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1. Impact of Neoantigen Expression and T-Cell Activation on Breast Cancer Survival

   https://doi.org/10.3390/cancers13122879  

   Li, Wenjing; Amei, Amei; Bui, Francis; Norouzifar, Saba; Lu, Lingeng; Wang, Zuoheng (June 2021, Cancers)

   Neoantigens are derived from tumor-specific somatic mutations. Neoantigen-based synthesized peptides have been under clinical investigation to boost cancer immunotherapy efficacy. The promising results prompt us to further elucidate the effect of neoantigen expression on patient survival in breast cancer. We applied Kaplan–Meier survival and multivariable Cox regression models to evaluate the effect of neoantigen expression and its interaction with T-cell activation on overall survival in a cohort of 729 breast cancer patients. Pearson’s chi-squared tests were used to assess the relationships between neoantigen expression and clinical pathological variables. Spearman correlation analysis was conducted to identify correlations between neoantigen expression, mutation load, and DNA repair gene expression. ERCC1, XPA, and XPC were negatively associated with neoantigen expression, while BLM, BRCA2, MSH2, XRCC2, RAD51, CHEK1, and CHEK2 were positively associated with neoantigen expression. Based on the multivariable Cox proportional hazard model, patients with a high level of neoantigen expression and activated T-cell status showed improved overall survival. Similarly, in the T-cell exhaustion and progesterone receptor (PR) positive subgroups, patients with a high level of neoantigen expression showed prolonged survival. In contrast, there was no significant difference in the T-cell activation and PR negative subgroups. In conclusion, neoantigens may serve as immunogenic agents for immunotherapy in breast cancer. 

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2. Integrating genome-wide CRISPR immune screen with multi-omic clinical data reveals distinct classes of tumor intrinsic immune regulators

   https://doi.org/10.1136/jitc-2020-001819  

   Hou, Jiakai; Wang, Yunfei; Shi, Leilei; Chen, Yuan; Xu, Chunyu; Saeedi, Arash; Pan, Ke; Bohat, Ritu; Egan, Nicholas A.; McKenzie, Jodi A.; et al (February 2021, Journal for ImmunoTherapy of Cancer)

   null (Ed.)

   Background Despite approval of immunotherapy for a wide range of cancers, the majority of patients fail to respond to immunotherapy or relapse following initial response. These failures may be attributed to immunosuppressive mechanisms co-opted by tumor cells. However, it is challenging to use conventional methods to systematically evaluate the potential of tumor intrinsic factors to act as immune regulators in patients with cancer. Methods To identify immunosuppressive mechanisms in non-responders to cancer immunotherapy in an unbiased manner, we performed genome-wide CRISPR immune screens and integrated our results with multi-omics clinical data to evaluate the role of tumor intrinsic factors in regulating two rate-limiting steps of cancer immunotherapy, namely, T cell tumor infiltration and T cell-mediated tumor killing. Results Our studies revealed two distinct types of immune resistance regulators and demonstrated their potential as therapeutic targets to improve the efficacy of immunotherapy. Among them, PRMT1 and RIPK1 were identified as a dual immune resistance regulator and a cytotoxicity resistance regulator, respectively. Although the magnitude varied between different types of immunotherapy, genetically targeting PRMT1 and RIPK1 sensitized tumors to T-cell killing and anti-PD-1/OX40 treatment. Interestingly, a RIPK1-specific inhibitor enhanced the antitumor activity of T cell-based and anti-OX40 therapy, despite limited impact on T cell tumor infiltration. Conclusions Collectively, the data provide a rich resource of novel targets for rational immuno-oncology combinations. 

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3. Exploring Gut Microbiome in Predicting the Efficacy of Immunotherapy in Non-Small Cell Lung Cancer

   https://doi.org/10.3390/cancers14215401  

   Liu, Ben; Chau, Justin; Dai, Qun; Zhong, Cuncong; Zhang, Jun (November 2022, Cancers)

   We performed various analyses on the taxonomic and functional features of the gut microbiome from NSCLC patients treated with immunotherapy to establish a model that may predict whether a patient will benefit from immunotherapy. We collected 65 published whole metagenome shotgun sequencing samples along with 14 samples from our previous study. We systematically studied the taxonomical characteristics of the dataset and used both the random forest (RF) and the multilayer perceptron (MLP) neural network models to predict patients with progression-free survival (PFS) above 6 months versus those below 3 months. Our results showed that the RF classifier achieved the highest F-score (85.2%) and the area under the receiver operating characteristic curve (AUC) (95%) using the protein families (Pfam) profile, and the MLP neural network classifier achieved a 99.9% F-score and 100% AUC using the same Pfam profile. When applying the model trained in the Pfam profile directly to predict the treatment response, we found that both trained RF and MLP classifiers significantly outperformed the stochastic predictor in F-score. Our results suggested that such a predictive model based on functional (e.g., Pfam) rather than taxonomic profile might be clinically useful to predict whether an NSCLC patient will benefit from immunotherapy, as both the F-score and AUC of functional profile outperform that of taxonomic profile. In addition, our model suggested that interactive biological processes such as methanogenesis, one-carbon, and amino acid metabolism might be important in regulating the immunotherapy response that warrants further investigation. 

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4. Intracellular optical doppler phenotypes of chemosensitivity in human epithelial ovarian cancer

   https://doi.org/10.1038/s41598-020-74336-x  

   Li, Zhe; An, Ran; Swetzig, Wendy M.; Kanis, Margaux; Nwani, Nkechiyere; Turek, John; Matei, Daniela; Nolte, David (December 2020, Scientific Reports)

   null (Ed.)

   Abstract Development of an assay to predict response to chemotherapy has remained an elusive goal in cancer research. We report a phenotypic chemosensitivity assay for epithelial ovarian cancer based on Doppler spectroscopy of infrared light scattered from intracellular motions in living three-dimensional tumor biopsy tissue measured in vitro. The study analyzed biospecimens from 20 human patients with epithelial ovarian cancer. Matched primary and metastatic tumor tissues were collected for 3 patients, and an additional 3 patients provided only metastatic tissues. Doppler fluctuation spectra were obtained using full-field optical coherence tomography through off-axis digital holography. Frequencies in the range from 10 mHz to 10 Hz are sensitive to changes in intracellular dynamics caused by platinum-based chemotherapy. Metastatic tumor tissues were found to display a biodynamic phenotype that was similar to primary tissue from patients who had poor clinical outcomes. The biodynamic phenotypic profile correctly classified 90% [88–91% c.i.] of the patients when the metastatic samples were characterized as having a chemoresistant phenotype. This work suggests that Doppler profiling of tissue response to chemotherapy has the potential to predict patient clinical outcomes based on primary, but not metastatic, tumor tissue. 

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5. Targeting the Interplay between Epithelial-to-Mesenchymal-Transition and the Immune System for Effective Immunotherapy

   https://doi.org/10.3390/cancers11050714  

   Soundararajan, Rama; Fradette, Jared; Konen, Jessica; Moulder, Stacy; Zhang, Xiang; Gibbons, Don; Varadarajan, Navin; Wistuba, Ignacio; Tripathy, Debasish; Bernatchez, Chantale; et al (May 2019, Cancers)

   Over the last decade, both early diagnosis and targeted therapy have improved the survival rates of many cancer patients. Most recently, immunotherapy has revolutionized the treatment options for cancers such as melanoma. Unfortunately, a significant portion of cancers (including lung and breast cancers) do not respond to immunotherapy, and many of them develop resistance to chemotherapy. Molecular characterization of non-responsive cancers suggest that an embryonic program known as epithelial-mesenchymal transition (EMT), which is mostly latent in adults, can be activated under selective pressures, rendering these cancers resistant to chemo- and immunotherapies. EMT can also drive tumor metastases, which in turn also suppress the cancer-fighting activity of cytotoxic T cells that traffic into the tumor, causing immunotherapy to fail. In this review, we compare and contrast immunotherapy treatment options of non-small cell lung cancer (NSCLC) and triple negative breast cancer (TNBC). We discuss why, despite breakthrough progress in immunotherapy, attaining predictable outcomes in the clinic is mostly an unsolved problem for these tumors. Although these two cancer types appear different based upon their tissues of origin and molecular classification, gene expression indicate that they possess many similarities. Patient tumors exhibit activation of EMT, and resulting stem cell properties in both these cancer types associate with metastasis and resistance to existing cancer therapies. In addition, the EMT transition in both these cancers plays a crucial role in immunosuppression, which exacerbates treatment resistance. To improve cancer-related survival we need to understand and circumvent, the mechanisms through which these tumors become therapy resistant. In this review, we discuss new information and complementary perspectives to inform combination treatment strategies to expand and improve the anti-tumor responses of currently available clinical immune checkpoint inhibitors. 

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