblastoma (GBM), 9 IDH-mutant astrocytoma (LGG-A), and 8 oligodendroglioma (LGG-O)]. All cases received only standard therapies, but not immunotheapies. Somatic missense mutations were identified by whole-exome sequencing. Predicted neoAgs (p-neoAgs) derived from missense mutations were identified based on the MHC class I binding prediction algorism NetMHCpan2.8. In addition, “expressed” neoAgs at mRNA levels (e-neoAgs) were specified according to RNA-seq data; the neoAg expression ratio of each sample was calculated by dividing e-neoAg count by p-neoAg. Differential gene expression analyses were performed using Gene Ontology (GO) analysis or pair-designed gene set enrichment analysis (GSEA) for the tumor-infiltrating leukocytes (TILs) and antigen presentation machinery (APM). Finally, immunohistochemistry (IHC) for CD8 and MHC class I on tumor samples was assessed for validation. RESULTS: Mutational load, p- and e-neoAg count did not significantly differ between primary and recurrent tumors. However, the neoAg expression ratio significantly decreased in recurrent tumors (p = 0.003) and was particularly strong in neoAgs with a higher affinity for MHC class I. Similar trends were demonstrated for GBM, LGG-A, and LGG-O, when analyzed separately. GO analysis revealed that a number of GO terms related to active immune response such as including “CXCR chemokine receptor binding” and “leukocyte migration” were significantly upregulated at recurrence in the cases with strongly reduced neoAg expression ratio (top 8 cases). In the same cases, GSEA for TILs demonstrated a few subpopulations including activated CD8+ T cells significantly increased at recurrence. On the other hand, several TIL subpopulations as well as many APM-related gene sets significantly depleted in those with less significantly reduced neoAg expression ratio (bottom 8). These findings were consistent with those of IHC for CD8 and MHC class I. CONCLUSION: These data may suggest that the tumor cells with reduced neoAg expression survived at recurrence as a result of persistent anti-tumor immune responses in some cases under the standard treatment. Reduced neoAg expression and impaired APM during progression may play complementary roles in the immune evasion of gliomas.

Background: Clinical trials of anti-CCR4 antibody for solid cancers with or without other immune-modulating agents including immune checkpoint blockade therapy are currently underway. However, little is known about the roles of CCR4 + lymphocytes and their prognostic impact in lung cancer. We hypothesized that high CCR4 expression in the tumor microenvironment would be associated with a poor prognosis and would act as a biomarker in lung adenocarcinoma. Methods: First, the prognostic impact of CCR4 gene expression was explored using pooled data from public transcriptomic databases with online survival analysis software. Second, tissue microarrays (TMAs) were constructed from resected lung adenocarcinoma specimens from tumors up to 3 cm in size. The density of CCR4 + lymphocytes infiltrating the tumor was then assessed by immunohistochemistry and related to survival. Confounding factors were controlled for by multivariate analysis using the Cox proportional hazards model. Results: Higher than median expression of the CCR4 gene was identified as an independent poor prognostic factor for overall survival (OS) by multivariate analysis of 720 lung adenocarcinoma patients in the public databases [HR =1.55 (95% CI: 1.03–2.35), P=0.037]. Consistent with this, high CCR4 + tumor-infiltrating lymphocyte (TIL) density was found to be an independent poor prognostic factor for both OS [HR =2.24 (1.01–5.34), P=0.049] and recurrence-free survival (RFS) [HR =2.20 (1.16–4.39), P=0.017] in the patients from whom TMA were obtained (n=180). Age, male gender, predominantly non-lepidic histological subtype, nodal involvement, and low CD8 + TIL density were also independent poor prognostic factors. However, FOXP3 gene expression and Foxp3 + lymphocyte infiltration did not possess any prognostic value in either study. Conclusions: High CCR4 expression in the tumor microenvironment may be a poor prognostic factor in lung adenocarcinoma. Patients with high CCR4 + lymphocyte infiltration may have a poor prognosis and thus be suitable candidates for clinical trials of anti-CCR4 antibody treatment.

Objectives Depletion in skeletal muscle is closely associated with limited physical ability and high mortality. In this study, we evaluated the prognostic significance of skeletal muscle depletion in patients with early-stage non-small-cell lung cancer. Methods A retrospective analysis of patients with pathological stages I-II lung cancer, who underwent curative resection between 2009 and 2013, was conducted. The truncal muscle index (TMI) (area/height2) at the first lumbar vertebral level was measured by preoperative axial computed tomography. Overall survival and recurrence-free survival were compared between the lowest gender-specific quartile of the TMI and the other quartiles. Results A total of 314 subjects were included in the study. The cumulative 5-year recurrence-free and overall survival rates were significantly shorter in patients with lower TMIs (69% vs 83.5%, P = 0.028; 64.8% vs 80.1%, P = 0.003, respectively). In multivariable models, the TMI was identified as an independent prognostic factor for overall survival (P = 0.017, hazard ratio 1.84, 95% confidence interval 1.12-3.05), after adjusting for age, gender, preoperative serum albumin, carcinoembryonic antigen, neutrophil to lymphocyte ratio and pathological stage. Conclusions A low preoperative TMI was associated with a poor postoperative outcome in patients with early-stage non-small-cell lung cancer. This factor may be included in the preoperative assessment of patients, for whom surgical intervention is considered.

Neoantigens derived from tumor-specific somatic mutations are excellent targets for anti-tumor immune responses. In ovarian clear cell carcinoma (OCCC), checkpoint blockade yields durable responses in a subset of patients. To approach the question of why only some patients respond, we first investigated neoantigen loads and immune signatures using exome sequencing and expression array data for 74 OCCC patients treated conventionally. Neither the number of missense mutations nor total predicted neoantigens assessed in the tumor correlated with clinical outcomes. However, the number of neoantigens per missense mutation (“neoAg frequency”) did correlate with clinical outcomes. Cox multivariate regression analysis demonstrated that low neoAg frequencies correlated with increased progression-free survival (PFS) and was an independent predictive factor for PFS in OCCC (p = 0.032), especially at stage I-II (p = 0.0045). Immunity-associated genes including those related to effector memory CD8 T cells were dominantly expressed in tumors with low neoAg frequencies in stage I-II patients, suggesting CD8 T cell-mediated elimination of immunogenic sub-clones expressing neoantigens (immunoediting) had occurred. In contrast, we observed decreased HLA-A, -B, and -C expression (p = 0.036, p = 0.026, and p = 0.030, respectively) as well as increased ratios of CTLA-4, PD-1, Tim-3, and LAG3 to CD8A expression (p = 0.0064, p = 0.017, p = 0.033 and p = 0.0136, respectively) in stage I-II tumors with high neoAg frequencies. Constrained anti-tumor immunity may thus result in limited immunoediting, and poor prognosis. Our results show that neoAg frequency in OCCC is an independent prognostic factor for clinical outcome and may become a potential candidate biomarker for immunomodulatory agent-based treatments.

Introduction The interaction of immune cells and cancer cells shapes the immunosuppressive tumor microenvironment. For successful cancer immunotherapy, comprehensive knowledge of antitumor immunity as a dynamic spatiotemporal process is required for each individual patient. To this end, we developed an immunogram for the cancer-immunity cycle by using next-generation sequencing. Methods Whole exome sequencing and RNA sequencing were performed in 20 patients with NSCLC (12 with adenocarcinoma, seven with squamous cell carcinoma, and one with large cell neuroendocrine carcinoma). Mutated neoantigens and cancer germline antigens expressed in the tumor were assessed for predicted binding to patients' human leukocyte antigen molecules. The expression of genes related to cancer immunity was assessed and normalized to construct a radar chart composed of eight axes reflecting seven steps in the cancer-immunity cycle. Results Three immunogram patterns were observed in patients with lung cancer: T-cell–rich, T-cell–poor, and intermediate. The T-cell–rich pattern was characterized by gene signatures of abundant T cells, regulatory T cells, myeloid-derived suppressor cells, checkpoint molecules, and immune-inhibitory molecules in the tumor, suggesting the presence of antitumor immunity dampened by an immunosuppressive microenvironment. The T-cell–poor phenotype reflected lack of antitumor immunity, inadequate dendritic cell activation, and insufficient antigen presentation in the tumor. Immunograms for both the patients with adenocarcinoma and the patients with nonadenocarcinoma tumors included both T-cell–rich and T-cell–poor phenotypes, suggesting that histologic type does not necessarily reflect the cancer immunity status of the tumor. Conclusions The patient-specific landscape of the tumor microenvironment can be appreciated by using immunograms as integrated biomarkers, which may thus become a valuable resource for optimal personalized immunotherapy.

Aim: Around 50% of high-grade serous ovarian carcinomas (HGSC) have deficiency in homologous recombination (HR) pathways. There has been increased evidence of benefit for the use of poly ADP ribose polymerase (PARP) inhibitors in a group of HGSC patients who especially have HR-deficient tumors. Therefore, it is needed to develop a new treatment strategy for the rest, an HR-proficient tumor. The aim of this study is to investigate immunological background of HR-proficient HGSC by integrated molecular analysis to explore the subset that would become candidates for immunotherapy such as immune checkpoint inhibitors. Methods: In total, 80 cases of HGSC were analyzed in this study. Exome and RNA sequencing were performed to identify germline and somatic mutations. Methylation arrays were also carried out to evaluate BRCA1 and RAD51C promoter methylation status. Predicted neoantigens derived from mutations were identified based on the MHC class I binding prediction algorithm NetMHCpan 2.8. Immune profile in the tumor was assessed by differential gene expression analysis and gene set enrichment analysis (GSEA) using RNA sequencing data. Neoantigen load, antigen presentation, immune profile and their relevance to clinical outcomes were also investigated. Results: Either BRCA1/2, RAD51C/D mutations, or BRCA1, RAD51C promoter methylation was defined as HR-deficient. A total of 34 (42.5%) and 46 (57.5%) patients were classified as having HR-deficient and HR-proficient tumors, respectively. As expected, the numbers of predicted neoantigens were lower in HR-proficient than HR-deficient tumors (p Conclusions: The number of neoantigens and HLA-class I expression characterized a subset of HR-proficient HGSC with improved prognosis and immunologically hot phenotype. This subset might be a candidate target for immune checkpoint inhibitors rather than PARP inhibitors. Citation Format: Hirokazu Matsushita, Kosei Hasegawa, Katsutoshi Oda, Shogo Yamamoto, Kayo Asada, Akira Yabuno, Akira Nishijima, Takahiro Karasaki, Yuji Ikeda, Keiichi Fujiwara, Hiroyuki Aburatani, Kakimi Kazuhiro. Neoantigen load and HLA-class I expression characterize a subset of HR-proficient high-grade serous ovarian carcinomas with favorable prognosis and T cell-inflamed phenotype [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5721.